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Sample records for ground segment overview

Figure-ground segmentation can occur without attention.

Science.gov (United States)

Kimchi, Ruth; Peterson, Mary A

2008-07-01

The question of whether or not figure-ground segmentation can occur without attention is unresolved. Early theorists assumed it can, but the evidence is scant and open to alternative interpretations. Recent research indicating that attention can influence figure-ground segmentation raises the question anew. We examined this issue by asking participants to perform a demanding change-detection task on a small matrix presented on a task-irrelevant scene of alternating regions organized into figures and grounds by convexity. Independently of any change in the matrix, the figure-ground organization of the scene changed or remained the same. Changes in scene organization produced congruency effects on target-change judgments, even though, when probed with surprise questions, participants could report neither the figure-ground status of the region on which the matrix appeared nor any change in that status. When attending to the scene, participants reported figure-ground status and changes to it highly accurately. These results clearly demonstrate that figure-ground segmentation can occur without focal attention.
Deficit in figure-ground segmentation following closed head injury.

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Baylis, G C; Baylis, L L

1997-08-01

Patient CB showed a severe impairment in figure-ground segmentation following a closed head injury. Unlike normal subjects, CB was unable to parse smaller and brighter parts of stimuli as figure. Moreover, she did not show the normal effect that symmetrical regions are seen as figure, although she was able to make overt judgments of symmetry. Since she was able to attend normally to isolated objects, CB demonstrates a dissociation between figure ground segmentation and subsequent processes of attention. Despite her severe impairment in figure-ground segmentation, CB showed normal 'parallel' single feature visual search. This suggests that figure-ground segmentation is dissociable from 'preattentive' processes such as visual search.
Noise destroys feedback enhanced figure-ground segmentation but not feedforward figure-ground segmentation

Science.gov (United States)

Romeo, August; Arall, Marina; Supèr, Hans

2012-01-01

Figure-ground (FG) segmentation is the separation of visual information into background and foreground objects. In the visual cortex, FG responses are observed in the late stimulus response period, when neurons fire in tonic mode, and are accompanied by a switch in cortical state. When such a switch does not occur, FG segmentation fails. Currently, it is not known what happens in the brain on such occasions. A biologically plausible feedforward spiking neuron model was previously devised that performed FG segmentation successfully. After incorporating feedback the FG signal was enhanced, which was accompanied by a change in spiking regime. In a feedforward model neurons respond in a bursting mode whereas in the feedback model neurons fired in tonic mode. It is known that bursts can overcome noise, while tonic firing appears to be much more sensitive to noise. In the present study, we try to elucidate how the presence of noise can impair FG segmentation, and to what extent the feedforward and feedback pathways can overcome noise. We show that noise specifically destroys the feedback enhanced FG segmentation and leaves the feedforward FG segmentation largely intact. Our results predict that noise produces failure in FG perception. PMID:22934028
The IXV Ground Segment design, implementation and operations

Science.gov (United States)

Martucci di Scarfizzi, Giovanni; Bellomo, Alessandro; Musso, Ivano; Bussi, Diego; Rabaioli, Massimo; Santoro, Gianfranco; Billig, Gerhard; Gallego Sanz, José María

2016-07-01

The Intermediate eXperimental Vehicle (IXV) is an ESA re-entry demonstrator that performed, on the 11th February of 2015, a successful re-entry demonstration mission. The project objectives were the design, development, manufacturing and on ground and in flight verification of an autonomous European lifting and aerodynamically controlled re-entry system. For the IXV mission a dedicated Ground Segment was provided. The main subsystems of the IXV Ground Segment were: IXV Mission Control Center (MCC), from where monitoring of the vehicle was performed, as well as support during pre-launch and recovery phases; IXV Ground Stations, used to cover IXV mission by receiving spacecraft telemetry and forwarding it toward the MCC; the IXV Communication Network, deployed to support the operations of the IXV mission by interconnecting all remote sites with MCC, supporting data, voice and video exchange. This paper describes the concept, architecture, development, implementation and operations of the ESA Intermediate Experimental Vehicle (IXV) Ground Segment and outlines the main operations and lessons learned during the preparation and successful execution of the IXV Mission.
Feed-forward segmentation of figure-ground and assignment of border-ownership.

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Hans Supèr

Full Text Available Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation. On the contrary, a role of feedforward projections in figure-ground segmentation is unknown. To have a better understanding of a role of feedforward connections in figure-ground organization, we constructed a feedforward spiking model using a biologically plausible neuron model. By means of surround inhibition our simple 3-layered model performs figure-ground segmentation and one-sided border-ownership coding. We propose that the visual system uses feed forward suppression for figure-ground segmentation and border-ownership assignment.
Feed-forward segmentation of figure-ground and assignment of border-ownership.

Science.gov (United States)

Supèr, Hans; Romeo, August; Keil, Matthias

2010-05-19

Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation. On the contrary, a role of feedforward projections in figure-ground segmentation is unknown. To have a better understanding of a role of feedforward connections in figure-ground organization, we constructed a feedforward spiking model using a biologically plausible neuron model. By means of surround inhibition our simple 3-layered model performs figure-ground segmentation and one-sided border-ownership coding. We propose that the visual system uses feed forward suppression for figure-ground segmentation and border-ownership assignment.
Running the figure to the ground: figure-ground segmentation during visual search.

Science.gov (United States)

Ralph, Brandon C W; Seli, Paul; Cheng, Vivian O Y; Solman, Grayden J F; Smilek, Daniel

2014-04-01

We examined how figure-ground segmentation occurs across multiple regions of a visual array during a visual search task. Stimuli consisted of arrays of black-and-white figure-ground images in which roughly half of each image depicted a meaningful object, whereas the other half constituted a less meaningful shape. The colours of the meaningful regions of the targets and distractors were either the same (congruent) or different (incongruent). We found that incongruent targets took longer to locate than congruent targets (Experiments 1, 2, and 3) and that this segmentation-congruency effect decreased when the number of search items was reduced (Experiment 2). Furthermore, an analysis of eye movements revealed that participants spent more time scrutinising the target before confirming its identity on incongruent trials than on congruent trials (Experiment 3). These findings suggest that the distractor context influences target segmentation and detection during visual search. Copyright © 2014 Elsevier B.V. All rights reserved.
Consistent interactive segmentation of pulmonary ground glass nodules identified in CT studies

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Zhang, Li; Fang, Ming; Naidich, David P.; Novak, Carol L.

2004-05-01

Ground glass nodules (GGNs) have proved especially problematic in lung cancer diagnosis, as despite frequently being malignant they characteristically have extremely slow rates of growth. This problem is further magnified by the small size of many of these lesions now being routinely detected following the introduction of multislice CT scanners capable of acquiring contiguous high resolution 1 to 1.25 mm sections throughout the thorax in a single breathhold period. Although segmentation of solid nodules can be used clinically to determine volume doubling times quantitatively, reliable methods for segmentation of pure ground glass nodules have yet to be introduced. Our purpose is to evaluate a newly developed computer-based segmentation method for rapid and reproducible measurements of pure ground glass nodules. 23 pure or mixed ground glass nodules were identified in a total of 8 patients by a radiologist and subsequently segmented by our computer-based method using Markov random field and shape analysis. The computer-based segmentation was initialized by a click point. Methodological consistency was assessed using the overlap ratio between 3 segmentations initialized by 3 different click points for each nodule. The 95% confidence interval on the mean of the overlap ratios proved to be [0.984, 0.998]. The computer-based method failed on two nodules that were difficult to segment even manually either due to especially low contrast or markedly irregular margins. While achieving consistent manual segmentation of ground glass nodules has proven problematic most often due to indistinct boundaries and interobserver variability, our proposed method introduces a powerful new tool for obtaining reproducible quantitative measurements of these lesions. It is our intention to further document the value of this approach with a still larger set of ground glass nodules.
The LOFT Ground Segment

DEFF Research Database (Denmark)

Bozzo, E.; Antonelli, A.; Argan, A.

2014-01-01

targets per orbit (~90 minutes), providing roughly ~80 GB of proprietary data per day (the proprietary period will be 12 months). The WFM continuously monitors about 1/3 of the sky at a time and provides data for about ~100 sources a day, resulting in a total of ~20 GB of additional telemetry. The LOFT...... Burst alert System additionally identifies on-board bright impulsive events (e.g., Gamma-ray Bursts, GRBs) and broadcasts the corresponding position and trigger time to the ground using a dedicated system of ~15 VHF receivers. All WFM data are planned to be made public immediately. In this contribution...... we summarize the planned organization of the LOFT ground segment (GS), as established in the mission Yellow Book 1 . We describe the expected GS contributions from ESA and the LOFT consortium. A review is provided of the planned LOFT data products and the details of the data flow, archiving...
Microstrip Resonator for High Field MRI with Capacitor-Segmented Strip and Ground Plane

DEFF Research Database (Denmark)

Zhurbenko, Vitaliy; Boer, Vincent; Petersen, Esben Thade

2017-01-01

) segmenting stripe and ground plane of the resonator with series capacitors. The design equations for capacitors providing symmetric current distribution are derived. The performance of two types of segmented resonators are investigated experimentally. To authors’ knowledge, a microstrip resonator, where both......, strip and ground plane are capacitor-segmented, is shown here for the first time....
LANDSAT-D ground segment operations plan, revision A

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Evans, B.

1982-01-01

The basic concept for the utilization of LANDSAT ground processing resources is described. Only the steady state activities that support normal ground processing are addressed. This ground segment operations plan covers all processing of the multispectral scanner and the processing of thematic mapper through data acquisition and payload correction data generation for the LANDSAT 4 mission. The capabilities embedded in the hardware and software elements are presented from an operations viewpoint. The personnel assignments associated with each functional process and the mechanisms available for controlling the overall data flow are identified.
Figure-ground segmentation based on class-independent shape priors

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Li, Yang; Liu, Yang; Liu, Guojun; Guo, Maozu

2018-01-01

We propose a method to generate figure-ground segmentation by incorporating shape priors into the graph-cuts algorithm. Given an image, we first obtain a linear representation of an image and then apply directional chamfer matching to generate class-independent, nonparametric shape priors, which provide shape clues for the graph-cuts algorithm. We then enforce shape priors in a graph-cuts energy function to produce object segmentation. In contrast to previous segmentation methods, the proposed method shares shape knowledge for different semantic classes and does not require class-specific model training. Therefore, the approach obtains high-quality segmentation for objects. We experimentally validate that the proposed method outperforms previous approaches using the challenging PASCAL VOC 2010/2012 and Berkeley (BSD300) segmentation datasets.
Fast and Accurate Ground Truth Generation for Skew-Tolerance Evaluation of Page Segmentation Algorithms

Directory of Open Access Journals (Sweden)

Okun Oleg

2006-01-01

Full Text Available Many image segmentation algorithms are known, but often there is an inherent obstacle in the unbiased evaluation of segmentation quality: the absence or lack of a common objective representation for segmentation results. Such a representation, known as the ground truth, is a description of what one should obtain as the result of ideal segmentation, independently of the segmentation algorithm used. The creation of ground truth is a laborious process and therefore any degree of automation is always welcome. Document image analysis is one of the areas where ground truths are employed. In this paper, we describe an automated tool called GROTTO intended to generate ground truths for skewed document images, which can be used for the performance evaluation of page segmentation algorithms. Some of these algorithms are claimed to be insensitive to skew (tilt of text lines. However, this fact is usually supported only by a visual comparison of what one obtains and what one should obtain since ground truths are mostly available for upright images, that is, those without skew. As a result, the evaluation is both subjective; that is, prone to errors, and tedious. Our tool allows users to quickly and easily produce many sufficiently accurate ground truths that can be employed in practice and therefore it facilitates automatic performance evaluation. The main idea is to utilize the ground truths available for upright images and the concept of the representative square [9] in order to produce the ground truths for skewed images. The usefulness of our tool is demonstrated through a number of experiments with real-document images of complex layout.
The Segmented Aperture Interferometric Nulling Testbed (SAINT) I: overview and air-side system description

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Hicks, Brian A.; Lyon, Richard G.; Petrone, Peter; Ballard, Marlin; Bolcar, Matthew R.; Bolognese, Jeff; Clampin, Mark; Dogoda, Peter; Dworzanski, Daniel; Helmbrecht, Michael A.; Koca, Corina; Shiri, Ron

2016-07-01

This work presents an overview of the Segmented Aperture Interferometric Nulling Testbed (SAINT), a project that will pair an actively-controlled macro-scale segmented mirror with the Visible Nulling Coronagraph (VNC). SAINT will incorporate the VNC's demonstrated wavefront sensing and control system to refine and quantify end-to-end high-contrast starlight suppression performance. This pathfinder testbed will be used as a tool to study and refine approaches to mitigating instabilities and complex diffraction expected from future large segmented aperture telescopes.
Effects of energy development on ground water quality: an overview and preliminary assessment

International Nuclear Information System (INIS)

Parker, W.M. III; Yin, S.C.L.; Davis, M.J.; Kutz, W.J.

1981-07-01

A preliminary national overview of the various effects on ground water quality likely to result from energy development. Based on estimates of present and projected energy-development activities, those regions of the country are identified where ground water quality has the potential for being adversely affected. The general causes of change in ground water quality are reviewed. Specific effects on ground water quality of selected energy technologies are discussed, and some case-history material is provided. A brief overview of pertinent legislation relating to the protection and management of ground water quality is presented. Six methodologies that have some value for assessing the potential effects on ground water quality of energy development activities are reviewed. A method of identifying regions in the 48 contiguous states where there is a potential for ground water quality problems is described and then applied
Space Shuttle Boundary Layer Transition Flight Experiment Ground Testing Overview

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Berger, Karen T.; Anderson, Brian P.; Campbell, Charles H.

2014-01-01

In support of the Boundary Layer Transition (BLT) Flight Experiment (FE) Project in which a manufactured protuberance tile was installed on the port wing of Space Shuttle Orbiter Discovery for STS-119, STS- 128, STS-131 and STS-133 as well as Space Shuttle Orbiter Endeavour for STS-134, a significant ground test campaign was completed. The primary goals of the test campaign were to provide ground test data to support the planning and safety certification efforts required to fly the flight experiment as well as validation for the collected flight data. These test included Arcjet testing of the tile protuberance, aerothermal testing to determine the boundary layer transition behavior and resultant surface heating and planar laser induced fluorescence (PLIF) testing in order to gain a better understanding of the flow field characteristics associated with the flight experiment. This paper provides an overview of the BLT FE Project ground testing. High-level overviews of the facilities, models, test techniques and data are presented, along with a summary of the insights gained from each test.
An Overview of Techniques for Cardiac Left Ventricle Segmentation on Short-Axis MRI

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Krasnobaev Arseny

2016-01-01

Full Text Available Nowadays, heart diseases are the leading cause of death. Left ventricle segmentation of a human heart in magnetic resonance images (MRI is a crucial step in both cardiac diseases diagnostics and heart internal structure reconstruction. It allows estimating such important parameters as ejection faction, left ventricle myocardium mass, stroke volume, etc. In addition, left ventricle segmentation helps to construct the personalized heart computational models in order to conduct the numerical simulations. At present, the fully automated cardiac segmentation methods still do not meet the accuracy requirements. We present an overview of left ventricle segmentation algorithms on short-axis MRI. A wide variety of completely different approaches are used for cardiac segmentation, including machine learning, graph-based methods, deformable models, and low-level heuristics. The current state-of-the-art technique is a combination of deformable models with advanced machine learning methods, such as deep learning or Markov random fields. We expect that approaches based on deep belief networks are the most promising ones because the main training process of networks with this architecture can be performed on the unlabelled data. In order to improve the quality of left ventricle segmentation algorithms, we need more datasets with labelled cardiac MRI data in open access.
Stereo visualization in the ground segment tasks of the science space missions

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Korneva, Natalia; Nazarov, Vladimir; Mogilevsky, Mikhail; Nazirov, Ravil

The ground segment is one of the key components of any science space mission. Its functionality substantially defines the scientific effectiveness of the experiment as a whole. And it should be noted that its outstanding feature (in contrast to the other information systems of the scientific space projects) is interaction between researcher and project information system in order to interpret data being obtained during experiments. Therefore the ability to visualize the data being processed is essential prerequisite for ground segment's software and the usage of modern technological solutions and approaches in this area will allow increasing science return in general and providing a framework for new experiments creation. Mostly for the visualization of data being processed 2D and 3D graphics are used that is caused by the traditional visualization tools capabilities. Besides that the stereo data visualization methods are used actively in solving some tasks. However their usage is usually limited to such tasks as visualization of virtual and augmented reality, remote sensing data processing and suchlike. Low prevalence of stereo visualization methods in solving science ground segment tasks is primarily explained by extremely high cost of the necessary hardware. But recently appeared low cost hardware solutions for stereo visualization based on the page-flip method of views separation. In this case it seems promising to use the stereo visualization as an instrument for investigation of a wide range of problems, mainly for stereo visualization of complex physical processes as well as mathematical abstractions and models. The article is concerned with an attempt to use this approach. It describes the details and problems of using stereo visualization (page-flip method based on NVIDIA 3D Vision Kit, graphic processor GeForce) for display of some datasets of magnetospheric satellite onboard measurements and also in development of the software for manual stereo matching.
Seismic fragility formulations for segmented buried pipeline systems including the impact of differential ground subsidence

Energy Technology Data Exchange (ETDEWEB)

Pineda Porras, Omar Andrey [Los Alamos National Laboratory; Ordaz, Mario [UNAM, MEXICO CITY

2009-01-01

Though Differential Ground Subsidence (DGS) impacts the seismic response of segmented buried pipelines augmenting their vulnerability, fragility formulations to estimate repair rates under such condition are not available in the literature. Physical models to estimate pipeline seismic damage considering other cases of permanent ground subsidence (e.g. faulting, tectonic uplift, liquefaction, and landslides) have been extensively reported, not being the case of DGS. The refinement of the study of two important phenomena in Mexico City - the 1985 Michoacan earthquake scenario and the sinking of the city due to ground subsidence - has contributed to the analysis of the interrelation of pipeline damage, ground motion intensity, and DGS; from the analysis of the 48-inch pipeline network of the Mexico City's Water System, fragility formulations for segmented buried pipeline systems for two DGS levels are proposed. The novel parameter PGV{sup 2}/PGA, being PGV peak ground velocity and PGA peak ground acceleration, has been used as seismic parameter in these formulations, since it has shown better correlation to pipeline damage than PGV alone according to previous studies. By comparing the proposed fragilities, it is concluded that a change in the DGS level (from Low-Medium to High) could increase the pipeline repair rates (number of repairs per kilometer) by factors ranging from 1.3 to 2.0; being the higher the seismic intensity the lower the factor.
Gaia Launch Imminent: A Review of Practices (Good and Bad) in Building the Gaia Ground Segment

Science.gov (United States)

O'Mullane, W.

2014-05-01

As we approach launch the Gaia ground segment is ready to process a steady stream of complex data coming from Gaia at L2. This talk will focus on the software engineering aspects of the ground segment. Of course in a short paper it is difficult to cover everything but an attempt will be made to highlight some good things, like the Dictionary Tool and some things to be careful with like computer aided software engineering tools. The usefulness of some standards like ECSS will be touched upon. Testing is also certainly part of this story as are Challenges or Rehearsals so they will not go without mention.

Generalization of Figure-Ground Segmentation from Binocular to Monocular Vision in an Embodied Biological Brain Model

Science.gov (United States)

2011-08-01

figure and ground the luminance cue breaks down and gestalt contours can fail to pop out. In this case we rely on color, which, having weak stereopsis...REPORT Generalization of Figure - Ground Segmentation from Monocular to Binocular Vision in an Embodied Biological Brain Model 14. ABSTRACT 16. SECURITY...U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 15. SUBJECT TERMS figure - ground , neural network, object
Figure/Ground Segmentation via a Haptic Glance: Attributing Initial Finger Contacts to Objects or Their Supporting Surfaces.

Science.gov (United States)

Pawluk, D; Kitada, R; Abramowicz, A; Hamilton, C; Lederman, S J

2011-01-01

The current study addresses the well-known "figure/ground" problem in human perception, a fundamental topic that has received surprisingly little attention from touch scientists to date. Our approach is grounded in, and directly guided by, current knowledge concerning the nature of haptic processing. Given inherent figure/ground ambiguity in natural scenes and limited sensory inputs from first contact (a "haptic glance"), we consider first whether people are even capable of differentiating figure from ground (Experiments 1 and 2). Participants were required to estimate the strength of their subjective impression that they were feeling an object (i.e., figure) as opposed to just the supporting structure (i.e., ground). Second, we propose a tripartite factor classification scheme to further assess the influence of kinetic, geometric (Experiments 1 and 2), and material (Experiment 2) factors on haptic figure/ground segmentation, complemented by more open-ended subjective responses obtained at the end of the experiment. Collectively, the results indicate that under certain conditions it is possible to segment figure from ground via a single haptic glance with a reasonable degree of certainty, and that all three factor classes influence the estimated likelihood that brief, spatially distributed fingertip contacts represent contact with an object and/or its background supporting structure.
Edge-assignment and figure-ground segmentation in short-term visual matching.

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Driver, J; Baylis, G C

1996-12-01

Eight experiments examined the role of edge-assignment in a contour matching task. Subjects judged whether the jagged vertical edge of a probe shape matched the jagged edge that divided two adjoining shapes in an immediately preceding figure-ground display. Segmentation factors biased assignment of this dividing edge toward a figural shape on just one of its sides. Subjects were faster and more accurate at matching when the probe edge had a corresponding assignment. The rapid emergence of this effect provides an on-line analog of the long-term memory advantage for figures over grounds which Rubin (1915/1958) reported. The present on-line advantage was found when figures were defined by relative contrast and size, or by symmetry, and could not be explained solely by the automatic drawing of attention toward the location of the figural region. However, deliberate attention to one region of an otherwise ambiguous figure-ground display did produce the advantage. We propose that one-sided assignment of dividing edges may be obligatory in vision.
The 1981 Argentina ground data collection

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Horvath, R.; Colwell, R. N. (Principal Investigator); Hicks, D.; Sellman, B.; Sheffner, E.; Thomas, G.; Wood, B.

1981-01-01

Over 600 fields in the corn, soybean and wheat growing regions of the Argentine pampa were categorized by crop or cover type and ancillary data including crop calendars, historical crop production statistics and certain cropping practices were also gathered. A summary of the field work undertaken is included along with a country overview, a chronology of field trip planning and field work events, and the field work inventory of selected sample segments. LANDSAT images were annotated and used as the field work base and several hundred ground and aerial photographs were taken. These items along with segment descriptions are presented. Meetings were held with officials of the State Secretariat of Agriculture (SEAG) and the National Commission on Space Investigations (CNIE), and their support to the program are described.
A sensitivity analysis method for the body segment inertial parameters based on ground reaction and joint moment regressor matrices.

Science.gov (United States)

Futamure, Sumire; Bonnet, Vincent; Dumas, Raphael; Venture, Gentiane

2017-11-07

This paper presents a method allowing a simple and efficient sensitivity analysis of dynamics parameters of complex whole-body human model. The proposed method is based on the ground reaction and joint moment regressor matrices, developed initially in robotics system identification theory, and involved in the equations of motion of the human body. The regressor matrices are linear relatively to the segment inertial parameters allowing us to use simple sensitivity analysis methods. The sensitivity analysis method was applied over gait dynamics and kinematics data of nine subjects and with a 15 segments 3D model of the locomotor apparatus. According to the proposed sensitivity indices, 76 segments inertial parameters out the 150 of the mechanical model were considered as not influent for gait. The main findings were that the segment masses were influent and that, at the exception of the trunk, moment of inertia were not influent for the computation of the ground reaction forces and moments and the joint moments. The same method also shows numerically that at least 90% of the lower-limb joint moments during the stance phase can be estimated only from a force-plate and kinematics data without knowing any of the segment inertial parameters. Copyright © 2017 Elsevier Ltd. All rights reserved.
The Cryosat Payload Data Ground Segment and Data Processing

Science.gov (United States)

Frommknecht, B.; Mizzi, L.; Parrinello, T.; Badessi, S.

2014-12-01

The main CryoSat-2 mission objectives can be summarised in the determination of the regional and basin-scale trends in perennial Arctic sea ice thickness and mass, and in the determination of regional and total contributions to global sea level of the Antarctic and Greenland Ice. Therefore, the observations made over the life time of the mission will provide conclusive evidence as to whether there is a trend towards diminishing polar ice cover and consequently improve our understanding of the relationship between ice and global climate change.Scope of this paper is to describe the Cryosat Ground Segment and its main function to satisfy the Cryosat mission requirements. In particular, the paper will discuss the current status of the L1b and L2 processing in terms of completeness and availability. An outlook will be given on planned product and processor updates, the associated reprocessing campaigns will be discussed as well.
A cooperative NRC/CEA research project on earthquake ground motion on soil sites: overview

International Nuclear Information System (INIS)

Murphy, A.J.; Mohammadioun, B.

1989-10-01

This paper provides an overview of a multi-phase experiment being conducted jointly by the U.S. Nuclear Regulatory Commission and the French Commissariat a l'Energie Atomique. The objective of the experiment is to collect a comprehensive set of data on the propagation of earthquake ground motions vertically through a shallow soil column (on the order of several tens of meters). The data will be used to validate several of the available engineering computer codes for modeling earthquake ground motion. The data set will also be used to develop an improved understanding of the earthquake source function and the potential for non-linear effects controlling the propagation through the shallow soil column
Multi-segment foot kinematics and ground reaction forces during gait of individuals with plantar fasciitis.

Science.gov (United States)

Chang, Ryan; Rodrigues, Pedro A; Van Emmerik, Richard E A; Hamill, Joseph

2014-08-22

Clinically, plantar fasciitis (PF) is believed to be a result and/or prolonged by overpronation and excessive loading, but there is little biomechanical data to support this assertion. The purpose of this study was to determine the differences between healthy individuals and those with PF in (1) rearfoot motion, (2) medial forefoot motion, (3) first metatarsal phalangeal joint (FMPJ) motion, and (4) ground reaction forces (GRF). We recruited healthy (n=22) and chronic PF individuals (n=22, symptomatic over three months) of similar age, height, weight, and foot shape (p>0.05). Retro-reflective skin markers were fixed according to a multi-segment foot and shank model. Ground reaction forces and three dimensional kinematics of the shank, rearfoot, medial forefoot, and hallux segment were captured as individuals walked at 1.35 ms(-1). Despite similarities in foot anthropometrics, when compared to healthy individuals, individuals with PF exhibited significantly (pfoot kinematics and kinetics. Consistent with the theoretical injury mechanisms of PF, we found these individuals to have greater total rearfoot eversion and peak FMPJ dorsiflexion, which may put undue loads on the plantar fascia. Meanwhile, increased medial forefoot plantar flexion at initial contact and decreased propulsive GRF are suggestive of compensatory responses, perhaps to manage pain. Copyright © 2014 Elsevier Ltd. All rights reserved.
Earthquake cycle modeling of multi-segmented faults: dynamic rupture and ground motion simulation of the 1992 Mw 7.3 Landers earthquake.

Science.gov (United States)

Petukhin, A.; Galvez, P.; Somerville, P.; Ampuero, J. P.

2017-12-01

We perform earthquake cycle simulations to study the characteristics of source scaling relations and strong ground motions and in multi-segmented fault ruptures. For earthquake cycle modeling, a quasi-dynamic solver (QDYN, Luo et al, 2016) is used to nucleate events and the fully dynamic solver (SPECFEM3D, Galvez et al., 2014, 2016) is used to simulate earthquake ruptures. The Mw 7.3 Landers earthquake has been chosen as a target earthquake to validate our methodology. The SCEC fault geometry for the three-segmented Landers rupture is included and extended at both ends to a total length of 200 km. We followed the 2-D spatial correlated Dc distributions based on Hillers et. al. (2007) that associates Dc distribution with different degrees of fault maturity. The fault maturity is related to the variability of Dc on a microscopic scale. Large variations of Dc represents immature faults and lower variations of Dc represents mature faults. Moreover we impose a taper (a-b) at the fault edges and limit the fault depth to 15 km. Using these settings, earthquake cycle simulations are performed to nucleate seismic events on different sections of the fault, and dynamic rupture modeling is used to propagate the ruptures. The fault segmentation brings complexity into the rupture process. For instance, the change of strike between fault segments enhances strong variations of stress. In fact, Oglesby and Mai (2012) show the normal stress varies from positive (clamping) to negative (unclamping) between fault segments, which leads to favorable or unfavorable conditions for rupture growth. To replicate these complexities and the effect of fault segmentation in the rupture process, we perform earthquake cycles with dynamic rupture modeling and generate events similar to the Mw 7.3 Landers earthquake. We extract the asperities of these events and analyze the scaling relations between rupture area, average slip and combined area of asperities versus moment magnitude. Finally, the
The SENTINEL-3 Mission: Overview and Status

Science.gov (United States)

Benveniste, J.; Mecklenburg, S.

2015-12-01

The Copernicus Programme, being Europe's Earth Observation and Monitoring Programme led by the European Union, aims to provide, on a sustainable basis, reliable and timely services related to environmental and security issues. The Sentinel-3 mission forms part of the Copernicus Space Component. Its main objectives, building on the heritage and experience of the European Space Agency's (ESA) ERS and ENVISAT missions, are to measure sea-surface topography, sea- and land-surface temperature and ocean- and land-surface colour in support of ocean forecasting systems, and for environmental and climate monitoring. The series of Sentinel-3 satellites will ensure global, frequent and near-real time ocean, ice and land monitoring, with the provision of observation data in routine, long term (up to 20 years of operations) and continuous fashion, with a consistent quality and a high level of reliability and availability. The Sentinel-3 missions will be jointly operated by ESA and EUMETSAT. ESA will be responsible for the operations, maintenance and evolution of the Sentinel-3 ground segment on land related products and EUMETSAT for the marine products. The Sentinel-3 ground segment systematically acquires, processes and distributes a set of pre-defined core data products. Sentinel-3A is foreseen to be launched at the beginning of November 2015. The paper will give an overview on the mission, its instruments and objectives, the data products provided, the mechanisms to access the mission's data, and if available first results.
A Comparison of Two Commercial Volumetry Software Programs in the Analysis of Pulmonary Ground-Glass Nodules: Segmentation Capability and Measurement Accuracy

Science.gov (United States)

Kim, Hyungjin; Lee, Sang Min; Lee, Hyun-Ju; Goo, Jin Mo

2013-01-01

Objective To compare the segmentation capability of the 2 currently available commercial volumetry software programs with specific segmentation algorithms for pulmonary ground-glass nodules (GGNs) and to assess their measurement accuracy. Materials and Methods In this study, 55 patients with 66 GGNs underwent unenhanced low-dose CT. GGN segmentation was performed by using 2 volumetry software programs (LungCARE, Siemens Healthcare; LungVCAR, GE Healthcare). Successful nodule segmentation was assessed visually and morphologic features of GGNs were evaluated to determine factors affecting segmentation by both types of software. In addition, the measurement accuracy of the software programs was investigated by using an anthropomorphic chest phantom containing simulated GGNs. Results The successful nodule segmentation rate was significantly higher in LungCARE (90.9%) than in LungVCAR (72.7%) (p = 0.012). Vascular attachment was a negatively influencing morphologic feature of nodule segmentation for both software programs. As for measurement accuracy, mean relative volume measurement errors in nodules ≥ 10 mm were 14.89% with LungCARE and 19.96% with LungVCAR. The mean relative attenuation measurement errors in nodules ≥ 10 mm were 3.03% with LungCARE and 5.12% with LungVCAR. Conclusion LungCARE shows significantly higher segmentation success rates than LungVCAR. Measurement accuracy of volume and attenuation of GGNs is acceptable in GGNs ≥ 10 mm by both software programs. PMID:23901328
A comparison of two commercial volumetry software programs in the analysis of pulmonary ground-glass nodules: Segmentation capability and measurement accuracy

International Nuclear Information System (INIS)

Kim, Hyung Jin; Park, Chang Min; Lee, Sang Min; Lee, Hyun Joo; Goo, Jin Mo

2013-01-01

To compare the segmentation capability of the 2 currently available commercial volumetry software programs with specific segmentation algorithms for pulmonary ground-glass nodules (GGNs) and to assess their measurement accuracy. In this study, 55 patients with 66 GGNs underwent unenhanced low-dose CT. GGN segmentation was performed by using 2 volumetry software programs (LungCARE, Siemens Healthcare; LungVCAR, GE Healthcare). Successful nodule segmentation was assessed visually and morphologic features of GGNs were evaluated to determine factors affecting segmentation by both types of software. In addition, the measurement accuracy of the software programs was investigated by using an anthropomorphic chest phantom containing simulated GGNs. The successful nodule segmentation rate was significantly higher in LungCARE (90.9%) than in LungVCAR (72.7%) (p = 0.012). Vascular attachment was a negatively influencing morphologic feature of nodule segmentation for both software programs. As for measurement accuracy, mean relative volume measurement errors in nodules ≥ 10 mm were 14.89% with LungCARE and 19.96% with LungVCAR. The mean relative attenuation measurement errors in nodules ≥ 10 mm were 3.03% with LungCARE and 5.12% with LungVCAR. LungCARE shows significantly higher segmentation success rates than LungVCAR. Measurement accuracy of volume and attenuation of GGNs is acceptable in GGNs ≥ 10 mm by both software programs.
A comparison of two commercial volumetry software programs in the analysis of pulmonary ground-glass nodules: Segmentation capability and measurement accuracy

Energy Technology Data Exchange (ETDEWEB)

Kim, Hyung Jin; Park, Chang Min; Lee, Sang Min; Lee, Hyun Joo; Goo, Jin Mo [Dept. of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul (Korea, Republic of)

2013-08-15

To compare the segmentation capability of the 2 currently available commercial volumetry software programs with specific segmentation algorithms for pulmonary ground-glass nodules (GGNs) and to assess their measurement accuracy. In this study, 55 patients with 66 GGNs underwent unenhanced low-dose CT. GGN segmentation was performed by using 2 volumetry software programs (LungCARE, Siemens Healthcare; LungVCAR, GE Healthcare). Successful nodule segmentation was assessed visually and morphologic features of GGNs were evaluated to determine factors affecting segmentation by both types of software. In addition, the measurement accuracy of the software programs was investigated by using an anthropomorphic chest phantom containing simulated GGNs. The successful nodule segmentation rate was significantly higher in LungCARE (90.9%) than in LungVCAR (72.7%) (p = 0.012). Vascular attachment was a negatively influencing morphologic feature of nodule segmentation for both software programs. As for measurement accuracy, mean relative volume measurement errors in nodules ≥ 10 mm were 14.89% with LungCARE and 19.96% with LungVCAR. The mean relative attenuation measurement errors in nodules ≥ 10 mm were 3.03% with LungCARE and 5.12% with LungVCAR. LungCARE shows significantly higher segmentation success rates than LungVCAR. Measurement accuracy of volume and attenuation of GGNs is acceptable in GGNs ≥ 10 mm by both software programs.
A NDVI assisted remote sensing image adaptive scale segmentation method

Science.gov (United States)

Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

2018-03-01

Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.
MRI Brain Tumor Segmentation Methods- A Review

OpenAIRE

Gursangeet, Kaur; Jyoti, Rani

2016-01-01

Medical image processing and its segmentation is an active and interesting area for researchers. It has reached at the tremendous place in diagnosing tumors after the discovery of CT and MRI. MRI is an useful tool to detect the brain tumor and segmentation is performed to carry out the useful portion from an image. The purpose of this paper is to provide an overview of different image segmentation methods like watershed algorithm, morphological operations, neutrosophic sets, thresholding, K-...
Sloped Terrain Segmentation for Autonomous Drive Using Sparse 3D Point Cloud

Directory of Open Access Journals (Sweden)

Seoungjae Cho

2014-01-01

Full Text Available A ubiquitous environment for road travel that uses wireless networks requires the minimization of data exchange between vehicles. An algorithm that can segment the ground in real time is necessary to obtain location data between vehicles simultaneously executing autonomous drive. This paper proposes a framework for segmenting the ground in real time using a sparse three-dimensional (3D point cloud acquired from undulating terrain. A sparse 3D point cloud can be acquired by scanning the geography using light detection and ranging (LiDAR sensors. For efficient ground segmentation, 3D point clouds are quantized in units of volume pixels (voxels and overlapping data is eliminated. We reduce nonoverlapping voxels to two dimensions by implementing a lowermost heightmap. The ground area is determined on the basis of the number of voxels in each voxel group. We execute ground segmentation in real time by proposing an approach to minimize the comparison between neighboring voxels. Furthermore, we experimentally verify that ground segmentation can be executed at about 19.31 ms per frame.
Ground System Survivability Overview

Science.gov (United States)

2012-03-27

Avoidance Blast Mitigation Optimization Customer ILIR RDT&E Funding 5.0 % 0.5% GSS has a proven, technically proficient workforce that meets...Evaluation of Defensive-Aid Suites (ARMED) Common Automatic Fire Extinguishing System ( CAFES ) Transparent Armor Development Ground Combat Vehicle...Survey TRADOC (WFO, CNA, etc) Voice of the Customer Sy st em s En gi ne er in g Publish overarching MIL-STD, design guidelines, technical
Minimizing manual image segmentation turn-around time for neuronal reconstruction by embracing uncertainty.

Directory of Open Access Journals (Sweden)

Stephen M Plaza

Full Text Available The ability to automatically segment an image into distinct regions is a critical aspect in many visual processing applications. Because inaccuracies often exist in automatic segmentation, manual segmentation is necessary in some application domains to correct mistakes, such as required in the reconstruction of neuronal processes from microscopic images. The goal of the automated segmentation tool is traditionally to produce the highest-quality segmentation, where quality is measured by the similarity to actual ground truth, so as to minimize the volume of manual correction necessary. Manual correction is generally orders-of-magnitude more time consuming than automated segmentation, often making handling large images intractable. Therefore, we propose a more relevant goal: minimizing the turn-around time of automated/manual segmentation while attaining a level of similarity with ground truth. It is not always necessary to inspect every aspect of an image to generate a useful segmentation. As such, we propose a strategy to guide manual segmentation to the most uncertain parts of segmentation. Our contributions include 1 a probabilistic measure that evaluates segmentation without ground truth and 2 a methodology that leverages these probabilistic measures to significantly reduce manual correction while maintaining segmentation quality.
PEER NGA-East Overview: Development of a Ground Motion Characterization Model (Ground Motion Prediction Equations) for Central and Eastern North America

Science.gov (United States)

Goulet, C. A.; Abrahamson, N. A.; Al Atik, L.; Atkinson, G. M.; Bozorgnia, Y.; Graves, R. W.; Kuehn, N. M.; Youngs, R. R.

2017-12-01

The Next Generation Attenuation project for Central and Eastern North America (CENA), NGA-East, is a major multi-disciplinary project coordinated by the Pacific Earthquake Engineering Research Center (PEER). The project was co-sponsored by the U.S. Nuclear Regulatory Commission (NRC), the U.S. Department of Energy (DOE), the Electric Power Research Institute (EPRI) and the U.S. Geological Survey (USGS). NGA-East involved a large number of participating researchers from various organizations in academia, industry and government and was carried-out as a combination of 1) a scientific research project and 2) a model-building component following the NRC Seismic Senior Hazard Analysis Committee (SSHAC) Level 3 process. The science part of the project led to several data products and technical reports while the SSHAC component aggregated the various results into a ground motion characterization (GMC) model. The GMC model consists in a set of ground motion models (GMMs) for median and standard deviation of ground motions and their associated weights, combined into logic-trees for use in probabilistic seismic hazard analyses (PSHA). NGA-East addressed many technical challenges, most of them related to the relatively small number of earthquake recordings available for CENA. To resolve this shortcoming, the project relied on ground motion simulations to supplement the available data. Other important scientific issues were addressed through research projects on topics such as the regionalization of seismic source, path and attenuation of motions, the treatment of variability and uncertainties and on the evaluation of site effects. Seven working groups were formed to cover the complexity and breadth of topics in the NGA-East project, each focused on a specific technical area. This presentation provides an overview of the NGA-East research project and its key products.
Eliciting Perceptual Ground Truth for Image Segmentation

OpenAIRE

Hodge, Victoria Jane; Eakins, John; Austin, Jim

2006-01-01

In this paper, we investigate human visual perception and establish a body of ground truth data elicited from human visual studies. We aim to build on the formative work of Ren, Eakins and Briggs who produced an initial ground truth database. Human subjects were asked to draw and rank their perceptions of the parts of a series of figurative images. These rankings were then used to score the perceptions, identify the preferred human breakdowns and thus allow us to induce perceptual rules for h...

ESA Earth Observation Ground Segment Evolution Strategy

Science.gov (United States)

Benveniste, J.; Albani, M.; Laur, H.

2016-12-01

One of the key elements driving the evolution of EO Ground Segments, in particular in Europe, has been to enable the creation of added value from EO data and products. This requires the ability to constantly adapt and improve the service to a user base expanding far beyond the `traditional' EO user community of remote sensing specialists. Citizen scientists, the general public, media and educational actors form another user group that is expected to grow. Technological advances, Open Data policies, including those implemented by ESA and the EU, as well as an increasing number of satellites in operations (e.g. Copernicus Sentinels) have led to an enormous increase in available data volumes. At the same time, even with modern network and data handling services, fewer users can afford to bulk-download and consider all potentially relevant data and associated knowledge. The "EO Innovation Europe" concept is being implemented in Europe in coordination between the European Commission, ESA and other European Space Agencies, and industry. This concept is encapsulated in the main ideas of "Bringing the User to the Data" and "Connecting the Users" to complement the traditional one-to-one "data delivery" approach of the past. Both ideas are aiming to better "empower the users" and to create a "sustainable system of interconnected EO Exploitation Platforms", with the objective to enable large scale exploitation of European EO data assets for stimulating innovation and to maximize their impact. These interoperable/interconnected platforms are virtual environments in which the users - individually or collaboratively - have access to the required data sources and processing tools, as opposed to downloading and handling the data `at home'. EO-Innovation Europe has been structured around three elements: an enabling element (acting as a back office), a stimulating element and an outreach element (acting as a front office). Within the enabling element, a "mutualisation" of efforts
Adaptive attenuation of aliased ground roll using the shearlet transform

Science.gov (United States)

Hosseini, Seyed Abolfazl; Javaherian, Abdolrahim; Hassani, Hossien; Torabi, Siyavash; Sadri, Maryam

2015-01-01

Attenuation of ground roll is an essential step in seismic data processing. Spatial aliasing of the ground roll may cause the overlap of the ground roll with reflections in the f-k domain. The shearlet transform is a directional and multidimensional transform that separates the events with different dips and generates subimages in different scales and directions. In this study, the shearlet transform was used adaptively to attenuate aliased and non-aliased ground roll. After defining a filtering zone, an input shot record is divided into segments. Each segment overlaps adjacent segments. To apply the shearlet transform on each segment, the subimages containing aliased and non-aliased ground roll, the locations of these events on each subimage are selected adaptively. Based on these locations, mute is applied on the selected subimages. The filtered segments are merged together, using the Hanning function, after applying the inverse shearlet transform. This adaptive process of ground roll attenuation was tested on synthetic data, and field shot records from west of Iran. Analysis of the results using the f-k spectra revealed that the non-aliased and most of the aliased ground roll were attenuated using the proposed adaptive attenuation procedure. Also, we applied this method on shot records of a 2D land survey, and the data sets before and after ground roll attenuation were stacked and compared. The stacked section after ground roll attenuation contained less linear ground roll noise and more continuous reflections in comparison with the stacked section before the ground roll attenuation. The proposed method has some drawbacks such as more run time in comparison with traditional methods such as f-k filtering and reduced performance when the dip and frequency content of aliased ground roll are the same as those of the reflections.
An overview of reactor vessel internals segmentation for nuclear plant decommissioning

International Nuclear Information System (INIS)

Litka, T.J.

1994-01-01

Several nuclear plants have undergone reactor vessel (RV) internals segmentation as part of or in preparation for decommissioning the plant. In addition, several other nuclear facilities are planning for similar work efforts. The primary technology used for segmentation of RV internals, whether in-air or underwater is Plasma Arc Cutting (PAC). Metal Disintegration Machining (MDM) is also used for difficult to make cuts. PAC and MDM are deployed by various means including Long Handled Tools (LHTs), fixtures, tracks, and multi-axis manipulators. These enable remote cutting due to the radiation and/or underwater environment. A Boiling Water Reactor (BWR), a Pressurized Water Reactor (PWR), and a High Temperature Gas Reactor (HTGR) have had their internals removed and segmented using PAC and MDM. The cutting technology used for each component, location of cut, cut geometry and environment had to be determined well before the actual cutting operations. This allowed for the design, fabrication, and testing of the delivery systems. The technologies, selection process, and methodology for RV internals segmentation will be discussed in this paper
Process Segmentation Typology in Czech Companies

Directory of Open Access Journals (Sweden)

Tucek David

2016-03-01

Full Text Available This article describes process segmentation typology during business process management implementation in Czech companies. Process typology is important for a manager’s overview of process orientation as well as for a manager’s general understanding of business process management. This article provides insight into a process-oriented organizational structure. The first part analyzes process segmentation typology itself as well as some original results of quantitative research evaluating process segmentation typology in the specific context of Czech company strategies. Widespread data collection was carried out in 2006 and 2013. The analysis of this data showed that managers have more options regarding process segmentation and its selection. In terms of practicality and ease of use, the most frequently used method of process segmentation (managerial, main, and supportive stems directly from the requirements of ISO 9001. Because of ISO 9001:2015, managers must now apply risk planning in relation to the selection of processes that are subjected to process management activities. It is for this fundamental reason that this article focuses on process segmentation typology.
Improved vegetation segmentation with ground shadow removal using an HDR camera

NARCIS (Netherlands)

Suh, Hyun K.; Hofstee, Jan W.; Henten, van Eldert J.

2018-01-01

A vision-based weed control robot for agricultural field application requires robust vegetation segmentation. The output of vegetation segmentation is the fundamental element in the subsequent process of weed and crop discrimination as well as weed control. There are two challenging issues for
Is STAPLE algorithm confident to assess segmentation methods in PET imaging?

International Nuclear Information System (INIS)

Dewalle-Vignion, Anne-Sophie; Betrouni, Nacim; Vermandel, Maximilien; Baillet, Clio

2015-01-01

Accurate tumor segmentation in [18F]-fluorodeoxyglucose positron emission tomography is crucial for tumor response assessment and target volume definition in radiation therapy. Evaluation of segmentation methods from clinical data without ground truth is usually based on physicians’ manual delineations. In this context, the simultaneous truth and performance level estimation (STAPLE) algorithm could be useful to manage the multi-observers variability. In this paper, we evaluated how this algorithm could accurately estimate the ground truth in PET imaging.Complete evaluation study using different criteria was performed on simulated data. The STAPLE algorithm was applied to manual and automatic segmentation results. A specific configuration of the implementation provided by the Computational Radiology Laboratory was used.Consensus obtained by the STAPLE algorithm from manual delineations appeared to be more accurate than manual delineations themselves (80% of overlap). An improvement of the accuracy was also observed when applying the STAPLE algorithm to automatic segmentations results.The STAPLE algorithm, with the configuration used in this paper, is more appropriate than manual delineations alone or automatic segmentations results alone to estimate the ground truth in PET imaging. Therefore, it might be preferred to assess the accuracy of tumor segmentation methods in PET imaging. (paper)
Is STAPLE algorithm confident to assess segmentation methods in PET imaging?

Science.gov (United States)

Dewalle-Vignion, Anne-Sophie; Betrouni, Nacim; Baillet, Clio; Vermandel, Maximilien

2015-12-01

Accurate tumor segmentation in [18F]-fluorodeoxyglucose positron emission tomography is crucial for tumor response assessment and target volume definition in radiation therapy. Evaluation of segmentation methods from clinical data without ground truth is usually based on physicians’ manual delineations. In this context, the simultaneous truth and performance level estimation (STAPLE) algorithm could be useful to manage the multi-observers variability. In this paper, we evaluated how this algorithm could accurately estimate the ground truth in PET imaging. Complete evaluation study using different criteria was performed on simulated data. The STAPLE algorithm was applied to manual and automatic segmentation results. A specific configuration of the implementation provided by the Computational Radiology Laboratory was used. Consensus obtained by the STAPLE algorithm from manual delineations appeared to be more accurate than manual delineations themselves (80% of overlap). An improvement of the accuracy was also observed when applying the STAPLE algorithm to automatic segmentations results. The STAPLE algorithm, with the configuration used in this paper, is more appropriate than manual delineations alone or automatic segmentations results alone to estimate the ground truth in PET imaging. Therefore, it might be preferred to assess the accuracy of tumor segmentation methods in PET imaging.
A Model Ground State of Polyampholytes

International Nuclear Information System (INIS)

Wofling, S.; Kantor, Y.

1998-01-01

The ground state of randomly charged polyampholytes (polymers with positive and negatively charged groups along their backbone) is conjectured to have a structure similar to a necklace, made of weakly charged parts of the chain, compacting into globules, connected by highly charged stretched 'strings' attempted to quantify the qualitative necklace model, by suggesting a zero approximation model, in which the longest neutral segment of the polyampholyte forms a globule, while the remaining part will form a tail. Expanding this approximation, we suggest a specific necklace-type structure for the ground state of randomly charged polyampholyte's, where all the neutral parts of the chain compact into globules: The longest neutral segment compacts into a globule; in the remaining part of the chain, the longest neutral segment (the second longest neutral segment) compacts into a globule, then the third, and so on. A random sequence of charges is equivalent to a random walk, and a neutral segment is equivalent to a loop inside the random walk. We use analytical and Monte Carlo methods to investigate the size distribution of loops in a one-dimensional random walk. We show that the length of the nth longest neutral segment in a sequence of N monomers (or equivalently, the nth longest loop in a random walk of N steps) is proportional to N/n 2 , while the mean number of neutral segments increases as √N. The polyampholytes in the ground state within our model is found to have an average linear size proportional to dN, and an average surface area proportional to N 2/3
Timing Embryo Segmentation: Dynamics and Regulatory Mechanisms of the Vertebrate Segmentation Clock

Science.gov (United States)

Resende, Tatiana P.; Andrade, Raquel P.; Palmeirim, Isabel

2014-01-01

All vertebrate species present a segmented body, easily observed in the vertebrate column and its associated components, which provides a high degree of motility to the adult body and efficient protection of the internal organs. The sequential formation of the segmented precursors of the vertebral column during embryonic development, the somites, is governed by an oscillating genetic network, the somitogenesis molecular clock. Herein, we provide an overview of the molecular clock operating during somite formation and its underlying molecular regulatory mechanisms. Human congenital vertebral malformations have been associated with perturbations in these oscillatory mechanisms. Thus, a better comprehension of the molecular mechanisms regulating somite formation is required in order to fully understand the origin of human skeletal malformations. PMID:24895605
PSNet: prostate segmentation on MRI based on a convolutional neural network.

Science.gov (United States)

Tian, Zhiqiang; Liu, Lizhi; Zhang, Zhenfeng; Fei, Baowei

2018-04-01

Automatic segmentation of the prostate on magnetic resonance images (MRI) has many applications in prostate cancer diagnosis and therapy. We proposed a deep fully convolutional neural network (CNN) to segment the prostate automatically. Our deep CNN model is trained end-to-end in a single learning stage, which uses prostate MRI and the corresponding ground truths as inputs. The learned CNN model can be used to make an inference for pixel-wise segmentation. Experiments were performed on three data sets, which contain prostate MRI of 140 patients. The proposed CNN model of prostate segmentation (PSNet) obtained a mean Dice similarity coefficient of [Formula: see text] as compared to the manually labeled ground truth. Experimental results show that the proposed model could yield satisfactory segmentation of the prostate on MRI.
An objective evaluation framework for segmentation techniques of functional positron emission tomography studies

CERN Document Server

Kim, J; Eberl, S; Feng, D

2004-01-01

Segmentation of multi-dimensional functional positron emission tomography (PET) studies into regions of interest (ROI) exhibiting similar temporal behavior is useful in diagnosis and evaluation of neurological images. Quantitative evaluation plays a crucial role in measuring the segmentation algorithm's performance. Due to the lack of "ground truth" available for evaluating segmentation of clinical images, automated segmentation results are usually compared with manual delineation of structures which is, however, subjective, and is difficult to perform. Alternatively, segmentation of co-registered anatomical images such as magnetic resonance imaging (MRI) can be used as the ground truth to the PET segmentation. However, this is limited to PET studies which have corresponding MRI. In this study, we introduce a framework for the objective and quantitative evaluation of functional PET study segmentation without the need for manual delineation or registration to anatomical images of the patient. The segmentation ...
CryoSat-2 Payload Data Ground Segment and Data Processing Status

Science.gov (United States)

Badessi, S.; Frommknecht, B.; Parrinello, T.; Mizzi, L.

2012-04-01

Selected as the first Earth Explorer Opportunity mission and following the launch failure of Cryosat-1 in 2005, the Cryosat-2 mission was launched on the 8th April 2010 and it is the first European ice mission dedicated to monitoring precise changes in the thickness of polar ice sheets and floating sea ice over a baseline 3-year period. The main CryoSat-2 mission objectives can be summarised in the determination of the regional and basin-scale trends in perennial Arctic sea ice thickness and mass, and in the determination of regional and total contributions to global sea level of the Antarctic and Greenland Ice. Therefore, the observations made over the life time of the mission will provide conclusive evidence as to whether there is a trend towards diminishing polar ice cover and consequently improve our understanding of the relationship between ice and global climate change. Scope of this paper is to describe the Cryosat-2 Ground Segment present configuration and its main function to satisfy the Cryosat-2 mission requirements. In particular, the paper will highlight the current status of the processing of the SIRAL instrument L1b and L2 products in terms of completeness and availability. Additional information will be also given on the PDGS current status and planned evolution, the latest product and processor updates and the status of the associated reprocessing campaign.
Feedback enhances feedforward figure-ground segmentation by changing firing mode.

Science.gov (United States)

Supèr, Hans; Romeo, August

2011-01-01

In the visual cortex, feedback projections are conjectured to be crucial in figure-ground segregation. However, the precise function of feedback herein is unclear. Here we tested a hypothetical model of reentrant feedback. We used a previous developed 2-layered feedforward spiking network that is able to segregate figure from ground and included feedback connections. Our computer model data show that without feedback, neurons respond with regular low-frequency (∼9 Hz) bursting to a figure-ground stimulus. After including feedback the firing pattern changed into a regular (tonic) spiking pattern. In this state, we found an extra enhancement of figure responses and a further suppression of background responses resulting in a stronger figure-ground signal. Such push-pull effect was confirmed by comparing the figure-ground responses with the responses to a homogenous texture. We propose that feedback controls figure-ground segregation by influencing the neural firing patterns of feedforward projecting neurons.
Feedback enhances feedforward figure-ground segmentation by changing firing mode.

Directory of Open Access Journals (Sweden)

Hans Supèr

Full Text Available In the visual cortex, feedback projections are conjectured to be crucial in figure-ground segregation. However, the precise function of feedback herein is unclear. Here we tested a hypothetical model of reentrant feedback. We used a previous developed 2-layered feedforward spiking network that is able to segregate figure from ground and included feedback connections. Our computer model data show that without feedback, neurons respond with regular low-frequency (∼9 Hz bursting to a figure-ground stimulus. After including feedback the firing pattern changed into a regular (tonic spiking pattern. In this state, we found an extra enhancement of figure responses and a further suppression of background responses resulting in a stronger figure-ground signal. Such push-pull effect was confirmed by comparing the figure-ground responses with the responses to a homogenous texture. We propose that feedback controls figure-ground segregation by influencing the neural firing patterns of feedforward projecting neurons.
Feedback Enhances Feedforward Figure-Ground Segmentation by Changing Firing Mode

Science.gov (United States)

Supèr, Hans; Romeo, August

2011-01-01

In the visual cortex, feedback projections are conjectured to be crucial in figure-ground segregation. However, the precise function of feedback herein is unclear. Here we tested a hypothetical model of reentrant feedback. We used a previous developed 2-layered feedforwardspiking network that is able to segregate figure from ground and included feedback connections. Our computer model data show that without feedback, neurons respond with regular low-frequency (∼9 Hz) bursting to a figure-ground stimulus. After including feedback the firing pattern changed into a regular (tonic) spiking pattern. In this state, we found an extra enhancement of figure responses and a further suppression of background responses resulting in a stronger figure-ground signal. Such push-pull effect was confirmed by comparing the figure-ground responses withthe responses to a homogenous texture. We propose that feedback controlsfigure-ground segregation by influencing the neural firing patterns of feedforward projecting neurons. PMID:21738747
Management of the science ground segment for the Euclid mission

Science.gov (United States)

Zacchei, Andrea; Hoar, John; Pasian, Fabio; Buenadicha, Guillermo; Dabin, Christophe; Gregorio, Anna; Mansutti, Oriana; Sauvage, Marc; Vuerli, Claudio

2016-07-01

Euclid is an ESA mission aimed at understanding the nature of dark energy and dark matter by using simultaneously two probes (weak lensing and baryon acoustic oscillations). The mission will observe galaxies and clusters of galaxies out to z 2, in a wide extra-galactic survey covering 15000 deg2, plus a deep survey covering an area of 40 deg². The payload is composed of two instruments, an imager in the visible domain (VIS) and an imager-spectrometer (NISP) covering the near-infrared. The launch is planned in Q4 of 2020. The elements of the Euclid Science Ground Segment (SGS) are the Science Operations Centre (SOC) operated by ESA and nine Science Data Centres (SDCs) in charge of data processing, provided by the Euclid Consortium (EC), formed by over 110 institutes spread in 15 countries. SOC and the EC started several years ago a tight collaboration in order to design and develop a single, cost-efficient and truly integrated SGS. The distributed nature, the size of the data set, and the needed accuracy of the results are the main challenges expected in the design and implementation of the SGS. In particular, the huge volume of data (not only Euclid data but also ground based data) to be processed in the SDCs will require distributed storage to avoid data migration across SDCs. This paper describes the management challenges that the Euclid SGS is facing while dealing with such complexity. The main aspect is related to the organisation of a geographically distributed software development team. In principle algorithms and code is developed in a large number of institutes, while data is actually processed at fewer centers (the national SDCs) where the operational computational infrastructures are maintained. The software produced for data handling, processing and analysis is built within a common development environment defined by the SGS System Team, common to SOC and ECSGS, which has already been active for several years. The code is built incrementally through
Generating Ground Reference Data for a Global Impervious Surface Survey

Science.gov (United States)

Tilton, James C.; deColstoun, Eric Brown; Wolfe, Robert E.; Tan, Bin; Huang, Chengquan

2012-01-01

either positive or negative examples, and displays a classification of the study area based on these examples. For our study, the positive examples are examples of impervious surfaces and negative examples are examples of non-impervious surfaces. HSegLearn searches the hierarchical segmentation from HSeg for the coarsest level of segmentation at which selected positive example locations do not conflict with negative example locations and labels the image accordingly. The negative example regions are always defined at the finest level of segmentation detail. The resulting classification map can be then further edited at a region object level using the previously developed HSegViewer tool [3]. After providing an overview of the HSeg image segmentation program, we provide a detailed description of the HSegLearn software tool. We then give examples of using HSegLearn to generate ground reference data and conclude with comments on the effectiveness of the HSegLearn tool.
Audio segmentation of broadcast news in the Albayzin-2010 evaluation: overview, results, and discussion

Directory of Open Access Journals (Sweden)

Butko Taras

2011-01-01

Full Text Available Abstract Recently, audio segmentation has attracted research interest because of its usefulness in several applications like audio indexing and retrieval, subtitling, monitoring of acoustic scenes, etc. Moreover, a previous audio segmentation stage may be useful to improve the robustness of speech technologies like automatic speech recognition and speaker diarization. In this article, we present the evaluation of broadcast news audio segmentation systems carried out in the context of the Albayzín-2010 evaluation campaign. That evaluation consisted of segmenting audio from the 3/24 Catalan TV channel into five acoustic classes: music, speech, speech over music, speech over noise, and the other. The evaluation results displayed the difficulty of this segmentation task. In this article, after presenting the database and metric, as well as the feature extraction methods and segmentation techniques used by the submitted systems, the experimental results are analyzed and compared, with the aim of gaining an insight into the proposed solutions, and looking for directions which are promising.
Neural Scene Segmentation by Oscillatory Correlation

National Research Council Canada - National Science Library

Wang, DeLiang

2000-01-01

The segmentation of a visual scene into a set of coherent patterns (objects) is a fundamental aspect of perception, which underlies a variety of important tasks such as figure/ground segregation, and scene analysis...
Overview of diffraction gratings technologies for spaceflight satellites and ground-based telescopes

Science.gov (United States)

Cotel, A.; Liard, A.; Desserouer, F.; Pichon, P.

2017-11-01

The diffraction gratings are widely used in Space-flight satellites for spectrograph instruments or in ground-based telescopes in astronomy. The diffraction gratings are one of the key optical components of such systems and have to exhibit very high optical performances. HORIBA Jobin Yvon S.A.S. (part of HORIBA Group) is in the forefront of such gratings development for more than 40 years. During the past decades, HORIBA Jobin Yvon (HJY) has developed a unique expertise in diffraction grating design and manufacturing processes for holographic, ruled or etched gratings. We will present in this paper an overview of diffraction grating technologies especially designed for space and astronomy applications. We will firstly review the heritage of the company in this field with the space qualification of different grating types. Then, we will describe several key grating technologies developed for specific space or astronomy projects: ruled blazed low groove density plane reflection grating, high-groove density holographic toroidal and spherical grating, and finally transmission Fused Silica Etched (FSE) grism-assembled grating. We will not present the Volume Phase Holographic (VPHG) grating type which is used in Astronomy.

The CryoSat-2 Payload Data Ground Segment and Data Processing

Science.gov (United States)

Frommknecht, Bjoern; Parrinello, Tommaso; Badessi, Stefano; Mizzi, Loretta; Torroni, Vittorio

2017-04-01

Selected as the first Earth Explorer Opportunity mission and following the launch failure of Cryosat-1 in 2005, the Cryosat-2 mission was launched on the 8th April 2010 and it is the first European ice mission dedicated to monitoring precise changes in the thickness of polar ice sheets and floating sea ice over a baseline 3-year period. The main CryoSat-2 mission objectives can be summarised in the determination of the regional and basin-scale trends in perennial Arctic sea ice thickness and mass, and in the determination of regional and total contributions to global sea level of the Antarctic and Greenland Ice. Therefore, the observations made over the life time of the mission will provide conclusive evidence as to whether there is a trend towards diminishing polar ice cover and consequently improve our understanding of the relationship between ice and global climate change. Scope of this paper is to describe the Cryosat-2 Ground Segment present configuration and its main function to satisfy the Cryosat-2 mission requirements. In particular, the paper will highlight the current status of the pro- cessing of the SIRAL instrument L1b and L2 products, both for ocean and ice products, in terms of completeness and availability. Additional information will be also given on the PDGS current status and planned evolutions, including product and processor updates and associated reprocessing campaigns.
Kennedy Space Center Orion Processing Team Planning for Ground Operations

Science.gov (United States)

Letchworth, Gary; Schlierf, Roland

2011-01-01

Topics in this presentation are: Constellation Ares I/Orion/Ground Ops Elements Orion Ground Operations Flow Orion Operations Planning Process and Toolset Overview, including: 1 Orion Concept of Operations by Phase 2 Ops Analysis Capabilities Overview 3 Operations Planning Evolution 4 Functional Flow Block Diagrams 5 Operations Timeline Development 6 Discrete Event Simulation (DES) Modeling 7 Ground Operations Planning Document Database (GOPDb) Using Operations Planning Tools for Operability Improvements includes: 1 Kaizen/Lean Events 2 Mockups 3 Human Factors Analysis
Molecular species identification of Central European ground beetles (Coleoptera: Carabidae using nuclear rDNA expansion segments and DNA barcodes

Directory of Open Access Journals (Sweden)

Raupach Michael J

2010-09-01

Full Text Available Abstract Background The identification of vast numbers of unknown organisms using DNA sequences becomes more and more important in ecological and biodiversity studies. In this context, a fragment of the mitochondrial cytochrome c oxidase I (COI gene has been proposed as standard DNA barcoding marker for the identification of organisms. Limitations of the COI barcoding approach can arise from its single-locus identification system, the effect of introgression events, incomplete lineage sorting, numts, heteroplasmy and maternal inheritance of intracellular endosymbionts. Consequently, the analysis of a supplementary nuclear marker system could be advantageous. Results We tested the effectiveness of the COI barcoding region and of three nuclear ribosomal expansion segments in discriminating ground beetles of Central Europe, a diverse and well-studied invertebrate taxon. As nuclear markers we determined the 18S rDNA: V4, 18S rDNA: V7 and 28S rDNA: D3 expansion segments for 344 specimens of 75 species. Seventy-three species (97% of the analysed species could be accurately identified using COI, while the combined approach of all three nuclear markers provided resolution among 71 (95% of the studied Carabidae. Conclusion Our results confirm that the analysed nuclear ribosomal expansion segments in combination constitute a valuable and efficient supplement for classical DNA barcoding to avoid potential pitfalls when only mitochondrial data are being used. We also demonstrate the high potential of COI barcodes for the identification of even closely related carabid species.
Molecular species identification of Central European ground beetles (Coleoptera: Carabidae) using nuclear rDNA expansion segments and DNA barcodes.

Science.gov (United States)

Raupach, Michael J; Astrin, Jonas J; Hannig, Karsten; Peters, Marcell K; Stoeckle, Mark Y; Wägele, Johann-Wolfgang

2010-09-13

The identification of vast numbers of unknown organisms using DNA sequences becomes more and more important in ecological and biodiversity studies. In this context, a fragment of the mitochondrial cytochrome c oxidase I (COI) gene has been proposed as standard DNA barcoding marker for the identification of organisms. Limitations of the COI barcoding approach can arise from its single-locus identification system, the effect of introgression events, incomplete lineage sorting, numts, heteroplasmy and maternal inheritance of intracellular endosymbionts. Consequently, the analysis of a supplementary nuclear marker system could be advantageous. We tested the effectiveness of the COI barcoding region and of three nuclear ribosomal expansion segments in discriminating ground beetles of Central Europe, a diverse and well-studied invertebrate taxon. As nuclear markers we determined the 18S rDNA: V4, 18S rDNA: V7 and 28S rDNA: D3 expansion segments for 344 specimens of 75 species. Seventy-three species (97%) of the analysed species could be accurately identified using COI, while the combined approach of all three nuclear markers provided resolution among 71 (95%) of the studied Carabidae. Our results confirm that the analysed nuclear ribosomal expansion segments in combination constitute a valuable and efficient supplement for classical DNA barcoding to avoid potential pitfalls when only mitochondrial data are being used. We also demonstrate the high potential of COI barcodes for the identification of even closely related carabid species.
Review of segmentation process in consumer markets

Directory of Open Access Journals (Sweden)

Veronika Jadczaková

2013-01-01

Full Text Available Although there has been a considerable debate on market segmentation over five decades, attention was merely devoted to single stages of the segmentation process. In doing so, stages as segmentation base selection or segments profiling have been heavily covered in the extant literature, whereas stages as implementation of the marketing strategy or market definition were of a comparably lower interest. Capitalizing on this shortcoming, this paper strives to close the gap and provide each step of the segmentation process with equal treatment. Hence, the objective of this paper is two-fold. First, a snapshot of the segmentation process in a step-by-step fashion will be provided. Second, each step (where possible will be evaluated on chosen criteria by means of description, comparison, analysis and synthesis of 32 academic papers and 13 commercial typology systems. Ultimately, the segmentation stages will be discussed with empirical findings prevalent in the segmentation studies and last but not least suggestions calling for further investigation will be presented. This seven-step-framework may assist when segmenting in practice allowing for more confidential targeting which in turn might prepare grounds for creating of a differential advantage.
Using simulated fluorescence cell micrographs for the evaluation of cell image segmentation algorithms.

Science.gov (United States)

Wiesmann, Veit; Bergler, Matthias; Palmisano, Ralf; Prinzen, Martin; Franz, Daniela; Wittenberg, Thomas

2017-03-18

Manual assessment and evaluation of fluorescent micrograph cell experiments is time-consuming and tedious. Automated segmentation pipelines can ensure efficient and reproducible evaluation and analysis with constant high quality for all images of an experiment. Such cell segmentation approaches are usually validated and rated in comparison to manually annotated micrographs. Nevertheless, manual annotations are prone to errors and display inter- and intra-observer variability which influence the validation results of automated cell segmentation pipelines. We present a new approach to simulate fluorescent cell micrographs that provides an objective ground truth for the validation of cell segmentation methods. The cell simulation was evaluated twofold: (1) An expert observer study shows that the proposed approach generates realistic fluorescent cell micrograph simulations. (2) An automated segmentation pipeline on the simulated fluorescent cell micrographs reproduces segmentation performances of that pipeline on real fluorescent cell micrographs. The proposed simulation approach produces realistic fluorescent cell micrographs with corresponding ground truth. The simulated data is suited to evaluate image segmentation pipelines more efficiently and reproducibly than it is possible on manually annotated real micrographs.
Unsupervised Tattoo Segmentation Combining Bottom-Up and Top-Down Cues

Energy Technology Data Exchange (ETDEWEB)

Allen, Josef D [ORNL

2011-01-01

Tattoo segmentation is challenging due to the complexity and large variance in tattoo structures. We have developed a segmentation algorithm for nding tattoos in an image. Our basic idea is split-merge: split each tattoo image into clusters through a bottom-up process, learn to merge the clusters containing skin and then distinguish tattoo from the other skin via top-down prior in the image itself. Tattoo segmentation with unknown number of clusters is transferred to a gure-ground segmentation. We have applied our segmentation algorithm on a tattoo dataset and the results have shown that our tattoo segmentation system is e cient and suitable for further tattoo classi cation and retrieval purpose.
Development of a Subject-Specific Foot-Ground Contact Model for Walking.

Science.gov (United States)

Jackson, Jennifer N; Hass, Chris J; Fregly, Benjamin J

2016-09-01

Computational walking simulations could facilitate the development of improved treatments for clinical conditions affecting walking ability. Since an effective treatment is likely to change a patient's foot-ground contact pattern and timing, such simulations should ideally utilize deformable foot-ground contact models tailored to the patient's foot anatomy and footwear. However, no study has reported a deformable modeling approach that can reproduce all six ground reaction quantities (expressed as three reaction force components, two center of pressure (CoP) coordinates, and a free reaction moment) for an individual subject during walking. This study proposes such an approach for use in predictive optimizations of walking. To minimize complexity, we modeled each foot as two rigid segments-a hindfoot (HF) segment and a forefoot (FF) segment-connected by a pin joint representing the toes flexion-extension axis. Ground reaction forces (GRFs) and moments acting on each segment were generated by a grid of linear springs with nonlinear damping and Coulomb friction spread across the bottom of each segment. The stiffness and damping of each spring and common friction parameter values for all springs were calibrated for both feet simultaneously via a novel three-stage optimization process that used motion capture and ground reaction data collected from a single walking trial. The sequential three-stage process involved matching (1) the vertical force component, (2) all three force components, and finally (3) all six ground reaction quantities. The calibrated model was tested using four additional walking trials excluded from calibration. With only small changes in input kinematics, the calibrated model reproduced all six ground reaction quantities closely (root mean square (RMS) errors less than 13 N for all three forces, 25 mm for anterior-posterior (AP) CoP, 8 mm for medial-lateral (ML) CoP, and 2 N·m for the free moment) for both feet in all walking trials. The
Boundary segmentation for fluorescence microscopy using steerable filters

Science.gov (United States)

Ho, David Joon; Salama, Paul; Dunn, Kenneth W.; Delp, Edward J.

2017-02-01

Fluorescence microscopy is used to image multiple subcellular structures in living cells which are not readily observed using conventional optical microscopy. Moreover, two-photon microscopy is widely used to image structures deeper in tissue. Recent advancement in fluorescence microscopy has enabled the generation of large data sets of images at different depths, times, and spectral channels. Thus, automatic object segmentation is necessary since manual segmentation would be inefficient and biased. However, automatic segmentation is still a challenging problem as regions of interest may not have well defined boundaries as well as non-uniform pixel intensities. This paper describes a method for segmenting tubular structures in fluorescence microscopy images of rat kidney and liver samples using adaptive histogram equalization, foreground/background segmentation, steerable filters to capture directional tendencies, and connected-component analysis. The results from several data sets demonstrate that our method can segment tubular boundaries successfully. Moreover, our method has better performance when compared to other popular image segmentation methods when using ground truth data obtained via manual segmentation.
Brain tumor segmentation based on a hybrid clustering technique

Directory of Open Access Journals (Sweden)

Eman Abdel-Maksoud

2015-03-01

This paper presents an efficient image segmentation approach using K-means clustering technique integrated with Fuzzy C-means algorithm. It is followed by thresholding and level set segmentation stages to provide an accurate brain tumor detection. The proposed technique can get benefits of the K-means clustering for image segmentation in the aspects of minimal computation time. In addition, it can get advantages of the Fuzzy C-means in the aspects of accuracy. The performance of the proposed image segmentation approach was evaluated by comparing it with some state of the art segmentation algorithms in case of accuracy, processing time, and performance. The accuracy was evaluated by comparing the results with the ground truth of each processed image. The experimental results clarify the effectiveness of our proposed approach to deal with a higher number of segmentation problems via improving the segmentation quality and accuracy in minimal execution time.
AISLE: an automatic volumetric segmentation method for the study of lung allometry.

Science.gov (United States)

Ren, Hongliang; Kazanzides, Peter

2011-01-01

We developed a fully automatic segmentation method for volumetric CT (computer tomography) datasets to support construction of a statistical atlas for the study of allometric laws of the lung. The proposed segmentation method, AISLE (Automated ITK-Snap based on Level-set), is based on the level-set implementation from an existing semi-automatic segmentation program, ITK-Snap. AISLE can segment the lung field without human interaction and provide intermediate graphical results as desired. The preliminary experimental results show that the proposed method can achieve accurate segmentation, in terms of volumetric overlap metric, by comparing with the ground-truth segmentation performed by a radiologist.
Biased figure-ground assignment affects conscious object recognition in spatial neglect.

Science.gov (United States)

Eramudugolla, Ranmalee; Driver, Jon; Mattingley, Jason B

2010-09-01

Unilateral spatial neglect is a disorder of attention and spatial representation, in which early visual processes such as figure-ground segmentation have been assumed to be largely intact. There is evidence, however, that the spatial attention bias underlying neglect can bias the segmentation of a figural region from its background. Relatively few studies have explicitly examined the effect of spatial neglect on processing the figures that result from such scene segmentation. Here, we show that a neglect patient's bias in figure-ground segmentation directly influences his conscious recognition of these figures. By varying the relative salience of figural and background regions in static, two-dimensional displays, we show that competition between elements in such displays can modulate a neglect patient's ability to recognise parsed figures in a scene. The findings provide insight into the interaction between scene segmentation, explicit object recognition, and attention.
Shearlet transform in aliased ground roll attenuation and its comparison with f-k filtering and curvelet transform

Science.gov (United States)

Abolfazl Hosseini, Seyed; Javaherian, Abdolrahim; Hassani, Hossien; Torabi, Siyavash; Sadri, Maryam

2015-06-01

Ground roll, which is a Rayleigh surface wave that exists in land seismic data, may mask reflections. Sometimes ground roll is spatially aliased. Attenuation of aliased ground roll is of importance in seismic data processing. Different methods have been developed to attenuate ground roll. The shearlet transform is a directional and multidimensional transform that generates subimages of an input image in different directions and scales. Events with different dips are separated in these subimages. In this study, the shearlet transform is used to attenuate the aliased ground roll. To do this, a shot record is divided into several segments, and the appropriate mute zone is defined for all segments. The shearlet transform is applied to each segment. The subimages related to the non-aliased and aliased ground roll are identified by plotting the energy distributions of subimages with visual checking. Then, muting filters are used on selected subimages. The inverse shearlet transform is applied to the filtered segment. This procedure is repeated for all segments. Finally, all filtered segments are merged using the Hanning window. This method of aliased ground roll attenuation was tested on a synthetic dataset and a field shot record from the west of Iran. The synthetic shot record included strong aliased ground roll, whereas the field shot record did not. To produce the strong aliased ground roll on the field shot record, the data were resampled in the offset direction from 30 to 60 m. To show the performance of the shearlet transform in attenuating the aliased ground roll, we compared the shearlet transform with the f-k filtering and curvelet transform. We showed that the performance of the shearlet transform in the aliased ground roll attenuation is better than that of the f-k filtering and curvelet transform in both the synthetic and field shot records. However, when the dip and frequency content of the aliased ground roll are the same as the reflections, ability of
A proposed framework for consensus-based lung tumour volume auto-segmentation in 4D computed tomography imaging

International Nuclear Information System (INIS)

Martin, Spencer; Rodrigues, George; Gaede, Stewart; Brophy, Mark; Barron, John L; Beauchemin, Steven S; Palma, David; Louie, Alexander V; Yu, Edward; Yaremko, Brian; Ahmad, Belal

2015-01-01

This work aims to propose and validate a framework for tumour volume auto-segmentation based on ground-truth estimates derived from multi-physician input contours to expedite 4D-CT based lung tumour volume delineation. 4D-CT datasets of ten non-small cell lung cancer (NSCLC) patients were manually segmented by 6 physicians. Multi-expert ground truth (GT) estimates were constructed using the STAPLE algorithm for the gross tumour volume (GTV) on all respiratory phases. Next, using a deformable model-based method, multi-expert GT on each individual phase of the 4D-CT dataset was propagated to all other phases providing auto-segmented GTVs and motion encompassing internal gross target volumes (IGTVs) based on GT estimates (STAPLE) from each respiratory phase of the 4D-CT dataset. Accuracy assessment of auto-segmentation employed graph cuts for 3D-shape reconstruction and point-set registration-based analysis yielding volumetric and distance-based measures. STAPLE-based auto-segmented GTV accuracy ranged from (81.51 ± 1.92) to (97.27 ± 0.28)% volumetric overlap of the estimated ground truth. IGTV auto-segmentation showed significantly improved accuracies with reduced variance for all patients ranging from 90.87 to 98.57% volumetric overlap of the ground truth volume. Additional metrics supported these observations with statistical significance. Accuracy of auto-segmentation was shown to be largely independent of selection of the initial propagation phase. IGTV construction based on auto-segmented GTVs within the 4D-CT dataset provided accurate and reliable target volumes compared to manual segmentation-based GT estimates. While inter-/intra-observer effects were largely mitigated, the proposed segmentation workflow is more complex than that of current clinical practice and requires further development. (paper)
A proposed framework for consensus-based lung tumour volume auto-segmentation in 4D computed tomography imaging

Science.gov (United States)

Martin, Spencer; Brophy, Mark; Palma, David; Louie, Alexander V.; Yu, Edward; Yaremko, Brian; Ahmad, Belal; Barron, John L.; Beauchemin, Steven S.; Rodrigues, George; Gaede, Stewart

2015-02-01

This work aims to propose and validate a framework for tumour volume auto-segmentation based on ground-truth estimates derived from multi-physician input contours to expedite 4D-CT based lung tumour volume delineation. 4D-CT datasets of ten non-small cell lung cancer (NSCLC) patients were manually segmented by 6 physicians. Multi-expert ground truth (GT) estimates were constructed using the STAPLE algorithm for the gross tumour volume (GTV) on all respiratory phases. Next, using a deformable model-based method, multi-expert GT on each individual phase of the 4D-CT dataset was propagated to all other phases providing auto-segmented GTVs and motion encompassing internal gross target volumes (IGTVs) based on GT estimates (STAPLE) from each respiratory phase of the 4D-CT dataset. Accuracy assessment of auto-segmentation employed graph cuts for 3D-shape reconstruction and point-set registration-based analysis yielding volumetric and distance-based measures. STAPLE-based auto-segmented GTV accuracy ranged from (81.51 ± 1.92) to (97.27 ± 0.28)% volumetric overlap of the estimated ground truth. IGTV auto-segmentation showed significantly improved accuracies with reduced variance for all patients ranging from 90.87 to 98.57% volumetric overlap of the ground truth volume. Additional metrics supported these observations with statistical significance. Accuracy of auto-segmentation was shown to be largely independent of selection of the initial propagation phase. IGTV construction based on auto-segmented GTVs within the 4D-CT dataset provided accurate and reliable target volumes compared to manual segmentation-based GT estimates. While inter-/intra-observer effects were largely mitigated, the proposed segmentation workflow is more complex than that of current clinical practice and requires further development.
Methods for recognition and segmentation of active fault

International Nuclear Information System (INIS)

Hyun, Chang Hun; Noh, Myung Hyun; Lee, Kieh Hwa; Chang, Tae Woo; Kyung, Jai Bok; Kim, Ki Young

2000-03-01

In order to identify and segment the active faults, the literatures of structural geology, paleoseismology, and geophysical explorations were investigated. The existing structural geological criteria for segmenting active faults were examined. These are mostly based on normal fault systems, thus, the additional criteria are demanded for application to different types of fault systems. Definition of the seismogenic fault, characteristics of fault activity, criteria and study results of fault segmentation, relationship between segmented fault length and maximum displacement, and estimation of seismic risk of segmented faults were examined in paleoseismic study. The history of earthquake such as dynamic pattern of faults, return period, and magnitude of the maximum earthquake originated by fault activity can be revealed by the study. It is confirmed through various case studies that numerous geophysical explorations including electrical resistivity, land seismic, marine seismic, ground-penetrating radar, magnetic, and gravity surveys have been efficiently applied to the recognition and segmentation of active faults
Survivability enhancement study for C/sup 3/I/BM (communications, command, control and intelligence/battle management) ground segments: Final report

Energy Technology Data Exchange (ETDEWEB)

1986-10-30

This study involves a concept developed by the Fairchild Space Company which is directly applicable to the Strategic Defense Initiative (SDI) Program as well as other national security programs requiring reliable, secure and survivable telecommunications systems. The overall objective of this study program was to determine the feasibility of combining and integrating long-lived, compact, autonomous isotope power sources with fiber optic and other types of ground segments of the SDI communications, command, control and intelligence/battle management (C/sup 3/I/BM) system in order to significantly enhance the survivability of those critical systems, especially against the potential threats of electromagnetic pulse(s) (EMP) resulting from high altitude nuclear weapon explosion(s). 28 figs., 2 tabs.
Multi-modal RGB–Depth–Thermal Human Body Segmentation

DEFF Research Database (Denmark)

Palmero, Cristina; Clapés, Albert; Bahnsen, Chris

2016-01-01

This work addresses the problem of human body segmentation from multi-modal visual cues as a first stage of automatic human behavior analysis. We propose a novel RGB-Depth-Thermal dataset along with a multi-modal seg- mentation baseline. The several modalities are registered us- ing a calibration...... to other state-of-the-art meth- ods, obtaining an overlap above 75% on the novel dataset when compared to the manually annotated ground-truth of human segmentations....
The CRYOSAT-2 Payload Ground Segment: Data Processing Status and Data Access

Science.gov (United States)

Parrinello, T.; Frommknecht, B.; Gilles, P.

2010-12-01

Selected as the first Earth Explorer Opportunity mission and following the launch failure of Cryosat-1 in 2005, the Cryosat-2 mission was launched on the 8th April 2010 and it is the first European ice mission dedicated to monitoring precise changes in the thickness of polar ice sheets and floating sea ice over a 3-year period. The main CryoSat-2 mission objectives can be summarised in the determination of the regional and basin-scale trends in perennial Arctic sea ice thickness and mass, and in the determination of regional and total contributions to global sea level of the Antarctic and Greenland Ice. Therefore, the observations made over the life time of the mission will provide conclusive evidence as to whether there is a trend towards diminishing polar ice cover and consequently improve our understanding of the relationship between ice and global climate change. Cryosat-2 carries an innovative radar altimeter called the Synthetic Aperture Interferometric Altimeter (SIRAL) with two antennas and with extended capabilities to meet the measurement requirements for ice-sheets elevation and sea-ice freeboard. Scope of this paper is to describe the Cryosat Ground Segment and its main function to satisfy the Cryosat mission requirements. In particular, the paper will discuss the processing steps necessary to produce SIRAL L1b waveform power data and the SIRAL L2 geophysical elevation data from the raw data acquired by the satellite. The papers will also present the current status of the data processing in terms of completeness, availability and data access to the scientific community.
Individual Building Rooftop and Tree Crown Segmentation from High-Resolution Urban Aerial Optical Images

Directory of Open Access Journals (Sweden)

Jichao Jiao

2016-01-01

Full Text Available We segment buildings and trees from aerial photographs by using superpixels, and we estimate the tree’s parameters by using a cost function proposed in this paper. A method based on image complexity is proposed to refine superpixels boundaries. In order to classify buildings from ground and classify trees from grass, the salient feature vectors that include colors, Features from Accelerated Segment Test (FAST corners, and Gabor edges are extracted from refined superpixels. The vectors are used to train the classifier based on Naive Bayes classifier. The trained classifier is used to classify refined superpixels as object or nonobject. The properties of a tree, including its locations and radius, are estimated by minimizing the cost function. The shadow is used to calculate the tree height using sun angle and the time when the image was taken. Our segmentation algorithm is compared with other two state-of-the-art segmentation algorithms, and the tree parameters obtained in this paper are compared to the ground truth data. Experiments show that the proposed method can segment trees and buildings appropriately, yielding higher precision and better recall rates, and the tree parameters are in good agreement with the ground truth data.

Metrics for image segmentation

Science.gov (United States)

Rees, Gareth; Greenway, Phil; Morray, Denise

1998-07-01

An important challenge in mapping image-processing techniques onto applications is the lack of quantitative performance measures. From a systems engineering perspective these are essential if system level requirements are to be decomposed into sub-system requirements which can be understood in terms of algorithm selection and performance optimization. Nowhere in computer vision is this more evident than in the area of image segmentation. This is a vigorous and innovative research activity, but even after nearly two decades of progress, it remains almost impossible to answer the question 'what would the performance of this segmentation algorithm be under these new conditions?' To begin to address this shortcoming, we have devised a well-principled metric for assessing the relative performance of two segmentation algorithms. This allows meaningful objective comparisons to be made between their outputs. It also estimates the absolute performance of an algorithm given ground truth. Our approach is an information theoretic one. In this paper, we describe the theory and motivation of our method, and present practical results obtained from a range of state of the art segmentation methods. We demonstrate that it is possible to measure the objective performance of these algorithms, and to use the information so gained to provide clues about how their performance might be improved.
TARDEC Overview: Ground Vehicle Power and Mobility

Science.gov (United States)

2011-02-04

Fuel & Water Distribution • Force Sustainment • Construction Equipment • Bridging • Assured Mobility Systems Robotics • TALON • PackBot • MARCbot...Equipment • Mechanical Countermine Equipment • Tactical Bridging Intelligent Ground Systems • Autonomous Robotics Systems • Safe Operations...Test Cell • Hybrid Electric Reconfigurable Moveable Integration Testbed (HERMIT) • Electro-chemical Analysis and Research Lab (EARL) • Battery Lab • Air
Contour tracing for segmentation of mammographic masses

International Nuclear Information System (INIS)

Elter, Matthias; Held, Christian; Wittenberg, Thomas

2010-01-01

CADx systems have the potential to support radiologists in the difficult task of discriminating benign and malignant mammographic lesions. The segmentation of mammographic masses from the background tissue is an important module of CADx systems designed for the characterization of mass lesions. In this work, a novel approach to this task is presented. The segmentation is performed by automatically tracing the mass' contour in-between manually provided landmark points defined on the mass' margin. The performance of the proposed approach is compared to the performance of implementations of three state-of-the-art approaches based on region growing and dynamic programming. For an unbiased comparison of the different segmentation approaches, optimal parameters are selected for each approach by means of tenfold cross-validation and a genetic algorithm. Furthermore, segmentation performance is evaluated on a dataset of ROI and ground-truth pairs. The proposed method outperforms the three state-of-the-art methods. The benchmark dataset will be made available with publication of this paper and will be the first publicly available benchmark dataset for mass segmentation.
Fully automatic segmentation of arbitrarily shaped fiducial markers in cone-beam CT projections

DEFF Research Database (Denmark)

Bertholet, Jenny; Wan, Hanlin; Toftegaard, Jakob

2017-01-01

segmentation, the DPTB algorithm generates and uses a 3D marker model to create 2D templates at any projection angle. The 2D templates are used to segment the marker position as the position with highest normalized cross-correlation in a search area centered at the DP segmented position. The accuracy of the DP...... algorithm and the new DPTB algorithm was quantified as the 2D segmentation error (pixels) compared to a manual ground truth segmentation for 97 markers in the projection images of CBCT scans of 40 patients. Also the fraction of wrong segmentations, defined as 2D errors larger than 5 pixels, was calculated...
Limitations and pitfalls of Couinaud's segmentation of the liver in transaxial Imaging

Energy Technology Data Exchange (ETDEWEB)

Strunk, H; Textor, J; Willinek, W [Department of Radiology, University of Bonn, Sigmund Freud-Strasse 25, 53105, Bonn (Germany); Stuckmann, G [Department of Radiology, Kantonsspital Winterthur (Switzerland)

2003-11-01

The segmental anatomy of the human liver has become a matter of increasing interest to the radiologist, especially in view of the need for an accurate preoperative localization of focal hepatic lesions. In this review article first an overview of the different classical concepts for delineating segmental and subsegmental anatomy on US, transaxial CT, and MR images is given. Essentially, these procedures are based on Couinaud's concept of three vertical planes that divide the liver into four segments and of a transverse scissura that further subdivides the segments into two subsegments each. In a second part, the limitations of these methods are delineated and discussed with the conclusion that if exact preoperative localization of hepatic lesions is needed, tumor must be located relative to the avascular planes between the different portal territories. (orig.)
Limitations and pitfalls of Couinaud's segmentation of the liver in transaxial Imaging

International Nuclear Information System (INIS)

Strunk, H.; Textor, J.; Willinek, W.; Stuckmann, G.

2003-01-01

The segmental anatomy of the human liver has become a matter of increasing interest to the radiologist, especially in view of the need for an accurate preoperative localization of focal hepatic lesions. In this review article first an overview of the different classical concepts for delineating segmental and subsegmental anatomy on US, transaxial CT, and MR images is given. Essentially, these procedures are based on Couinaud's concept of three vertical planes that divide the liver into four segments and of a transverse scissura that further subdivides the segments into two subsegments each. In a second part, the limitations of these methods are delineated and discussed with the conclusion that if exact preoperative localization of hepatic lesions is needed, tumor must be located relative to the avascular planes between the different portal territories. (orig.)
An overview on the equatorial electrojet theoretical grounds

International Nuclear Information System (INIS)

Zamlutti, C.J.; Sobral, J.H.A.; Abdu, M.A.

1988-01-01

The grounds on which the equatorial electrojet theory is based are reexamined in a way as to suggest specific additional implementations in the existing electrodynamical modeling of this phenomena, making use of now existing improved computer processing speeds. (author) [pt
Comparison of atlas-based techniques for whole-body bone segmentation

DEFF Research Database (Denmark)

Arabi, Hossein; Zaidi, Habib

2017-01-01

out in terms of estimating bone extraction accuracy from whole-body MRI using standard metrics, such as Dice similarity (DSC) and relative volume difference (RVD) considering bony structures obtained from intensity thresholding of the reference CT images as the ground truth. Considering the Dice....../MRI. To this end, a variety of atlas-based segmentation strategies commonly used in medical image segmentation and pseudo-CT generation were implemented and evaluated in terms of whole-body bone segmentation accuracy. Bone segmentation was performed on 23 whole-body CT/MR image pairs via leave-one-out cross...... validation procedure. The evaluated segmentation techniques include: (i) intensity averaging (IA), (ii) majority voting (MV), (iii) global and (iv) local (voxel-wise) weighting atlas fusion frameworks implemented utilizing normalized mutual information (NMI), normalized cross-correlation (NCC) and mean...
Measurement of ground motion in various sites

International Nuclear Information System (INIS)

Bialowons, W.; Amirikas, R.; Bertolini, A.; Kruecker, D.

2007-04-01

Ground vibrations may affect low emittance beam transport in linear colliders, Free Electron Lasers (FEL) and synchrotron radiation facilities. This paper is an overview of a study program to measure ground vibrations in various sites which can be used for site characterization in relation to accelerator design. Commercial broadband seismometers have been used to measure ground vibrations and the resultant database is available to the scientific community. The methodology employed is to use the same equipment and data analysis tools for ease of comparison. This database of ground vibrations taken in 19 sites around the world is first of its kind. (orig.)
Automatic aortic root segmentation in CTA whole-body dataset

Science.gov (United States)

Gao, Xinpei; Kitslaar, Pieter H.; Scholte, Arthur J. H. A.; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke; Reiber, Johan H. C.

2016-03-01

Trans-catheter aortic valve replacement (TAVR) is an evolving technique for patients with serious aortic stenosis disease. Typically, in this application a CTA data set is obtained of the patient's arterial system from the subclavian artery to the femoral arteries, to evaluate the quality of the vascular access route and analyze the aortic root to determine if and which prosthesis should be used. In this paper, we concentrate on the automated segmentation of the aortic root. The purpose of this study was to automatically segment the aortic root in computed tomography angiography (CTA) datasets to support TAVR procedures. The method in this study includes 4 major steps. First, the patient's cardiac CTA image was resampled to reduce the computation time. Next, the cardiac CTA image was segmented using an atlas-based approach. The most similar atlas was selected from a total of 8 atlases based on its image similarity to the input CTA image. Third, the aortic root segmentation from the previous step was transferred to the patient's whole-body CTA image by affine registration and refined in the fourth step using a deformable subdivision surface model fitting procedure based on image intensity. The pipeline was applied to 20 patients. The ground truth was created by an analyst who semi-automatically corrected the contours of the automatic method, where necessary. The average Dice similarity index between the segmentations of the automatic method and the ground truth was found to be 0.965±0.024. In conclusion, the current results are very promising.
High Frequency Near-Field Ground Motion Excited by Strike-Slip Step Overs

Science.gov (United States)

Hu, Feng; Wen, Jian; Chen, Xiaofei

2018-03-01

We performed dynamic rupture simulations on step overs with 1-2 km step widths and present their corresponding horizontal peak ground velocity distributions in the near field within different frequency ranges. The rupture speeds on fault segments are determinant in controlling the near-field ground motion. A Mach wave impact area at the free surface, which can be inferred from the distribution of the ratio of the maximum fault-strike particle velocity to the maximum fault-normal particle velocity, is generated in the near field with sustained supershear ruptures on fault segments, and the Mach wave impact area cannot be detected with unsustained supershear ruptures alone. Sub-Rayleigh ruptures produce stronger ground motions beyond the end of fault segments. The existence of a low-velocity layer close to the free surface generates large amounts of high-frequency seismic radiation at step over discontinuities. For near-vertical step overs, normal stress perturbations on the primary fault caused by dipping structures affect the rupture speed transition, which further determines the distribution of the near-field ground motion. The presence of an extensional linking fault enhances the near-field ground motion in the extensional regime. This work helps us understand the characteristics of high-frequency seismic radiation in the vicinities of step overs and provides useful insights for interpreting the rupture speed distributions derived from the characteristics of near-field ground motion.
Overview and status of ITER Cryostat manufacturing

Energy Technology Data Exchange (ETDEWEB)

Bhardwaj, Anil K., E-mail: anil.bhardwaj@iter-india.org [ITER-India, Institute For Plasma Research, A-29, GIDC Electronics Estate, Sector-25, Gandhinagar 382016 (India); Gupta, Girish; Prajapati, Rajnikant; Joshi, Vaibhav; Patel, Mitul; Bhavsar, Jagrut; More, Vipul; Jindal, Mukesh; Bhattacharya, Avik; Jogi, Gourav; Palaliya, Amit; Jha, Saroj; Pandey, Manish; Shukla, Dileep [ITER-India, Institute For Plasma Research, A-29, GIDC Electronics Estate, Sector-25, Gandhinagar 382016 (India); Iyer, Ganesh; Jadhav, Pandurang; Goyal, Dipesh; Desai, Anish [Larsen & Toubro Limited, Heavy Engineering, Hazira Manufacturing Complex, Gujarat (India); Sekachev, I.; Vitupier, Guillaume [ITER Organization, Route de Vinon sur Verdon – CS 90046, 13067 Saint Paul Lez Durance Cedex (France); and others

2016-11-01

Highlights: • Manufacturing status of one of the largest and the heaviest fully welded stainless steel vacuum chambers in the world (ITER Cryostat). • Overview of manufacturing stages and its segmentation. • Overview of manufacturing procedures and assembly and installation. - Abstract: One of ITER-India's commitments to the ITER Organization is procurement of the ITER Cryostat. It is a large vacuum vessel (∼29 m dia. and ∼29 m height), which is made up of 304/304 L dual marked stainless steel and has a total mass over 3500 t. The thickness of the vessel wall varies from 50 mm to 190 mm. It is one of the largest and the heaviest fully welded stainless steel vacuum chambers in the world which provides vacuum thermal insulation for the superconducting magnets operating at 4.5 K and for the thermal shield operating at 80 K. It also mechanically supports the magnet system along with the vacuum vessel (VV). The cryostat is designed and constructed according to ASME Section-VIII Division-2 with additional ITER Vacuum Handbook requirements and it is classified as protection important component (PIC-2). Manufacturing of cryostat segments is ongoing in India; sub-assembly of four major sections of the cryostat from the segments will be done at the ITER site in a temporary workshop building and the final assembly will be done in the pit of the tokamak building, the final location. The cryostat manufacturing contract has been awarded to Larsen and Toubro Limited in August 2012 after completion of design [4] and signing of Procurement Arrangement [1] with ITER Organization. Manufacturing of the cryostat was started in January 2014 after approval of the manufacturing drawings and procedures. The temporary workshop of 44 m × 110 m × 26 m in height has been completed in November 2014 at the ITER site with a 200 t crane installed. This paper gives an overview and the status of the cryostat manufacturing.
Automated segmentation of pulmonary structures in thoracic computed tomography scans: a review

International Nuclear Information System (INIS)

Van Rikxoort, Eva M; Van Ginneken, Bram

2013-01-01

Computed tomography (CT) is the modality of choice for imaging the lungs in vivo. Sub-millimeter isotropic images of the lungs can be obtained within seconds, allowing the detection of small lesions and detailed analysis of disease processes. The high resolution of thoracic CT and the high prevalence of lung diseases require a high degree of automation in the analysis pipeline. The automated segmentation of pulmonary structures in thoracic CT has been an important research topic for over a decade now. This systematic review provides an overview of current literature. We discuss segmentation methods for the lungs, the pulmonary vasculature, the airways, including airway tree construction and airway wall segmentation, the fissures, the lobes and the pulmonary segments. For each topic, the current state of the art is summarized, and topics for future research are identified. (topical review)
Active mask segmentation of fluorescence microscope images.

Science.gov (United States)

Srinivasa, Gowri; Fickus, Matthew C; Guo, Yusong; Linstedt, Adam D; Kovacević, Jelena

2009-08-01

We propose a new active mask algorithm for the segmentation of fluorescence microscope images of punctate patterns. It combines the (a) flexibility offered by active-contour methods, (b) speed offered by multiresolution methods, (c) smoothing offered by multiscale methods, and (d) statistical modeling offered by region-growing methods into a fast and accurate segmentation tool. The framework moves from the idea of the "contour" to that of "inside and outside," or masks, allowing for easy multidimensional segmentation. It adapts to the topology of the image through the use of multiple masks. The algorithm is almost invariant under initialization, allowing for random initialization, and uses a few easily tunable parameters. Experiments show that the active mask algorithm matches the ground truth well and outperforms the algorithm widely used in fluorescence microscopy, seeded watershed, both qualitatively, as well as quantitatively.
Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions.

Science.gov (United States)

Akkus, Zeynettin; Galimzianova, Alfiia; Hoogi, Assaf; Rubin, Daniel L; Erickson, Bradley J

2017-08-01

Quantitative analysis of brain MRI is routine for many neurological diseases and conditions and relies on accurate segmentation of structures of interest. Deep learning-based segmentation approaches for brain MRI are gaining interest due to their self-learning and generalization ability over large amounts of data. As the deep learning architectures are becoming more mature, they gradually outperform previous state-of-the-art classical machine learning algorithms. This review aims to provide an overview of current deep learning-based segmentation approaches for quantitative brain MRI. First we review the current deep learning architectures used for segmentation of anatomical brain structures and brain lesions. Next, the performance, speed, and properties of deep learning approaches are summarized and discussed. Finally, we provide a critical assessment of the current state and identify likely future developments and trends.
Pairwise Trajectory Management (PTM): Concept Overview

Science.gov (United States)

Jones, Kenneth M.; Graff, Thomas J.; Chartrand, Ryan C.; Carreno, Victor; Kibler, Jennifer L.

2017-01-01

Pairwise Trajectory Management (PTM) is an Interval Management (IM) concept that utilizes airborne and ground-based capabilities to enable the implementation of airborne pairwise spacing capabilities in oceanic regions. The goal of PTM is to use airborne surveillance and tools to manage an "at or greater than" inter-aircraft spacing. Due to the precision of Automatic Dependent Surveillance-Broadcast (ADS-B) information and the use of airborne spacing guidance, the PTM minimum spacing distance will be less than distances a controller can support with current automation systems that support oceanic operations. Ground tools assist the controller in evaluating the traffic picture and determining appropriate PTM clearances to be issued. Avionics systems provide guidance information that allows the flight crew to conform to the PTM clearance issued by the controller. The combination of a reduced minimum distance and airborne spacing management will increase the capacity and efficiency of aircraft operations at a given altitude or volume of airspace. This paper provides an overview of the proposed application, description of a few key scenarios, high level discussion of expected air and ground equipment and procedure changes, overview of a potential flight crew human-machine interface that would support PTM operations and some initial PTM benefits results.
Figure-ground segregation modulates apparent motion.

Science.gov (United States)

Ramachandran, V S; Anstis, S

1986-01-01

We explored the relationship between figure-ground segmentation and apparent motion. Results suggest that: static elements in the surround can eliminate apparent motion of a cluster of dots in the centre, but only if the cluster and surround have similar "grain" or texture; outlines that define occluding surfaces are taken into account by the motion mechanism; the brain uses a hierarchy of precedence rules in attributing motion to different segments of the visual scene. Being designated as "figure" confers a high rank in this scheme of priorities.
Multi-granularity synthesis segmentation for high spatial resolution Remote sensing images

International Nuclear Information System (INIS)

Yi, Lina; Liu, Pengfei; Qiao, Xiaojun; Zhang, Xiaoning; Gao, Yuan; Feng, Boyan

2014-01-01

Traditional segmentation method can only partition an image in a single granularity space, with segmentation accuracy limited to the single granularity space. This paper proposes a multi-granularity synthesis segmentation method for high spatial resolution remote sensing images based on a quotient space model. Firstly, we divide the whole image area into multiple granules (regions), each region is consisted of ground objects that have similar optimal segmentation scale, and then select and synthesize the sub-optimal segmentations of each region to get the final segmentation result. To validate this method, the land cover category map is used to guide the scale synthesis of multi-scale image segmentations for Quickbird image land use classification. Firstly, the image is coarsely divided into multiple regions, each region belongs to a certain land cover category. Then multi-scale segmentation results are generated by the Mumford-Shah function based region merging method. For each land cover category, the optimal segmentation scale is selected by the supervised segmentation accuracy assessment method. Finally, the optimal scales of segmentation results are synthesized under the guide of land cover category. Experiments show that the multi-granularity synthesis segmentation can produce more accurate segmentation than that of a single granularity space and benefit the classification
Overview of ground coupled heat pump research and technology transfer activities

Science.gov (United States)

Baxter, V. D.; Mei, V. C.

Highlights of DOE-sponsored ground coupled heat pump (GCHP) research at Oak Ridge National Laboratory (ORNL) are presented. ORNL, in cooperation with Niagara Mohawk Power Company, Climate Master, Inc., and Brookhaven National Laboratory developed and demonstrated an advanced GCHP design concept with shorter ground coils that can reduce installed costs for northern climates. In these areas it can also enhance the competitiveness of GCHP systems versus air-source heat pumps by lowering their payback from 6 to 7 years to 3 to 5 years. Ground coil heat exchanger models (based primarily on first principles) have been developed and used by others to generate less conservative ground coil sizing methods. An aggressive technology transfer initiative was undertaken to publicize results of this research and make it available to the industry. Included in this effort were an international workshop, trade press releases and articles, and participation in a live teleconference on GCHP technology.
A Novel Unsupervised Segmentation Quality Evaluation Method for Remote Sensing Images.

Science.gov (United States)

Gao, Han; Tang, Yunwei; Jing, Linhai; Li, Hui; Ding, Haifeng

2017-10-24

The segmentation of a high spatial resolution remote sensing image is a critical step in geographic object-based image analysis (GEOBIA). Evaluating the performance of segmentation without ground truth data, i.e., unsupervised evaluation, is important for the comparison of segmentation algorithms and the automatic selection of optimal parameters. This unsupervised strategy currently faces several challenges in practice, such as difficulties in designing effective indicators and limitations of the spectral values in the feature representation. This study proposes a novel unsupervised evaluation method to quantitatively measure the quality of segmentation results to overcome these problems. In this method, multiple spectral and spatial features of images are first extracted simultaneously and then integrated into a feature set to improve the quality of the feature representation of ground objects. The indicators designed for spatial stratified heterogeneity and spatial autocorrelation are included to estimate the properties of the segments in this integrated feature set. These two indicators are then combined into a global assessment metric as the final quality score. The trade-offs of the combined indicators are accounted for using a strategy based on the Mahalanobis distance, which can be exhibited geometrically. The method is tested on two segmentation algorithms and three testing images. The proposed method is compared with two existing unsupervised methods and a supervised method to confirm its capabilities. Through comparison and visual analysis, the results verified the effectiveness of the proposed method and demonstrated the reliability and improvements of this method with respect to other methods.

A Novel Unsupervised Segmentation Quality Evaluation Method for Remote Sensing Images

Directory of Open Access Journals (Sweden)

Han Gao

2017-10-01

Full Text Available The segmentation of a high spatial resolution remote sensing image is a critical step in geographic object-based image analysis (GEOBIA. Evaluating the performance of segmentation without ground truth data, i.e., unsupervised evaluation, is important for the comparison of segmentation algorithms and the automatic selection of optimal parameters. This unsupervised strategy currently faces several challenges in practice, such as difficulties in designing effective indicators and limitations of the spectral values in the feature representation. This study proposes a novel unsupervised evaluation method to quantitatively measure the quality of segmentation results to overcome these problems. In this method, multiple spectral and spatial features of images are first extracted simultaneously and then integrated into a feature set to improve the quality of the feature representation of ground objects. The indicators designed for spatial stratified heterogeneity and spatial autocorrelation are included to estimate the properties of the segments in this integrated feature set. These two indicators are then combined into a global assessment metric as the final quality score. The trade-offs of the combined indicators are accounted for using a strategy based on the Mahalanobis distance, which can be exhibited geometrically. The method is tested on two segmentation algorithms and three testing images. The proposed method is compared with two existing unsupervised methods and a supervised method to confirm its capabilities. Through comparison and visual analysis, the results verified the effectiveness of the proposed method and demonstrated the reliability and improvements of this method with respect to other methods.
Superpixel-based segmentation of muscle fibers in multi-channel microscopy.

Science.gov (United States)

Nguyen, Binh P; Heemskerk, Hans; So, Peter T C; Tucker-Kellogg, Lisa

2016-12-05

Confetti fluorescence and other multi-color genetic labelling strategies are useful for observing stem cell regeneration and for other problems of cell lineage tracing. One difficulty of such strategies is segmenting the cell boundaries, which is a very different problem from segmenting color images from the real world. This paper addresses the difficulties and presents a superpixel-based framework for segmentation of regenerated muscle fibers in mice. We propose to integrate an edge detector into a superpixel algorithm and customize the method for multi-channel images. The enhanced superpixel method outperforms the original and another advanced superpixel algorithm in terms of both boundary recall and under-segmentation error. Our framework was applied to cross-section and lateral section images of regenerated muscle fibers from confetti-fluorescent mice. Compared with "ground-truth" segmentations, our framework yielded median Dice similarity coefficients of 0.92 and higher. Our segmentation framework is flexible and provides very good segmentations of multi-color muscle fibers. We anticipate our methods will be useful for segmenting a variety of tissues in confetti fluorecent mice and in mice with similar multi-color labels.
Biodiesel Production from Spent Coffee Grounds

Science.gov (United States)

Blinová, Lenka; Bartošová, Alica; Sirotiak, Maroš

2017-06-01

The residue after brewing the spent coffee grounds is an oil-containing waste material having a potential of being used as biodiesel feedstock. Biodiesel production from the waste coffee grounds oil involves collection and transportation of coffee residue, drying, oil extraction, and finally production of biodiesel. Different methods of oil extraction with organic solvents under different conditions show significant differences in the extraction yields. In the manufacturing of biodiesel from coffee oil, the level of reaction completion strongly depends on the quality of the feedstock oil. This paper presents an overview of oil extraction and a method of biodiesel production from spent coffee grounds.
Segmentation and packaging reactor vessels internals

International Nuclear Information System (INIS)

Boucau, Joseph

2014-01-01

segmentation and packaging project. The purpose of this presentation is to provide an overview of the Westinghouse reactor internals segmentation experience with a focus on optimum segmentation and packaging plans and eventually minimization of the number of waste containers. (author)
Pollutant infiltration and ground water management

International Nuclear Information System (INIS)

1993-01-01

Following a short overview of hazard potentials for ground water in Germany, this book, which was compiled by the technical committee of DVWK on ground water use, discusses the natural scientific bases of pollutant movement to and in ground water. It points out whether and to what extent soil/ground water systems can be protected from harmful influences, and indicates relative strategies. Two zones are distinguished: the unsaturated zone, where local defence and remedial measures are frequently possible, and the saturated zone. From the protective function of geological systems, which is always pollutant-specific, criteria are derived for judging the systems generally, or at least regarding entire classes of pollutants. Finally, the impact of the infiltration of pollutants into ground water on its use as drinking water is pointed out and an estimate of the cost of remedial measures is given. (orig.) [de
High-dynamic-range imaging for cloud segmentation

Science.gov (United States)

Dev, Soumyabrata; Savoy, Florian M.; Lee, Yee Hui; Winkler, Stefan

2018-04-01

Sky-cloud images obtained from ground-based sky cameras are usually captured using a fisheye lens with a wide field of view. However, the sky exhibits a large dynamic range in terms of luminance, more than a conventional camera can capture. It is thus difficult to capture the details of an entire scene with a regular camera in a single shot. In most cases, the circumsolar region is overexposed, and the regions near the horizon are underexposed. This renders cloud segmentation for such images difficult. In this paper, we propose HDRCloudSeg - an effective method for cloud segmentation using high-dynamic-range (HDR) imaging based on multi-exposure fusion. We describe the HDR image generation process and release a new database to the community for benchmarking. Our proposed approach is the first using HDR radiance maps for cloud segmentation and achieves very good results.
Shape-specific perceptual learning in a figure-ground segregation task.

Science.gov (United States)

Yi, Do-Joon; Olson, Ingrid R; Chun, Marvin M

2006-03-01

What does perceptual experience contribute to figure-ground segregation? To study this question, we trained observers to search for symmetric dot patterns embedded in random dot backgrounds. Training improved shape segmentation, but learning did not completely transfer either to untrained locations or to untrained shapes. Such partial specificity persisted for a month after training. Interestingly, training on shapes in empty backgrounds did not help segmentation of the trained shapes in noisy backgrounds. Our results suggest that perceptual training increases the involvement of early sensory neurons in the segmentation of trained shapes, and that successful segmentation requires perceptual skills beyond shape recognition alone.
Ibis ground calibration

International Nuclear Information System (INIS)

Bird, A.J.; Barlow, E.J.; Tikkanen, T.; Bazzano, A.; Del Santo, M.; Ubertini, P.; Blondel, C.; Laurent, P.; Lebrun, F.; Di Cocco, G.; Malaguti, E.; Gabriele, M.; La Rosa, G.; Segreto, A.; Quadrini, E.; Volkmer, R.

2003-01-01

We present an overview of results obtained from IBIS ground calibrations. The spectral and spatial characteristics of the detector planes and surrounding passive materials have been determined through a series of calibration campaigns. Measurements of pixel gain, energy resolution, detection uniformity, efficiency and imaging capability are presented. The key results obtained from the ground calibration have been: - optimization of the instrument tunable parameters, - determination of energy linearity for all detection modes, - determination of energy resolution as a function of energy through the range 20 keV - 3 MeV, - demonstration of imaging capability in each mode, - measurement of intrinsic detector non-uniformity and understanding of the effects of passive materials surrounding the detector plane, and - discovery (and closure) of various leakage paths through the passive shielding system
Limitations and pitfalls of Couinaud's segmentation of the liver in transaxial Imaging

Energy Technology Data Exchange (ETDEWEB)

Strunk, H.; Textor, J.; Willinek, W. [Department of Radiology, University of Bonn, Sigmund Freud-Strasse 25, 53105, Bonn (Germany); Stuckmann, G. [Department of Radiology, Kantonsspital Winterthur (Switzerland)

2003-11-01

The segmental anatomy of the human liver has become a matter of increasing interest to the radiologist, especially in view of the need for an accurate preoperative localization of focal hepatic lesions. In this review article first an overview of the different classical concepts for delineating segmental and subsegmental anatomy on US, transaxial CT, and MR images is given. Essentially, these procedures are based on Couinaud's concept of three vertical planes that divide the liver into four segments and of a transverse scissura that further subdivides the segments into two subsegments each. In a second part, the limitations of these methods are delineated and discussed with the conclusion that if exact preoperative localization of hepatic lesions is needed, tumor must be located relative to the avascular planes between the different portal territories. (orig.)
Overview of Boundary Layer Clouds Using Satellite and Ground-Based Measurements

Science.gov (United States)

Xi, B.; Dong, X.; Wu, P.; Qiu, S.

2017-12-01

A comprehensive summary of boundary layer clouds properties based on our few recently studies will be presented. The analyses include the global cloud fractions and cloud macro/micro- physical properties based on satellite measurements using both CERES-MODIS and CloudSat/Caliposo data products,; the annual/seasonal/diurnal variations of stratocumulus clouds over different climate regions (mid-latitude land, mid-latitude ocean, and Arctic region) using DOE ARM ground-based measurements over Southern great plain (SGP), Azores (GRW), and North slope of Alaska (NSA) sites; the impact of environmental conditions to the formation and dissipation process of marine boundary layer clouds over Azores site; characterizing Arctice mixed-phase cloud structure and favorable environmental conditions for the formation/maintainess of mixed-phase clouds over NSA site. Though the presentation has widely spread topics, we will focus on the representation of the ground-based measurements over different climate regions; evaluation of satellite retrieved cloud properties using these ground-based measurements, and understanding the uncertainties of both satellite and ground-based retrievals and measurements.
Automated 3D closed surface segmentation: application to vertebral body segmentation in CT images.

Science.gov (United States)

Liu, Shuang; Xie, Yiting; Reeves, Anthony P

2016-05-01

A fully automated segmentation algorithm, progressive surface resolution (PSR), is presented in this paper to determine the closed surface of approximately convex blob-like structures that are common in biomedical imaging. The PSR algorithm was applied to the cortical surface segmentation of 460 vertebral bodies on 46 low-dose chest CT images, which can be potentially used for automated bone mineral density measurement and compression fracture detection. The target surface is realized by a closed triangular mesh, which thereby guarantees the enclosure. The surface vertices of the triangular mesh representation are constrained along radial trajectories that are uniformly distributed in 3D angle space. The segmentation is accomplished by determining for each radial trajectory the location of its intersection with the target surface. The surface is first initialized based on an input high confidence boundary image and then resolved progressively based on a dynamic attraction map in an order of decreasing degree of evidence regarding the target surface location. For the visual evaluation, the algorithm achieved acceptable segmentation for 99.35 % vertebral bodies. Quantitative evaluation was performed on 46 vertebral bodies and achieved overall mean Dice coefficient of 0.939 (with max [Formula: see text] 0.957, min [Formula: see text] 0.906 and standard deviation [Formula: see text] 0.011) using manual annotations as the ground truth. Both visual and quantitative evaluations demonstrate encouraging performance of the PSR algorithm. This novel surface resolution strategy provides uniform angular resolution for the segmented surface with computation complexity and runtime that are linearly constrained by the total number of vertices of the triangular mesh representation.
Photoreceptor inner segment ellipsoid band integrity on spectral domain optical coherence tomography

Directory of Open Access Journals (Sweden)

Saxena S

2014-12-01

Full Text Available Sandeep Saxena,1 Khushboo Srivastav,1 Chui M Cheung,2 Joanne YW Ng,3 Timothy YY Lai3 1Retina Service, Department of Ophthalmology, King George’s Medical University Lucknow, India; 2Singapore National Eye Centre, Singapore; 3Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Kowloon, Hong Kong Abstract: Spectral domain optical coherence tomography cross-sectional imaging of the macula has conventionally been resolved into four bands. However, some doubts were raised regarding authentication of the existence of these bands. Recently, a number of studies have suggested that the second band appeared to originate from the inner segment ellipsoids of the foveal cone photoreceptors, and therefore the previously called inner segment-outer segment junction is now referred to as inner segment ellipsoidband. Photoreceptor dysfunction may be a significant predictor of visual acuity in a spectrum of surgical and medical retinal diseases. This review aims to provide an overview and summarizes the role of the photoreceptor inner segment ellipsoid band in the management and prognostication of various vitreoretinal diseases. Keywords: spectral domain optical coherence tomography, inner segment-outer segment junction, external limiting membrane, macular hole, diabetic macular edema, age relate macular degeneration
Optimization-Based Image Segmentation by Genetic Algorithms

Directory of Open Access Journals (Sweden)

Rosenberger C

2008-01-01

Full Text Available Abstract Many works in the literature focus on the definition of evaluation metrics and criteria that enable to quantify the performance of an image processing algorithm. These evaluation criteria can be used to define new image processing algorithms by optimizing them. In this paper, we propose a general scheme to segment images by a genetic algorithm. The developed method uses an evaluation criterion which quantifies the quality of an image segmentation result. The proposed segmentation method can integrate a local ground truth when it is available in order to set the desired level of precision of the final result. A genetic algorithm is then used in order to determine the best combination of information extracted by the selected criterion. Then, we show that this approach can either be applied for gray-levels or multicomponents images in a supervised context or in an unsupervised one. Last, we show the efficiency of the proposed method through some experimental results on several gray-levels and multicomponents images.
Optimization-Based Image Segmentation by Genetic Algorithms

Directory of Open Access Journals (Sweden)

H. Laurent

2008-05-01

Full Text Available Many works in the literature focus on the definition of evaluation metrics and criteria that enable to quantify the performance of an image processing algorithm. These evaluation criteria can be used to define new image processing algorithms by optimizing them. In this paper, we propose a general scheme to segment images by a genetic algorithm. The developed method uses an evaluation criterion which quantifies the quality of an image segmentation result. The proposed segmentation method can integrate a local ground truth when it is available in order to set the desired level of precision of the final result. A genetic algorithm is then used in order to determine the best combination of information extracted by the selected criterion. Then, we show that this approach can either be applied for gray-levels or multicomponents images in a supervised context or in an unsupervised one. Last, we show the efficiency of the proposed method through some experimental results on several gray-levels and multicomponents images.
How consumers pick a hotel strategic segmentation and target marketing

CERN Document Server

Winston, William

2013-01-01

Venture through the pages of How Consumers Pick a Hotel to learn the steps of selecting a target and using consumer behavior applications to segment the market to reach your target. Much as a consumer goes through the process of selecting a satisfying hotel, you can choose to use the information provided to make your hospitality career relaxing and satisfying. When you finish this fantastic reading journey, you'll be prepared to offer services that meet the public's demands, and you'll possess the prerequisite knowledge and skills for developing your own strategic approach to a target market. As the many methods of segmentation are discussed in detail, you will also learn effective strategies for communicating with multiple segments. Ideal as a supplementary text for marketing and hospitality marketing courses, How Consumers Pick a Hotel provides a concise overview of consumer behavior and intertwines marketing theory with sound ways in which to implement the theory. This will both orient you and give you a s...
Dynamic segmentation to estimate vine vigor from ground images

OpenAIRE

Sáiz Rubio, Verónica; Rovira Más, Francisco

2012-01-01

[EN] The geographic information required to implement precision viticulture applications in real fields has led to the extensive use of remote sensing and airborne imagery. While advantageous because they cover large areas and provide diverse radiometric data, they are unreachable to most of medium-size Spanish growers who cannot afford such image sourcing. This research develops a new methodology to generate globally-referenced vigor maps in vineyards from ground images taken wit...
Dynamic segmentation to estimate vine vigor from ground images

OpenAIRE

Sáiz-Rubio, V.; Rovira-Más, F.

2012-01-01

The geographic information required to implement precision viticulture applications in real fields has led to the extensive use of remote sensing and airborne imagery. While advantageous because they cover large areas and provide diverse radiometric data, they are unreachable to most of medium-size Spanish growers who cannot afford such image sourcing. This research develops a new methodology to generate globally-referenced vigor maps in vineyards from ground images taken with a camera mounte...
Renewable Energy Opportunties at Dugway Proving Ground, Utah

Energy Technology Data Exchange (ETDEWEB)

Orrell, Alice C.; Kora, Angela R.; Russo, Bryan J.; Horner, Jacob A.; Williamson, Jennifer L.; Weimar, Mark R.; Gorrissen, Willy J.; Nesse, Ronald J.; Dixon, Douglas R.

2010-05-31

This document provides an overview of renewable resource potential at Dugway Proving Ground, based primarily upon analysis of secondary data sources supplemented with limited on-site evaluations. This effort focuses on grid-connected generation of electricity from renewable energy sources and ground source heat pumps (GSHPs). The effort was funded by the U.S. Army Installation Management Command (IMCOM) as follow-on to the 2005 Department of Defense (DoD) Renewables Assessment.
Rapid Automated Target Segmentation and Tracking on 4D Data without Initial Contours

International Nuclear Information System (INIS)

Chebrolu, V.V.; Chebrolu, V.V.; Saenz, D.; Tewatia, D.; Paliwal, B.R.; Chebrolu, V.V.; Saenz, D.; Paliwal, B.R.; Sethares, W.A.; Cannon, G.

2014-01-01

To achieve rapid automated delineation of gross target volume (GTV) and to quantify changes in volume/position of the target for radiotherapy planning using four-dimensional (4D) CT. Methods and Materials. Novel morphological processing and successive localization (MPSL) algorithms were designed and implemented for achieving auto segmentation. Contours automatically generated using MPSL method were compared with contours generated using state-of-the-art deformable registration methods (using Elastix © and MIMV ista software). Metrics such as the Dice similarity coefficient, sensitivity, and positive predictive value (PPV) were analyzed. The target motion tracked using the centroid of the GTV estimated using MPSL method was compared with motion tracked using deformable registration methods. Results. MPSL algorithm segmented the GTV in 4DCT images in 27.0 ±11.1 seconds per phase ( 512 ×512 resolution) as compared to 142.3±11.3 seconds per phase for deformable registration based methods in 9 cases. Dice coefficients between MPSL generated GTV contours and manual contours (considered as ground-truth) were 0.865 ± 0.037. In comparison, the Dice coefficients between ground-truth and contours generated using deformable registration based methods were 0.909 ± 0.051. Conclusions. The MPSL method achieved similar segmentation accuracy as compared to state-of-the-art deformable registration based segmentation methods, but with significant reduction in time required for GTV segmentation.
Joint Polar Satellite System (JPSS) Common Ground System (CGS) Overview and Architectural Tenets

Science.gov (United States)

Miller, S. W.; Grant, K. D.; Jamilkowski, M. L.

2013-12-01

The National Oceanic and Atmospheric Administration (NOAA) and National Aeronautics and Space Administration (NASA) are jointly acquiring the next-generation civilian weather and environmental satellite system: the Joint Polar Satellite System (JPSS). The Joint Polar Satellite System will replace the afternoon orbit component and ground processing system of the current Polar-orbiting Operational Environmental Satellites (POES) managed by NOAA. The JPSS satellites will carry a suite of sensors designed to collect meteorological, oceanographic, climatological and geophysical observations of the Earth. The ground processing system for JPSS is known as the JPSS Common Ground System (JPSS CGS). Developed and maintained by Raytheon Intelligence and Information Systems (IIS), the CGS is a multi-mission enterprise system serving NOAA, NASA and their national and international partners. The CGS provides a wide range of support to a number of missions: 1) Command and control and mission management for the Suomi National Polar Partnership (S-NPP) mission today, expanding this support to the JPSS-1 satellite and the Polar Free Flyer mission in 2017 2) Data acquisition via a Polar Receptor Network (PRN) for S-NPP, the Japan Aerospace Exploration Agency's (JAXA) Global Change Observation Mission - Water (GCOM-W1), POES, and the Defense Meteorological Satellite Program (DMSP) and Coriolis/WindSat for the Department of Defense (DoD) 3) Data routing over a global fiber Wide Area Network (WAN) for S-NPP, JPSS-1, Polar Free Flyer, GCOM-W1, POES, DMSP, Coriolis/WindSat, the NASA Space Communications and Navigation (SCaN, which includes several Earth Observing System [EOS] missions), MetOp for the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), and the National Science Foundation (NSF) 4) Environmental data processing and distribution for S-NPP, GCOM-W1 and JPSS-1 The CGS architecture will receive a technology refresh in 2015 to satisfy several key

Classification and Weakly Supervised Pain Localization using Multiple Segment Representation.

Science.gov (United States)

Sikka, Karan; Dhall, Abhinav; Bartlett, Marian Stewart

2014-10-01

Automatic pain recognition from videos is a vital clinical application and, owing to its spontaneous nature, poses interesting challenges to automatic facial expression recognition (AFER) research. Previous pain vs no-pain systems have highlighted two major challenges: (1) ground truth is provided for the sequence, but the presence or absence of the target expression for a given frame is unknown, and (2) the time point and the duration of the pain expression event(s) in each video are unknown. To address these issues we propose a novel framework (referred to as MS-MIL) where each sequence is represented as a bag containing multiple segments, and multiple instance learning (MIL) is employed to handle this weakly labeled data in the form of sequence level ground-truth. These segments are generated via multiple clustering of a sequence or running a multi-scale temporal scanning window, and are represented using a state-of-the-art Bag of Words (BoW) representation. This work extends the idea of detecting facial expressions through 'concept frames' to 'concept segments' and argues through extensive experiments that algorithms such as MIL are needed to reap the benefits of such representation. The key advantages of our approach are: (1) joint detection and localization of painful frames using only sequence-level ground-truth, (2) incorporation of temporal dynamics by representing the data not as individual frames but as segments, and (3) extraction of multiple segments, which is well suited to signals with uncertain temporal location and duration in the video. Extensive experiments on UNBC-McMaster Shoulder Pain dataset highlight the effectiveness of the approach by achieving competitive results on both tasks of pain classification and localization in videos. We also empirically evaluate the contributions of different components of MS-MIL. The paper also includes the visualization of discriminative facial patches, important for pain detection, as discovered by our
Superiority Of Graph-Based Visual Saliency GVS Over Other Image Segmentation Methods

Directory of Open Access Journals (Sweden)

Umu Lamboi

2017-02-01

Full Text Available Although inherently tedious the segmentation of images and the evaluation of segmented images are critical in computer vision processes. One of the main challenges in image segmentation evaluation arises from the basic conflict between generality and objectivity. For general segmentation purposes the lack of well-defined ground-truth and segmentation accuracy limits the evaluation of specific applications. Subjectivity is the most common method of evaluation of segmentation quality where segmented images are visually compared. This is daunting task however limits the scope of segmentation evaluation to a few predetermined sets of images. As an alternative supervised evaluation compares segmented images against manually-segmented or pre-processed benchmark images. Not only good evaluation methods allow for different comparisons but also for integration with target recognition systems for adaptive selection of appropriate segmentation granularity with improved recognition accuracy. Most of the current segmentation methods still lack satisfactory measures of effectiveness. Thus this study proposed a supervised framework which uses visual saliency detection to quantitatively evaluate image segmentation quality. The new benchmark evaluator uses Graph-based Visual Saliency GVS to compare boundary outputs for manually segmented images. Using the Berkeley Segmentation Database the proposed algorithm was tested against 4 other quantitative evaluation methods Probabilistic Rand Index PRI Variation of Information VOI Global Consistency Error GSE and Boundary Detection Error BDE. Based on the results the GVS approach outperformed any of the other 4 independent standard methods in terms of visual saliency detection of images.
Model-Based Learning of Local Image Features for Unsupervised Texture Segmentation

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Kiechle, Martin; Storath, Martin; Weinmann, Andreas; Kleinsteuber, Martin

2018-04-01

Features that capture well the textural patterns of a certain class of images are crucial for the performance of texture segmentation methods. The manual selection of features or designing new ones can be a tedious task. Therefore, it is desirable to automatically adapt the features to a certain image or class of images. Typically, this requires a large set of training images with similar textures and ground truth segmentation. In this work, we propose a framework to learn features for texture segmentation when no such training data is available. The cost function for our learning process is constructed to match a commonly used segmentation model, the piecewise constant Mumford-Shah model. This means that the features are learned such that they provide an approximately piecewise constant feature image with a small jump set. Based on this idea, we develop a two-stage algorithm which first learns suitable convolutional features and then performs a segmentation. We note that the features can be learned from a small set of images, from a single image, or even from image patches. The proposed method achieves a competitive rank in the Prague texture segmentation benchmark, and it is effective for segmenting histological images.
Polarization image segmentation of radiofrequency ablated porcine myocardial tissue.

Directory of Open Access Journals (Sweden)

Iftikhar Ahmad

Full Text Available Optical polarimetry has previously imaged the spatial extent of a typical radiofrequency ablated (RFA lesion in myocardial tissue, exhibiting significantly lower total depolarization at the necrotic core compared to healthy tissue, and intermediate values at the RFA rim region. Here, total depolarization in ablated myocardium was used to segment the total depolarization image into three (core, rim and healthy zones. A local fuzzy thresholding algorithm was used for this multi-region segmentation, and then compared with a ground truth segmentation obtained from manual demarcation of RFA core and rim regions on the histopathology image. Quantitative comparison of the algorithm segmentation results was performed with evaluation metrics such as dice similarity coefficient (DSC = 0.78 ± 0.02 and 0.80 ± 0.02, sensitivity (Sn = 0.83 ± 0.10 and 0.91 ± 0.08, specificity (Sp = 0.76 ± 0.17 and 0.72 ± 0.17 and accuracy (Acc = 0.81 ± 0.09 and 0.71 ± 0.10 for RFA core and rim regions, respectively. This automatic segmentation of parametric depolarization images suggests a novel application of optical polarimetry, namely its use in objective RFA image quantification.
A Proven Methodology for Developing Secure Software and Applying It to Ground Systems

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Bailey, Brandon

2016-01-01

Part Two expands upon Part One in an attempt to translate the methodology for ground system personnel. The goal is to build upon the methodology presented in Part One by showing examples and details on how to implement the methodology. Section 1: Ground Systems Overview; Section 2: Secure Software Development; Section 3: Defense in Depth for Ground Systems; Section 4: What Now?
Robust Object Segmentation Using a Multi-Layer Laser Scanner

Science.gov (United States)

Kim, Beomseong; Choi, Baehoon; Yoo, Minkyun; Kim, Hyunju; Kim, Euntai

2014-01-01

The major problem in an advanced driver assistance system (ADAS) is the proper use of sensor measurements and recognition of the surrounding environment. To this end, there are several types of sensors to consider, one of which is the laser scanner. In this paper, we propose a method to segment the measurement of the surrounding environment as obtained by a multi-layer laser scanner. In the segmentation, a full set of measurements is decomposed into several segments, each representing a single object. Sometimes a ghost is detected due to the ground or fog, and the ghost has to be eliminated to ensure the stability of the system. The proposed method is implemented on a real vehicle, and its performance is tested in a real-world environment. The experiments show that the proposed method demonstrates good performance in many real-life situations. PMID:25356645
Classification and Segmentation of Satellite Orthoimagery Using Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Martin Längkvist

2016-04-01

Full Text Available The availability of high-resolution remote sensing (HRRS data has opened up the possibility for new interesting applications, such as per-pixel classification of individual objects in greater detail. This paper shows how a convolutional neural network (CNN can be applied to multispectral orthoimagery and a digital surface model (DSM of a small city for a full, fast and accurate per-pixel classification. The predicted low-level pixel classes are then used to improve the high-level segmentation. Various design choices of the CNN architecture are evaluated and analyzed. The investigated land area is fully manually labeled into five categories (vegetation, ground, roads, buildings and water, and the classification accuracy is compared to other per-pixel classification works on other land areas that have a similar choice of categories. The results of the full classification and segmentation on selected segments of the map show that CNNs are a viable tool for solving both the segmentation and object recognition task for remote sensing data.
Quantitative Comparison of SPM, FSL, and Brainsuite for Brain MR Image Segmentation

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Kazemi K

2014-03-01

Full Text Available Background: Accurate brain tissue segmentation from magnetic resonance (MR images is an important step in analysis of cerebral images. There are software packages which are used for brain segmentation. These packages usually contain a set of skull stripping, intensity non-uniformity (bias correction and segmentation routines. Thus, assessment of the quality of the segmented gray matter (GM, white matter (WM and cerebrospinal fluid (CSF is needed for the neuroimaging applications. Methods: In this paper, performance evaluation of three widely used brain segmentation software packages SPM8, FSL and Brainsuite is presented. Segmentation with SPM8 has been performed in three frameworks: i default segmentation, ii SPM8 New-segmentation and iii modified version using hidden Markov random field as implemented in SPM8-VBM toolbox. Results: The accuracy of the segmented GM, WM and CSF and the robustness of the tools against changes of image quality has been assessed using Brainweb simulated MR images and IBSR real MR images. The calculated similarity between the segmented tissues using different tools and corresponding ground truth shows variations in segmentation results. Conclusion: A few studies has investigated GM, WM and CSF segmentation. In these studies, the skull stripping and bias correction are performed separately and they just evaluated the segmentation. Thus, in this study, assessment of complete segmentation framework consisting of pre-processing and segmentation of these packages is performed. The obtained results can assist the users in choosing an appropriate segmentation software package for the neuroimaging application of interest.
a Universal De-Noising Algorithm for Ground-Based LIDAR Signal

Science.gov (United States)

Ma, Xin; Xiang, Chengzhi; Gong, Wei

2016-06-01

Ground-based lidar, working as an effective remote sensing tool, plays an irreplaceable role in the study of atmosphere, since it has the ability to provide the atmospheric vertical profile. However, the appearance of noise in a lidar signal is unavoidable, which leads to difficulties and complexities when searching for more information. Every de-noising method has its own characteristic but with a certain limitation, since the lidar signal will vary with the atmosphere changes. In this paper, a universal de-noising algorithm is proposed to enhance the SNR of a ground-based lidar signal, which is based on signal segmentation and reconstruction. The signal segmentation serving as the keystone of the algorithm, segments the lidar signal into three different parts, which are processed by different de-noising method according to their own characteristics. The signal reconstruction is a relatively simple procedure that is to splice the signal sections end to end. Finally, a series of simulation signal tests and real dual field-of-view lidar signal shows the feasibility of the universal de-noising algorithm.
Segmentation: Identification of consumer segments

DEFF Research Database (Denmark)

Høg, Esben

2005-01-01

It is very common to categorise people, especially in the advertising business. Also traditional marketing theory has taken in consumer segments as a favorite topic. Segmentation is closely related to the broader concept of classification. From a historical point of view, classification has its...... origin in other sciences as for example biology, anthropology etc. From an economic point of view, it is called segmentation when specific scientific techniques are used to classify consumers to different characteristic groupings. What is the purpose of segmentation? For example, to be able to obtain...... a basic understanding of grouping people. Advertising agencies may use segmentation totarget advertisements, while food companies may usesegmentation to develop products to various groups of consumers. MAPP has for example investigated the positioning of fish in relation to other food products...
Malignant pleural mesothelioma segmentation for photodynamic therapy planning.

Science.gov (United States)

Brahim, Wael; Mestiri, Makram; Betrouni, Nacim; Hamrouni, Kamel

2018-04-01

Medical imaging modalities such as computed tomography (CT) combined with computer-aided diagnostic processing have already become important part of clinical routine specially for pleural diseases. The segmentation of the thoracic cavity represents an extremely important task in medical imaging for different reasons. Multiple features can be extracted by analyzing the thoracic cavity space and these features are signs of pleural diseases including the malignant pleural mesothelioma (MPM) which is the main focus of our research. This paper presents a method that detects the MPM in the thoracic cavity and plans the photodynamic therapy in the preoperative phase. This is achieved by using a texture analysis of the MPM region combined with a thoracic cavity segmentation method. The algorithm to segment the thoracic cavity consists of multiple stages. First, the rib cage structure is segmented using various image processing techniques. We used the segmented rib cage to detect feature points which represent the thoracic cavity boundaries. Next, the proposed method segments the structures of the inner thoracic cage and fits 2D closed curves to the detected pleural cavity features in each slice. The missing bone structures are interpolated using a prior knowledge from manual segmentation performed by an expert. Next, the tumor region is segmented inside the thoracic cavity using a texture analysis approach. Finally, the contact surface between the tumor region and the thoracic cavity curves is reconstructed in order to plan the photodynamic therapy. Using the adjusted output of the thoracic cavity segmentation method and the MPM segmentation method, we evaluated the contact surface generated from these two steps by comparing it to the ground truth. For this evaluation, we used 10 CT scans with pathologically confirmed MPM at stages 1 and 2. We obtained a high similarity rate between the manually planned surface and our proposed method. The average value of Jaccard index
Quality assurance using outlier detection on an automatic segmentation method for the cerebellar peduncles

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Li, Ke; Ye, Chuyang; Yang, Zhen; Carass, Aaron; Ying, Sarah H.; Prince, Jerry L.

2016-03-01

Cerebellar peduncles (CPs) are white matter tracts connecting the cerebellum to other brain regions. Automatic segmentation methods of the CPs have been proposed for studying their structure and function. Usually the performance of these methods is evaluated by comparing segmentation results with manual delineations (ground truth). However, when a segmentation method is run on new data (for which no ground truth exists) it is highly desirable to efficiently detect and assess algorithm failures so that these cases can be excluded from scientific analysis. In this work, two outlier detection methods aimed to assess the performance of an automatic CP segmentation algorithm are presented. The first one is a univariate non-parametric method using a box-whisker plot. We first categorize automatic segmentation results of a dataset of diffusion tensor imaging (DTI) scans from 48 subjects as either a success or a failure. We then design three groups of features from the image data of nine categorized failures for failure detection. Results show that most of these features can efficiently detect the true failures. The second method—supervised classification—was employed on a larger DTI dataset of 249 manually categorized subjects. Four classifiers—linear discriminant analysis (LDA), logistic regression (LR), support vector machine (SVM), and random forest classification (RFC)—were trained using the designed features and evaluated using a leave-one-out cross validation. Results show that the LR performs worst among the four classifiers and the other three perform comparably, which demonstrates the feasibility of automatically detecting segmentation failures using classification methods.
Sequential segmental classification of feline congenital heart disease.

Science.gov (United States)

Scansen, Brian A; Schneider, Matthias; Bonagura, John D

2015-12-01

Feline congenital heart disease is less commonly encountered in veterinary medicine than acquired feline heart diseases such as cardiomyopathy. Understanding the wide spectrum of congenital cardiovascular disease demands a familiarity with a variety of lesions, occurring both in isolation and in combination, along with an appreciation of complex nomenclature and variable classification schemes. This review begins with an overview of congenital heart disease in the cat, including proposed etiologies and prevalence, examination approaches, and principles of therapy. Specific congenital defects are presented and organized by a sequential segmental classification with respect to their morphologic lesions. Highlights of diagnosis, treatment options, and prognosis are offered. It is hoped that this review will provide a framework for approaching congenital heart disease in the cat, and more broadly in other animal species based on the sequential segmental approach, which represents an adaptation of the common methodology used in children and adults with congenital heart disease. Copyright © 2015 Elsevier B.V. All rights reserved.
Operational Space-Assisted Irrigation Advisory Services: Overview Of And Lessons Learned From The Project DEMETER

Science.gov (United States)

Osann Jochum, M. A.; Demeter Partners

2006-08-01

The project DEMETER (DEMonstration of Earth observation TEchnologies in Routine irrigation advisory services) was dedicated to assessing and demonstrating improvements introduced by Earth observation (EO) and Information and Communication Technologies (ICT) in farm and Irrigation Advisory Service (IAS) day-to-day operations. The DEMETER concept of near-real-time delivery of EO-based irrigation scheduling information to IAS and farmers has proven to be valid. The operationality of the space segment was demonstrated for Landsat 5-TM in the Barrax pilot zone during the 2004 and 2005 irrigation campaigns. Extra-fast image delivery and quality controlled operational processing make the EO-based crop coefficient maps available at the same speed and quality as ground-based data (point samples), while significantly extending the spatial coverage and reducing service cost. Leading-edge online analysis and visualization tools provide easy, intuitive access to the information and personalized service to users. First feedback of users at IAS and farmer level is encouraging. The paper gives an overview of the project and its main achievements.
Precise Alignment and Permanent Mounting of Thin and Lightweight X-ray Segments

Science.gov (United States)

Biskach, Michael P.; Chan, Kai-Wing; Hong, Melinda N.; Mazzarella, James R.; McClelland, Ryan S.; Norman, Michael J.; Saha, Timo T.; Zhang, William W.

2012-01-01

To provide observations to support current research efforts in high energy astrophysics. future X-ray telescope designs must provide matching or better angular resolution while significantly increasing the total collecting area. In such a design the permanent mounting of thin and lightweight segments is critical to the overall performance of the complete X-ray optic assembly. The thin and lightweight segments used in the assemhly of the modules are desigued to maintain and/or exceed the resolution of existing X-ray telescopes while providing a substantial increase in collecting area. Such thin and delicate X-ray segments are easily distorted and yet must be aligned to the arcsecond level and retain accurate alignment for many years. The Next Generation X-ray Optic (NGXO) group at NASA Goddard Space Flight Center has designed, assembled. and implemented new hardware and procedures mth the short term goal of aligning three pairs of X-ray segments in a technology demonstration module while maintaining 10 arcsec alignment through environmental testing as part of the eventual design and construction of a full sized module capable of housing hundreds of X-ray segments. The recent attempts at multiple segment pair alignment and permanent mounting is described along with an overview of the procedure used. A look into what the next year mll bring for the alignment and permanent segment mounting effort illustrates some of the challenges left to overcome before an attempt to populate a full sized module can begin.
Automatic Segmentation of Optic Disc in Eye Fundus Images: A Survey

OpenAIRE

Allam, Ali; Youssif, Aliaa; Ghalwash, Atef

2015-01-01

Optic disc detection and segmentation is one of the key elements for automatic retinal disease screening systems. The aim of this survey paper is to review, categorize and compare the optic disc detection algorithms and methodologies, giving a description of each of them, highlighting their key points and performance measures. Accordingly, this survey firstly overviews the anatomy of the eye fundus showing its main structural components along with their properties and functions. Consequently,...
Retinal Vessels Segmentation Techniques and Algorithms: A Survey

Directory of Open Access Journals (Sweden)

Jasem Almotiri

2018-01-01

Full Text Available Retinal vessels identification and localization aim to separate the different retinal vasculature structure tissues, either wide or narrow ones, from the fundus image background and other retinal anatomical structures such as optic disc, macula, and abnormal lesions. Retinal vessels identification studies are attracting more and more attention in recent years due to non-invasive fundus imaging and the crucial information contained in vasculature structure which is helpful for the detection and diagnosis of a variety of retinal pathologies included but not limited to: Diabetic Retinopathy (DR, glaucoma, hypertension, and Age-related Macular Degeneration (AMD. With the development of almost two decades, the innovative approaches applying computer-aided techniques for segmenting retinal vessels are becoming more and more crucial and coming closer to routine clinical applications. The purpose of this paper is to provide a comprehensive overview for retinal vessels segmentation techniques. Firstly, a brief introduction to retinal fundus photography and imaging modalities of retinal images is given. Then, the preprocessing operations and the state of the art methods of retinal vessels identification are introduced. Moreover, the evaluation and validation of the results of retinal vessels segmentation are discussed. Finally, an objective assessment is presented and future developments and trends are addressed for retinal vessels identification techniques.
Unsupervised motion-based object segmentation refined by color

Science.gov (United States)

Piek, Matthijs C.; Braspenning, Ralph; Varekamp, Chris

2003-06-01

. The presented method has no problems with bifurcations. For the pixel resolution segmentation itself we reclassify pixels such that we optimize an error norm which favour similarly coloured regions and straight edges. SEGMENTATION MEASURE To assist in the evaluation of the proposed algorithm we developed a quality metric. Because the problem does not have an exact specification, we decided to define a ground truth output which we find desirable for a given input. We define the measure for the segmentation quality as being how different the segmentation is from the ground truth. Our measure enables us to evaluate oversegmentation and undersegmentation seperately. Also, it allows us to evaluate which parts of a frame suffer from oversegmentation or undersegmentation. The proposed algorithm has been tested on several typical sequences. CONCLUSIONS In this abstract we presented a new video segmentation method which performs well in the segmentation of multiple independently moving foreground objects from each other and the background. It combines the strong points of both colour and motion segmentation in the way we expected. One of the weak points is that the segmentation method suffers from undersegmentation when adjacent objects display similar motion. In sequences with detailed backgrounds the segmentation will sometimes display noisy edges. Apart from these results, we think that some of the techniques, and in particular the K-regions technique, may be useful for other two-dimensional data segmentation problems.
TED: A Tolerant Edit Distance for segmentation evaluation.

Science.gov (United States)

Funke, Jan; Klein, Jonas; Moreno-Noguer, Francesc; Cardona, Albert; Cook, Matthew

2017-02-15

In this paper, we present a novel error measure to compare a computer-generated segmentation of images or volumes against ground truth. This measure, which we call Tolerant Edit Distance (TED), is motivated by two observations that we usually encounter in biomedical image processing: (1) Some errors, like small boundary shifts, are tolerable in practice. Which errors are tolerable is application dependent and should be explicitly expressible in the measure. (2) Non-tolerable errors have to be corrected manually. The effort needed to do so should be reflected by the error measure. Our measure is the minimal weighted sum of split and merge operations to apply to one segmentation such that it resembles another segmentation within specified tolerance bounds. This is in contrast to other commonly used measures like Rand index or variation of information, which integrate small, but tolerable, differences. Additionally, the TED provides intuitive numbers and allows the localization and classification of errors in images or volumes. We demonstrate the applicability of the TED on 3D segmentations of neurons in electron microscopy images where topological correctness is arguable more important than exact boundary locations. Furthermore, we show that the TED is not just limited to evaluation tasks. We use it as the loss function in a max-margin learning framework to find parameters of an automatic neuron segmentation algorithm. We show that training to minimize the TED, i.e., to minimize crucial errors, leads to higher segmentation accuracy compared to other learning methods. Copyright © 2016. Published by Elsevier Inc.
Rapid Automated Target Segmentation and Tracking on 4D Data without Initial Contours

Directory of Open Access Journals (Sweden)

Venkata V. Chebrolu

2014-01-01

Full Text Available Purpose. To achieve rapid automated delineation of gross target volume (GTV and to quantify changes in volume/position of the target for radiotherapy planning using four-dimensional (4D CT. Methods and Materials. Novel morphological processing and successive localization (MPSL algorithms were designed and implemented for achieving autosegmentation. Contours automatically generated using MPSL method were compared with contours generated using state-of-the-art deformable registration methods (using Elastix© and MIMVista software. Metrics such as the Dice similarity coefficient, sensitivity, and positive predictive value (PPV were analyzed. The target motion tracked using the centroid of the GTV estimated using MPSL method was compared with motion tracked using deformable registration methods. Results. MPSL algorithm segmented the GTV in 4DCT images in 27.0±11.1 seconds per phase (512×512 resolution as compared to 142.3±11.3 seconds per phase for deformable registration based methods in 9 cases. Dice coefficients between MPSL generated GTV contours and manual contours (considered as ground-truth were 0.865±0.037. In comparison, the Dice coefficients between ground-truth and contours generated using deformable registration based methods were 0.909 ± 0.051. Conclusions. The MPSL method achieved similar segmentation accuracy as compared to state-of-the-art deformable registration based segmentation methods, but with significant reduction in time required for GTV segmentation.

Rapid Automated Target Segmentation and Tracking on 4D Data without Initial Contours.

Science.gov (United States)

Chebrolu, Venkata V; Saenz, Daniel; Tewatia, Dinesh; Sethares, William A; Cannon, George; Paliwal, Bhudatt R

2014-01-01

Purpose. To achieve rapid automated delineation of gross target volume (GTV) and to quantify changes in volume/position of the target for radiotherapy planning using four-dimensional (4D) CT. Methods and Materials. Novel morphological processing and successive localization (MPSL) algorithms were designed and implemented for achieving autosegmentation. Contours automatically generated using MPSL method were compared with contours generated using state-of-the-art deformable registration methods (using Elastix© and MIMVista software). Metrics such as the Dice similarity coefficient, sensitivity, and positive predictive value (PPV) were analyzed. The target motion tracked using the centroid of the GTV estimated using MPSL method was compared with motion tracked using deformable registration methods. Results. MPSL algorithm segmented the GTV in 4DCT images in 27.0 ± 11.1 seconds per phase (512 × 512 resolution) as compared to 142.3 ± 11.3 seconds per phase for deformable registration based methods in 9 cases. Dice coefficients between MPSL generated GTV contours and manual contours (considered as ground-truth) were 0.865 ± 0.037. In comparison, the Dice coefficients between ground-truth and contours generated using deformable registration based methods were 0.909 ± 0.051. Conclusions. The MPSL method achieved similar segmentation accuracy as compared to state-of-the-art deformable registration based segmentation methods, but with significant reduction in time required for GTV segmentation.
Impact of consensus contours from multiple PET segmentation methods on the accuracy of functional volume delineation

Energy Technology Data Exchange (ETDEWEB)

Schaefer, A. [Saarland University Medical Centre, Department of Nuclear Medicine, Homburg (Germany); Vermandel, M. [U1189 - ONCO-THAI - Image Assisted Laser Therapy for Oncology, University of Lille, Inserm, CHU Lille, Lille (France); CHU Lille, Nuclear Medicine Department, Lille (France); Baillet, C. [CHU Lille, Nuclear Medicine Department, Lille (France); Dewalle-Vignion, A.S. [U1189 - ONCO-THAI - Image Assisted Laser Therapy for Oncology, University of Lille, Inserm, CHU Lille, Lille (France); Modzelewski, R.; Vera, P.; Gardin, I. [Centre Henri-Becquerel and LITIS EA4108, Rouen (France); Massoptier, L.; Parcq, C.; Gibon, D. [AQUILAB, Research and Innovation Department, Loos Les Lille (France); Fechter, T.; Nestle, U. [University Medical Center Freiburg, Department for Radiation Oncology, Freiburg (Germany); German Cancer Consortium (DKTK) Freiburg and German Cancer Research Center (DKFZ), Heidelberg (Germany); Nemer, U. [University Medical Center Freiburg, Department of Nuclear Medicine, Freiburg (Germany)

2016-05-15

The aim of this study was to evaluate the impact of consensus algorithms on segmentation results when applied to clinical PET images. In particular, whether the use of the majority vote or STAPLE algorithm could improve the accuracy and reproducibility of the segmentation provided by the combination of three semiautomatic segmentation algorithms was investigated. Three published segmentation methods (contrast-oriented, possibility theory and adaptive thresholding) and two consensus algorithms (majority vote and STAPLE) were implemented in a single software platform (Artiview registered). Four clinical datasets including different locations (thorax, breast, abdomen) or pathologies (primary NSCLC tumours, metastasis, lymphoma) were used to evaluate accuracy and reproducibility of the consensus approach in comparison with pathology as the ground truth or CT as a ground truth surrogate. Variability in the performance of the individual segmentation algorithms for lesions of different tumour entities reflected the variability in PET images in terms of resolution, contrast and noise. Independent of location and pathology of the lesion, however, the consensus method resulted in improved accuracy in volume segmentation compared with the worst-performing individual method in the majority of cases and was close to the best-performing method in many cases. In addition, the implementation revealed high reproducibility in the segmentation results with small changes in the respective starting conditions. There were no significant differences in the results with the STAPLE algorithm and the majority vote algorithm. This study showed that combining different PET segmentation methods by the use of a consensus algorithm offers robustness against the variable performance of individual segmentation methods and this approach would therefore be useful in radiation oncology. It might also be relevant for other scenarios such as the merging of expert recommendations in clinical routine and
Segmentation of Thalamus from MR images via Task-Driven Dictionary Learning.

Science.gov (United States)

Liu, Luoluo; Glaister, Jeffrey; Sun, Xiaoxia; Carass, Aaron; Tran, Trac D; Prince, Jerry L

2016-02-27

Automatic thalamus segmentation is useful to track changes in thalamic volume over time. In this work, we introduce a task-driven dictionary learning framework to find the optimal dictionary given a set of eleven features obtained from T1-weighted MRI and diffusion tensor imaging. In this dictionary learning framework, a linear classifier is designed concurrently to classify voxels as belonging to the thalamus or non-thalamus class. Morphological post-processing is applied to produce the final thalamus segmentation. Due to the uneven size of the training data samples for the non-thalamus and thalamus classes, a non-uniform sampling scheme is proposed to train the classifier to better discriminate between the two classes around the boundary of the thalamus. Experiments are conducted on data collected from 22 subjects with manually delineated ground truth. The experimental results are promising in terms of improvements in the Dice coefficient of the thalamus segmentation over state-of-the-art atlas-based thalamus segmentation algorithms.
Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields.

Science.gov (United States)

Robinson, Sean; Guyon, Laurent; Nevalainen, Jaakko; Toriseva, Mervi; Åkerfelt, Malin; Nees, Matthias

2015-01-01

Organotypic, three dimensional (3D) cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs) and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs). The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy.
Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields.

Directory of Open Access Journals (Sweden)

Sean Robinson

Full Text Available Organotypic, three dimensional (3D cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs. The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy.
Using multimodal information for the segmentation of fluorescent micrographs with application to virology and microbiology.

Science.gov (United States)

Held, Christian; Wenzel, Jens; Webel, Rike; Marschall, Manfred; Lang, Roland; Palmisano, Ralf; Wittenberg, Thomas

2011-01-01

In order to improve reproducibility and objectivity of fluorescence microscopy based experiments and to enable the evaluation of large datasets, flexible segmentation methods are required which are able to adapt to different stainings and cell types. This adaption is usually achieved by the manual adjustment of the segmentation methods parameters, which is time consuming and challenging for biologists with no knowledge on image processing. To avoid this, parameters of the presented methods automatically adapt to user generated ground truth to determine the best method and the optimal parameter setup. These settings can then be used for segmentation of the remaining images. As robust segmentation methods form the core of such a system, the currently used watershed transform based segmentation routine is replaced by a fast marching level set based segmentation routine which incorporates knowledge on the cell nuclei. Our evaluations reveal that incorporation of multimodal information improves segmentation quality for the presented fluorescent datasets.
Foreground-background segmentation and attention: a change blindness study.

Science.gov (United States)

Mazza, Veronica; Turatto, Massimo; Umiltà, Carlo

2005-01-01

One of the most debated questions in visual attention research is what factors affect the deployment of attention in the visual scene? Segmentation processes are influential factors, providing candidate objects for further attentional selection, and the relevant literature has concentrated on how figure-ground segmentation mechanisms influence visual attention. However, another crucial process, namely foreground-background segmentation, seems to have been neglected. By using a change blindness paradigm, we explored whether attention is preferentially allocated to the foreground elements or to the background ones. The results indicated that unless attention was voluntarily deployed to the background, large changes in the color of its elements remained unnoticed. In contrast, minor changes in the foreground elements were promptly reported. Differences in change blindness between the two regions of the display indicate that attention is, by default, biased toward the foreground elements. This also supports the phenomenal observations made by Gestaltists, who demonstrated the greater salience of the foreground than the background.
Polyfluorinated chemicals in European surface waters, ground- and drinking waters

NARCIS (Netherlands)

Eschauzier, C.; de Voogt, P.; Brauch, H.-J.; Lange, F.T.; Knepper, T.P.; Lange, F.T.

2012-01-01

Polyfluorinated chemicals (PFCs), especially short chain fluorinated alkyl sulfonates and carboxylates, are ubiquitously found in the environment. This chapter aims at giving an overview of PFC concentrations found in European surface, ground- and drinking waters and their behavior during
Nearest neighbor 3D segmentation with context features

Science.gov (United States)

Hristova, Evelin; Schulz, Heinrich; Brosch, Tom; Heinrich, Mattias P.; Nickisch, Hannes

2018-03-01

Automated and fast multi-label segmentation of medical images is challenging and clinically important. This paper builds upon a supervised machine learning framework that uses training data sets with dense organ annotations and vantage point trees to classify voxels in unseen images based on similarity of binary feature vectors extracted from the data. Without explicit model knowledge, the algorithm is applicable to different modalities and organs, and achieves high accuracy. The method is successfully tested on 70 abdominal CT and 42 pelvic MR images. With respect to ground truth, an average Dice overlap score of 0.76 for the CT segmentation of liver, spleen and kidneys is achieved. The mean score for the MR delineation of bladder, bones, prostate and rectum is 0.65. Additionally, we benchmark several variations of the main components of the method and reduce the computation time by up to 47% without significant loss of accuracy. The segmentation results are - for a nearest neighbor method - surprisingly accurate, robust as well as data and time efficient.
Overview of risk analysis research on tanker groundings and collisions

DEFF Research Database (Denmark)

Pedersen, Preben Terndrup

1999-01-01

for evaluation of the oil outlfow performance of alternative tanker designs in the event of a collision or grounding. The present paper is an invited contribution oto the first meeting of the Committee on Evaluating Double Hull Alterntive Tanker Designs held at the National Academy of Sciences' Georgetown...
Status of the segment interconnect, cable segment ancillary logic, and the cable segment hybrid driver projects

International Nuclear Information System (INIS)

Swoboda, C.; Barsotti, E.; Chappa, S.; Downing, R.; Goeransson, G.; Lensy, D.; Moore, G.; Rotolo, C.; Urish, J.

1985-01-01

The FASTBUS Segment Interconnect (SI) provides a communication path between two otherwise independent, asynchronous bus segments. In particular, the Segment Interconnect links a backplane crate segment to a cable segment. All standard FASTBUS address and data transactions can be passed through the SI or any number of SIs and segments in a path. Thus systems of arbitrary connection complexity can be formed, allowing simultaneous independent processing, yet still permitting devices associated with one segment to be accessed from others. The model S1 Segment Interconnect and the Cable Segment Ancillary Logic covered in this report comply with all the mandatory features stated in the FASTBUS specification document DOE/ER-0189. A block diagram of the SI is shown
Benchmark for license plate character segmentation

Science.gov (United States)

Gonçalves, Gabriel Resende; da Silva, Sirlene Pio Gomes; Menotti, David; Shwartz, William Robson

2016-09-01

Automatic license plate recognition (ALPR) has been the focus of many researches in the past years. In general, ALPR is divided into the following problems: detection of on-track vehicles, license plate detection, segmentation of license plate characters, and optical character recognition (OCR). Even though commercial solutions are available for controlled acquisition conditions, e.g., the entrance of a parking lot, ALPR is still an open problem when dealing with data acquired from uncontrolled environments, such as roads and highways when relying only on imaging sensors. Due to the multiple orientations and scales of the license plates captured by the camera, a very challenging task of the ALPR is the license plate character segmentation (LPCS) step, because its effectiveness is required to be (near) optimal to achieve a high recognition rate by the OCR. To tackle the LPCS problem, this work proposes a benchmark composed of a dataset designed to focus specifically on the character segmentation step of the ALPR within an evaluation protocol. Furthermore, we propose the Jaccard-centroid coefficient, an evaluation measure more suitable than the Jaccard coefficient regarding the location of the bounding box within the ground-truth annotation. The dataset is composed of 2000 Brazilian license plates consisting of 14000 alphanumeric symbols and their corresponding bounding box annotations. We also present a straightforward approach to perform LPCS efficiently. Finally, we provide an experimental evaluation for the dataset based on five LPCS approaches and demonstrate the importance of character segmentation for achieving an accurate OCR.
Spot detection and image segmentation in DNA microarray data.

Science.gov (United States)

Qin, Li; Rueda, Luis; Ali, Adnan; Ngom, Alioune

2005-01-01

Following the invention of microarrays in 1994, the development and applications of this technology have grown exponentially. The numerous applications of microarray technology include clinical diagnosis and treatment, drug design and discovery, tumour detection, and environmental health research. One of the key issues in the experimental approaches utilising microarrays is to extract quantitative information from the spots, which represent genes in a given experiment. For this process, the initial stages are important and they influence future steps in the analysis. Identifying the spots and separating the background from the foreground is a fundamental problem in DNA microarray data analysis. In this review, we present an overview of state-of-the-art methods for microarray image segmentation. We discuss the foundations of the circle-shaped approach, adaptive shape segmentation, histogram-based methods and the recently introduced clustering-based techniques. We analytically show that clustering-based techniques are equivalent to the one-dimensional, standard k-means clustering algorithm that utilises the Euclidean distance.
Application of In-Segment Multiple Sampling in Object-Based Classification

Directory of Open Access Journals (Sweden)

Nataša Đurić

2014-12-01

Full Text Available When object-based analysis is applied to very high-resolution imagery, pixels within the segments reveal large spectral inhomogeneity; their distribution can be considered complex rather than normal. When normality is violated, the classification methods that rely on the assumption of normally distributed data are not as successful or accurate. It is hard to detect normality violations in small samples. The segmentation process produces segments that vary highly in size; samples can be very big or very small. This paper investigates whether the complexity within the segment can be addressed using multiple random sampling of segment pixels and multiple calculations of similarity measures. In order to analyze the effect sampling has on classification results, statistics and probability value equations of non-parametric two-sample Kolmogorov-Smirnov test and parametric Student’s t-test are selected as similarity measures in the classification process. The performance of both classifiers was assessed on a WorldView-2 image for four land cover classes (roads, buildings, grass and trees and compared to two commonly used object-based classifiers—k-Nearest Neighbor (k-NN and Support Vector Machine (SVM. Both proposed classifiers showed a slight improvement in the overall classification accuracies and produced more accurate classification maps when compared to the ground truth image.
Managing Media: Segmenting Media Through Consumer Expectancies

Directory of Open Access Journals (Sweden)

Matt Eastin

2014-04-01

Full Text Available It has long been understood that consumers are motivated to media differently. However, given the lack of comparative model analysis, this assumption is without empirical validation, and thus, the orientation of segmentation from a media management perspective is without motivational grounds. Thus, evolving the literature on media consumption, the current study develops and compares models of media segmentation within the context of use. From this study, six models of media expectancies were constructed so that motivational differences between media (i.e., local and national newspapers, network and cable television, radio, and Internet could be observed. Utilizing higher order statistical analyses the data indicates differences across a model comparison approach for media motivations. Furthermore, these differences vary across numerous demographic factors. Results afford theoretical advancement within the literature of consumer media consumption as well as provide media planners’ insight into consumer choices.
Segmentation of radiographic images under topological constraints: application to the femur.

Science.gov (United States)

Gamage, Pavan; Xie, Sheng Quan; Delmas, Patrice; Xu, Wei Liang

2010-09-01

A framework for radiographic image segmentation under topological control based on two-dimensional (2D) image analysis was developed. The system is intended for use in common radiological tasks including fracture treatment analysis, osteoarthritis diagnostics and osteotomy management planning. The segmentation framework utilizes a generic three-dimensional (3D) model of the bone of interest to define the anatomical topology. Non-rigid registration is performed between the projected contours of the generic 3D model and extracted edges of the X-ray image to achieve the segmentation. For fractured bones, the segmentation requires an additional step where a region-based active contours curve evolution is performed with a level set Mumford-Shah method to obtain the fracture surface edge. The application of the segmentation framework to analysis of human femur radiographs was evaluated. The proposed system has two major innovations. First, definition of the topological constraints does not require a statistical learning process, so the method is generally applicable to a variety of bony anatomy segmentation problems. Second, the methodology is able to handle both intact and fractured bone segmentation. Testing on clinical X-ray images yielded an average root mean squared distance (between the automatically segmented femur contour and the manual segmented ground truth) of 1.10 mm with a standard deviation of 0.13 mm. The proposed point correspondence estimation algorithm was benchmarked against three state-of-the-art point matching algorithms, demonstrating successful non-rigid registration for the cases of interest. A topologically constrained automatic bone contour segmentation framework was developed and tested, providing robustness to noise, outliers, deformations and occlusions.
Segmentation of radiographic images under topological constraints: application to the femur

International Nuclear Information System (INIS)

Gamage, Pavan; Xie, Sheng Quan; Delmas, Patrice; Xu, Wei Liang

2010-01-01

A framework for radiographic image segmentation under topological control based on two-dimensional (2D) image analysis was developed. The system is intended for use in common radiological tasks including fracture treatment analysis, osteoarthritis diagnostics and osteotomy management planning. The segmentation framework utilizes a generic three-dimensional (3D) model of the bone of interest to define the anatomical topology. Non-rigid registration is performed between the projected contours of the generic 3D model and extracted edges of the X-ray image to achieve the segmentation. For fractured bones, the segmentation requires an additional step where a region-based active contours curve evolution is performed with a level set Mumford-Shah method to obtain the fracture surface edge. The application of the segmentation framework to analysis of human femur radiographs was evaluated. The proposed system has two major innovations. First, definition of the topological constraints does not require a statistical learning process, so the method is generally applicable to a variety of bony anatomy segmentation problems. Second, the methodology is able to handle both intact and fractured bone segmentation. Testing on clinical X-ray images yielded an average root mean squared distance (between the automatically segmented femur contour and the manual segmented ground truth) of 1.10 mm with a standard deviation of 0.13 mm. The proposed point correspondence estimation algorithm was benchmarked against three state-of-the-art point matching algorithms, demonstrating successful non-rigid registration for the cases of interest. A topologically constrained automatic bone contour segmentation framework was developed and tested, providing robustness to noise, outliers, deformations and occlusions. (orig.)
Segmentation of radiographic images under topological constraints: application to the femur

Energy Technology Data Exchange (ETDEWEB)

Gamage, Pavan; Xie, Sheng Quan [University of Auckland, Department of Mechanical Engineering (Mechatronics), Auckland (New Zealand); Delmas, Patrice [University of Auckland, Department of Computer Science, Auckland (New Zealand); Xu, Wei Liang [Massey University, School of Engineering and Advanced Technology, Auckland (New Zealand)

2010-09-15

A framework for radiographic image segmentation under topological control based on two-dimensional (2D) image analysis was developed. The system is intended for use in common radiological tasks including fracture treatment analysis, osteoarthritis diagnostics and osteotomy management planning. The segmentation framework utilizes a generic three-dimensional (3D) model of the bone of interest to define the anatomical topology. Non-rigid registration is performed between the projected contours of the generic 3D model and extracted edges of the X-ray image to achieve the segmentation. For fractured bones, the segmentation requires an additional step where a region-based active contours curve evolution is performed with a level set Mumford-Shah method to obtain the fracture surface edge. The application of the segmentation framework to analysis of human femur radiographs was evaluated. The proposed system has two major innovations. First, definition of the topological constraints does not require a statistical learning process, so the method is generally applicable to a variety of bony anatomy segmentation problems. Second, the methodology is able to handle both intact and fractured bone segmentation. Testing on clinical X-ray images yielded an average root mean squared distance (between the automatically segmented femur contour and the manual segmented ground truth) of 1.10 mm with a standard deviation of 0.13 mm. The proposed point correspondence estimation algorithm was benchmarked against three state-of-the-art point matching algorithms, demonstrating successful non-rigid registration for the cases of interest. A topologically constrained automatic bone contour segmentation framework was developed and tested, providing robustness to noise, outliers, deformations and occlusions. (orig.)
Automatic lung segmentation using control feedback system: morphology and texture paradigm.

Science.gov (United States)

Noor, Norliza M; Than, Joel C M; Rijal, Omar M; Kassim, Rosminah M; Yunus, Ashari; Zeki, Amir A; Anzidei, Michele; Saba, Luca; Suri, Jasjit S

2015-03-01

Interstitial Lung Disease (ILD) encompasses a wide array of diseases that share some common radiologic characteristics. When diagnosing such diseases, radiologists can be affected by heavy workload and fatigue thus decreasing diagnostic accuracy. Automatic segmentation is the first step in implementing a Computer Aided Diagnosis (CAD) that will help radiologists to improve diagnostic accuracy thereby reducing manual interpretation. Automatic segmentation proposed uses an initial thresholding and morphology based segmentation coupled with feedback that detects large deviations with a corrective segmentation. This feedback is analogous to a control system which allows detection of abnormal or severe lung disease and provides a feedback to an online segmentation improving the overall performance of the system. This feedback system encompasses a texture paradigm. In this study we studied 48 males and 48 female patients consisting of 15 normal and 81 abnormal patients. A senior radiologist chose the five levels needed for ILD diagnosis. The results of segmentation were displayed by showing the comparison of the automated and ground truth boundaries (courtesy of ImgTracer™ 1.0, AtheroPoint™ LLC, Roseville, CA, USA). The left lung's performance of segmentation was 96.52% for Jaccard Index and 98.21% for Dice Similarity, 0.61 mm for Polyline Distance Metric (PDM), -1.15% for Relative Area Error and 4.09% Area Overlap Error. The right lung's performance of segmentation was 97.24% for Jaccard Index, 98.58% for Dice Similarity, 0.61 mm for PDM, -0.03% for Relative Area Error and 3.53% for Area Overlap Error. The segmentation overall has an overall similarity of 98.4%. The segmentation proposed is an accurate and fully automated system.
Intelligent systems for KSC ground processing

Science.gov (United States)

Heard, Astrid E.

1992-01-01

The ground processing and launch of Shuttle vehicles and their payloads is the primary task of Kennedy Space Center. It is a process which is largely manual and contains little inherent automation. Business is conducted today much as it was during previous NASA programs such as Apollo. In light of new programs and decreasing budgets, NASA must find more cost effective ways in which to do business while retaining the quality and safety of activities. Advanced technologies including artificial intelligence could cut manpower and processing time. This paper is an overview of the research and development in Al technology at KSC with descriptions of the systems which have been implemented, as well as a few under development which are promising additions to ground processing software. Projects discussed cover many facets of ground processing activities, including computer sustaining engineering, subsystem monitor and diagnosis tools and launch team assistants. The deployed Al applications have proven an effectiveness which has helped to demonstrate the benefits of utilizing intelligent software in the ground processing task.

3D segmentation of scintigraphic images with validation on realistic GATE simulations

International Nuclear Information System (INIS)

Burg, Samuel

2011-01-01

The objective of this thesis was to propose a new 3D segmentation method for scintigraphic imaging. The first part of the work was to simulate 3D volumes with known ground truth in order to validate a segmentation method over other. Monte-Carlo simulations were performed using the GATE software (Geant4 Application for Emission Tomography). For this, we characterized and modeled the gamma camera 'γ Imager' Biospace"T"M by comparing each measurement from a simulated acquisition to his real equivalent. The 'low level' segmentation tool that we have developed is based on a modeling of the levels of the image by probabilistic mixtures. Parameters estimation is done by an SEM algorithm (Stochastic Expectation Maximization). The 3D volume segmentation is achieved by an ICM algorithm (Iterative Conditional Mode). We compared the segmentation based on Gaussian and Poisson mixtures to segmentation by thresholding on the simulated volumes. This showed the relevance of the segmentations obtained using probabilistic mixtures, especially those obtained with Poisson mixtures. Those one has been used to segment real "1"8FDG PET images of the brain and to compute descriptive statistics of the different tissues. In order to obtain a 'high level' segmentation method and find anatomical structures (necrotic part or active part of a tumor, for example), we proposed a process based on the point processes formalism. A feasibility study has yielded very encouraging results. (author) [fr
Learning-based 3T brain MRI segmentation with guidance from 7T MRI labeling.

Science.gov (United States)

Deng, Minghui; Yu, Renping; Wang, Li; Shi, Feng; Yap, Pew-Thian; Shen, Dinggang

2016-12-01

Segmentation of brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is crucial for brain structural measurement and disease diagnosis. Learning-based segmentation methods depend largely on the availability of good training ground truth. However, the commonly used 3T MR images are of insufficient image quality and often exhibit poor intensity contrast between WM, GM, and CSF. Therefore, they are not ideal for providing good ground truth label data for training learning-based methods. Recent advances in ultrahigh field 7T imaging make it possible to acquire images with excellent intensity contrast and signal-to-noise ratio. In this paper, the authors propose an algorithm based on random forest for segmenting 3T MR images by training a series of classifiers based on reliable labels obtained semiautomatically from 7T MR images. The proposed algorithm iteratively refines the probability maps of WM, GM, and CSF via a cascade of random forest classifiers for improved tissue segmentation. The proposed method was validated on two datasets, i.e., 10 subjects collected at their institution and 797 3T MR images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Specifically, for the mean Dice ratio of all 10 subjects, the proposed method achieved 94.52% ± 0.9%, 89.49% ± 1.83%, and 79.97% ± 4.32% for WM, GM, and CSF, respectively, which are significantly better than the state-of-the-art methods (p-values brain MR image segmentation. © 2016 American Association of Physicists in Medicine.
Review of commonly used remote sensing and ground-based ...

African Journals Online (AJOL)

This review provides an overview of the use of remote sensing data, the development of spectral reflectance indices for detecting plant water stress, and the usefulness of field measurements for ground-truthing purposes. Reliable measurements of plant water stress over large areas are often required for management ...
Segmented block copolymers with monodisperse aramide end-segments

NARCIS (Netherlands)

Araichimani, A.; Gaymans, R.J.

2008-01-01

Segmented block copolymers were synthesized using monodisperse diaramide (TT) as hard segments and PTMO with a molecular weight of 2 900 g · mol-1 as soft segments. The aramide: PTMO segment ratio was increased from 1:1 to 2:1 thereby changing the structure from a high molecular weight multi-block
The Influence of F0 Discontinuity on Intonational Cues to Word Segmentation

DEFF Research Database (Denmark)

Welby, Pauline; Niebuhr, Oliver

2016-01-01

The paper presents the results of a 2AFC offline wordidentification experiment by [1], reanalyzed to investigate how F0 discontinuities due to voiceless fricatives and voiceless stops affect cues to word segmentation in accentual phraseinitial rises (APRs) of French relative to a reference...... condition with liquid and nasal consonants. Although preliminary due to the small sample size, we found initial evidence that voiceless consonants degrade F0 cues to word segmentation relative to liquids and nasals. In addition, this degradation seems to be stronger for voiceless stops than for voiceless...... pitch impressions created by the fricative noise. Our results call for follow-up studies that use French APRs as a testing ground for this intonational model and also examine the precise nature of intonational cues to word segmentation....
Segmentation of consumer's markets and evaluation of market's segments

OpenAIRE

ŠVECOVÁ, Iveta

2013-01-01

The goal of this bachelor thesis was to explain a possibly segmentation of consumer´s markets for a chosen company, and to present a suitable goods offer, so it would be suitable to the needs of selected segments. The work is divided into theoretical and practical part. First part describes marketing, segmentation, segmentation of consumer's markets, consumer's market, market's segments a other terms. Second part describes an evaluation of questionnaire survey, discovering of market's segment...
Structural Analysis of Grounding Damages on MS DEXTRA

DEFF Research Database (Denmark)

Pedersen, Preben Terndrup; Simonsen, Bo Cerup; Zhang, Shengming

Sub-task 1.2 of DEXTREMEL deals with development of models for external ship collision and grounding dynamics and for internal ship structure dynamics. In order to get a better overview of the work performed in this task it has been decided to write two reports on the work. One dealing...... with internal and external collision dynamics and the present report which deals with structural analysis of grounding events.The first part of the present report is devoted to an energy balance for raking damage situations.Then follows a numerical study of the forces associated with cutting and crushing...
Analysis Methodology for Optimal Selection of Ground Station Site in Space Missions

Science.gov (United States)

Nieves-Chinchilla, J.; Farjas, M.; Martínez, R.

2013-12-01

Optimization of ground station sites is especially important in complex missions that include several small satellites (clusters or constellations) such as the QB50 project, where one ground station would be able to track several spatial vehicles, even simultaneously. In this regard the design of the communication system has to carefully take into account the ground station site and relevant signal phenomena, depending on the frequency band. To propose the optimal location of the ground station, these aspects become even more relevant to establish a trusted communication link due to the ground segment site in urban areas and/or selection of low orbits for the space segment. In addition, updated cartography with high resolution data of the location and its surroundings help to develop recommendations in the design of its location for spatial vehicles tracking and hence to improve effectiveness. The objectives of this analysis methodology are: completion of cartographic information, modelling the obstacles that hinder communication between the ground and space segment and representation in the generated 3D scene of the degree of impairment in the signal/noise of the phenomena that interferes with communication. The integration of new technologies of geographic data capture, such as 3D Laser Scan, determine that increased optimization of the antenna elevation mask, in its AOS and LOS azimuths along the horizon visible, maximizes visibility time with spatial vehicles. Furthermore, from the three-dimensional cloud of points captured, specific information is selected and, using 3D modeling techniques, the 3D scene of the antenna location site and surroundings is generated. The resulting 3D model evidences nearby obstacles related to the cartographic conditions such as mountain formations and buildings, and any additional obstacles that interfere with the operational quality of the antenna (other antennas and electronic devices that emit or receive in the same bandwidth
Segmenting high-frequency intracardiac ultrasound images of myocardium into infarcted, ischemic, and normal regions.

Science.gov (United States)

Hao, X; Bruce, C J; Pislaru, C; Greenleaf, J F

2001-12-01

Segmenting abnormal from normal myocardium using high-frequency intracardiac echocardiography (ICE) images presents new challenges for image processing. Gray-level intensity and texture features of ICE images of myocardium with the same structural/perfusion properties differ. This significant limitation conflicts with the fundamental assumption on which existing segmentation techniques are based. This paper describes a new seeded region growing method to overcome the limitations of the existing segmentation techniques. Three criteria are used for region growing control: 1) Each pixel is merged into the globally closest region in the multifeature space. 2) "Geographic similarity" is introduced to overcome the problem that myocardial tissue, despite having the same property (i.e., perfusion status), may be segmented into several different regions using existing segmentation methods. 3) "Equal opportunity competence" criterion is employed making results independent of processing order. This novel segmentation method is applied to in vivo intracardiac ultrasound images using pathology as the reference method for the ground truth. The corresponding results demonstrate that this method is reliable and effective.
MODFLOW-2000, The U.S. Geological Survey Modular Ground-Water Model - User Guide to Modularization Concepts and the Ground-Water Flow Process

Science.gov (United States)

Harbaugh, Arlen W.; Banta, Edward R.; Hill, Mary C.; McDonald, Michael G.

2000-01-01

MODFLOW is a computer program that numerically solves the three-dimensional ground-water flow equation for a porous medium by using a finite-difference method. Although MODFLOW was designed to be easily enhanced, the design was oriented toward additions to the ground-water flow equation. Frequently there is a need to solve additional equations; for example, transport equations and equations for estimating parameter values that produce the closest match between model-calculated heads and flows and measured values. This report documents a new version of MODFLOW, called MODFLOW-2000, which is designed to accommodate the solution of equations in addition to the ground-water flow equation. This report is a user's manual. It contains an overview of the old and added design concepts, documents one new package, and contains input instructions for using the model to solve the ground-water flow equation.
Engineering uses of physics-based ground motion simulations

Science.gov (United States)

Baker, Jack W.; Luco, Nicolas; Abrahamson, Norman A.; Graves, Robert W.; Maechling, Phillip J.; Olsen, Kim B.

2014-01-01

This paper summarizes validation methodologies focused on enabling ground motion simulations to be used with confidence in engineering applications such as seismic hazard analysis and dynmaic analysis of structural and geotechnical systems. Numberical simullation of ground motion from large erthquakes, utilizing physics-based models of earthquake rupture and wave propagation, is an area of active research in the earth science community. Refinement and validatoin of these models require collaboration between earthquake scientists and engineering users, and testing/rating methodolgies for simulated ground motions to be used with confidence in engineering applications. This paper provides an introduction to this field and an overview of current research activities being coordinated by the Souther California Earthquake Center (SCEC). These activities are related both to advancing the science and computational infrastructure needed to produce ground motion simulations, as well as to engineering validation procedures. Current research areas and anticipated future achievements are also discussed.
Five-Segment Solid Rocket Motor Development Status

Science.gov (United States)

Priskos, Alex S.

2012-01-01

In support of the National Aeronautics and Space Administration (NASA), Marshall Space Flight Center (MSFC) is developing a new, more powerful solid rocket motor for space launch applications. To minimize technical risks and development costs, NASA chose to use the Space Shuttle s solid rocket boosters as a starting point in the design and development. The new, five segment motor provides a greater total impulse with improved, more environmentally friendly materials. To meet the mass and trajectory requirements, the motor incorporates substantial design and system upgrades, including new propellant grain geometry with an additional segment, new internal insulation system, and a state-of-the art avionics system. Significant progress has been made in the design, development and testing of the propulsion, and avionics systems. To date, three development motors (one each in 2009, 2010, and 2011) have been successfully static tested by NASA and ATK s Launch Systems Group in Promontory, UT. These development motor tests have validated much of the engineering with substantial data collected, analyzed, and utilized to improve the design. This paper provides an overview of the development progress on the first stage propulsion system.
No increase in fluctuating asymmetry in ground beetles (Carabidae) as urbanisation progresses

DEFF Research Database (Denmark)

Elek, Zoltán; Lövei, Gabor L; Batki, Marton

2014-01-01

fluctuating asymmetry in three common predatory ground beetles, Carabus nemoralis, Nebria brevicollis and Pterostichus melanarius. Eight metrical (length of the second and third antennal segments, elytral length, length of the first tarsus segment, length of the first and second tibiae, length of the proximal......Environmental stress can lead to a reduction in developmental homeostasis, which could be reflected in increased variability of morphological traits. Fluctuating asymmetry (FA) is one possible manifestation of such a stress, and is often taken as a proxy for individual fitness. To test...... the usefulness of FA in morphological traits as an indicator of environmental quality, we studied the effect of urbanisation on FA in ground beetles (Carabidae) near a Danish city. First, we performed a critical examina- tion whether morphological character traits suggested in the literature displayed true...
A Hybrid Hierarchical Approach for Brain Tissue Segmentation by Combining Brain Atlas and Least Square Support Vector Machine

Science.gov (United States)

Kasiri, Keyvan; Kazemi, Kamran; Dehghani, Mohammad Javad; Helfroush, Mohammad Sadegh

2013-01-01

In this paper, we present a new semi-automatic brain tissue segmentation method based on a hybrid hierarchical approach that combines a brain atlas as a priori information and a least-square support vector machine (LS-SVM). The method consists of three steps. In the first two steps, the skull is removed and the cerebrospinal fluid (CSF) is extracted. These two steps are performed using the toolbox FMRIB's automated segmentation tool integrated in the FSL software (FSL-FAST) developed in Oxford Centre for functional MRI of the brain (FMRIB). Then, in the third step, the LS-SVM is used to segment grey matter (GM) and white matter (WM). The training samples for LS-SVM are selected from the registered brain atlas. The voxel intensities and spatial positions are selected as the two feature groups for training and test. SVM as a powerful discriminator is able to handle nonlinear classification problems; however, it cannot provide posterior probability. Thus, we use a sigmoid function to map the SVM output into probabilities. The proposed method is used to segment CSF, GM and WM from the simulated magnetic resonance imaging (MRI) using Brainweb MRI simulator and real data provided by Internet Brain Segmentation Repository. The semi-automatically segmented brain tissues were evaluated by comparing to the corresponding ground truth. The Dice and Jaccard similarity coefficients, sensitivity and specificity were calculated for the quantitative validation of the results. The quantitative results show that the proposed method segments brain tissues accurately with respect to corresponding ground truth. PMID:24696800
The Segmentation of Point Clouds with K-Means and ANN (artifical Neural Network)

Science.gov (United States)

Kuçak, R. A.; Özdemir, E.; Erol, S.

2017-05-01

Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM) generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM) which is a type of ANN (Artificial Neural Network) segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS) were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging) and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.
THE SEGMENTATION OF POINT CLOUDS WITH K-MEANS AND ANN (ARTIFICAL NEURAL NETWORK

Directory of Open Access Journals (Sweden)

R. A. Kuçak

2017-05-01

Full Text Available Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM which is a type of ANN (Artificial Neural Network segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.
Single-event effect ground test issues

International Nuclear Information System (INIS)

Koga, R.

1996-01-01

Ground-based single event effect (SEE) testing of microcircuits permits characterization of device susceptibility to various radiation induced disturbances, including: (1) single event upset (SEU) and single event latchup (SEL) in digital microcircuits; (2) single event gate rupture (SEGR), and single event burnout (SEB) in power transistors; and (3) bit errors in photonic devices. These characterizations can then be used to generate predictions of device performance in the space radiation environment. This paper provides a general overview of ground-based SEE testing and examines in critical depth several underlying conceptual constructs relevant to the conduct of such tests and to the proper interpretation of results. These more traditional issues are contrasted with emerging concerns related to the testing of modern, advanced microcircuits
The role of the background: texture segregation and figure-ground segmentation.

Science.gov (United States)

Caputo, G

1996-09-01

The effects of a texture surround composed of line elements on a stimulus within which a target line element segregates, were studied. Detection and discrimination of the target when it had the same orientation as the surround were impaired at short presentation time; on the other hand, no effect was present when they were reciprocally orthogonal. These results are interpreted as background completion in texture segregation; a texture made up of similar elements is represented as a continuous surface with contour and contrast of an embedded element inhibited. This interpretation is further confirmed with a simple line protruding from an annulus. Generally, the results are taken as evidence that local features are prevented from segmenting when they are parts of a global entity.
Project overview and update on WEAVE: the next generation wide-field spectroscopy facility for the William Herschel Telescope

NARCIS (Netherlands)

Dalton, Gavin; Trager, Scott; Abrams, Don Carlos; Bonifacio, Piercarlo; López Aguerri, J. Alfonso; Middleton, Kevin; Benn, Chris; Dee, Kevin; Sayède, Frédéric; Lewis, Ian; Pragt, Johan; Pico, Sergio; Walton, Nic; Rey, Juerg; Allende Prieto, Carlos; Peñate, José; Lhome, Emilie; Agócs, Tibor; Alonso, José; Terrett, David; Brock, Matthew; Gilbert, James; Ridings, Andy; Guinouard, Isabelle; Verheijen, Marc A.W.; Tosh, Ian; Rogers, Kevin; Steele, Iain; Stuik, Remko; Tromp, Neils; Jasko, Attila; Kragt, Jan; Lesman, Dirk; Mottram, Chris; Bates, Stuart; Gribbin, Frank; Rodriguez, Luis Fernando; Delgado, José M.; Martin, Carlos; Cano, Diego; Navarro, Ramón; Irwin, Mike; Lewis, Jim; Gonzalez Solares, Eduardo; O'Mahony, Neil; Bianco, Andrea; Zurita, Christina; ter Horst, Rik; Molinari, Emilio; Lodi, Marcello; Guerra, José; Vallenari, Antonella; Baruffolo, Andrea

We present an overview of and status report on the WEAVE next-generation spectroscopy facility for the William Herschel Telescope (WHT). WEAVE principally targets optical ground-based follow up of upcoming ground-based (LOFAR) and space-based (Gaia) surveys. WEAVE is a multi-object and multi-IFU
A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI.

Science.gov (United States)

Avendi, M R; Kheradvar, Arash; Jafarkhani, Hamid

2016-05-01

Segmentation of the left ventricle (LV) from cardiac magnetic resonance imaging (MRI) datasets is an essential step for calculation of clinical indices such as ventricular volume and ejection fraction. In this work, we employ deep learning algorithms combined with deformable models to develop and evaluate a fully automatic LV segmentation tool from short-axis cardiac MRI datasets. The method employs deep learning algorithms to learn the segmentation task from the ground true data. Convolutional networks are employed to automatically detect the LV chamber in MRI dataset. Stacked autoencoders are used to infer the LV shape. The inferred shape is incorporated into deformable models to improve the accuracy and robustness of the segmentation. We validated our method using 45 cardiac MR datasets from the MICCAI 2009 LV segmentation challenge and showed that it outperforms the state-of-the art methods. Excellent agreement with the ground truth was achieved. Validation metrics, percentage of good contours, Dice metric, average perpendicular distance and conformity, were computed as 96.69%, 0.94, 1.81 mm and 0.86, versus those of 79.2-95.62%, 0.87-0.9, 1.76-2.97 mm and 0.67-0.78, obtained by other methods, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

The NPOESS Preparatory Project Science Data Segment: Brief Overview

Science.gov (United States)

Schweiss, Robert J.; Ho, Evelyn; Ullman, Richard; Samadi, Shahin

2006-01-01

The NPOESS Preparatory Project (NPP) provides remotely-sensed land, ocean, atmospheric, ozone, and sounder data that will serve the meteorological and global climate change scientific communities while also providing risk reduction for the National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government s future low-Earth orbiting satellite system monitoring global weather and environmental conditions. NPOESS and NPP are a new era, not only because the sensors will provide unprecedented quality and volume of data but also because it is a joint mission of three federal agencies, NASA, NOAA, and DoD. NASA's primary science role in NPP is to independently assess the quality of the NPP science and environmental data records. Such assessment is critical for making NPOESS products the best that they can be for operational use and ultimately for climate studies. The Science Data Segment (SDS) supports science assessment by assuring the timely provision of NPP data to NASA s science teams organized by climate measurement themes. The SDS breaks down into nine major elements, an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. This paper will describe how the NPP SDS will leverage on NASA experience to provide a mission-reliable research capability for science assessment of NPP derived measurements.
Buildings and Terrain of Urban Area Point Cloud Segmentation based on PCL

International Nuclear Information System (INIS)

Liu, Ying; Zhong, Ruofei

2014-01-01

One current problem with laser radar point data classification is building and urban terrain segmentation, this paper proposes a point cloud segmentation method base on PCL libraries. PCL is a large cross-platform open source C++ programming library, which implements a large number of point cloud related efficient data structures and generic algorithms involving point cloud retrieval, filtering, segmentation, registration, feature extraction and curved surface reconstruction, visualization, etc. Due to laser radar point cloud characteristics with large amount of data, unsymmetrical distribution, this paper proposes using the data structure of kd-tree to organize data; then using Voxel Grid filter for point cloud resampling, namely to reduce the amount of point cloud data, and at the same time keep the point cloud shape characteristic; use PCL Segmentation Module, we use a Euclidean Cluster Extraction class with Europe clustering for buildings and ground three-dimensional point cloud segmentation. The experimental results show that this method avoids the multiple copy system existing data needs, saves the program storage space through the call of PCL library method and class, shortens the program compiled time and improves the running speed of the program
An overview of regional and local characteristics of aerosols in South Africa using satellite, ground, and modeling data

Science.gov (United States)

Hersey, S. P.; Garland, R. M.; Crosbie, E.; Shingler, T.; Sorooshian, A.; Piketh, S.; Burger, R.

2014-09-01

We present a comprehensive overview of particulate air quality across the five major metropolitan areas of South Africa (Cape Town, Bloemfontein, Johannesburg and Tshwane (Gauteng Province), the Industrial Highveld Air Quality Priority Area (HVAPA), and Durban), based on a decadal (1 January 2000 to 31 December 2009) aerosol climatology from multiple satellite platforms and a detailed analysis of ground-based data from 19 sites throughout Gauteng. Data include Aerosol Optical Depth (AOD550, 555) from Aqua (550 nm), Terra (550 nm), and MISR (555 nm) platforms, Ängström Exponent (α550/865, 470/660) from Aqua (550/865 nm) and Terra (470/660 nm), Ultraviolet Aerosol Index (UVAI) from TOMS, and model results from the Goddard Ozone Chemistry Aerosol Radiation and Transport (GOCART) model. Results in Cape Town are distinct, owing to a typically clean, marine airmass origin and infrequent continental influence. At continentally-influenced sites, AOD550, AOD555, α550/865, α470/660 and UVAI reach maxima (0.12-0.20, 1.0-1.8, and 1.0-1.2, respectively) during late winter and early spring (August-October), coinciding with a period of enhanced dust generation and the maximum frequency of close-proximity and subtropical fires identified by MODIS Fire Information for Resource Management System (FIRMS). The adjacent metropolitan and industrial Gauteng and HVAPA areas have been identified as a megacity based on NO2 concentrations, but AOD is a factor of 3-6 lower than other megacities worldwide. GOCART results suggest that the contributions of organics and black carbon to AOD are significantly enhanced during biomass burning season (ASO), but that sulfate is the most significant contributor to AOD (~70-80%) through the rest of the year. Dust appears to be underestimated by GOCART emissions inventories at continentally-influenced metropolitan areas of South Africa. Ground monitoring sites were classified according to site type: (1) township and informal settlement sites with
SU-C-207B-05: Tissue Segmentation of Computed Tomography Images Using a Random Forest Algorithm: A Feasibility Study

International Nuclear Information System (INIS)

Polan, D; Brady, S; Kaufman, R

2016-01-01

Purpose: Develop an automated Random Forest algorithm for tissue segmentation of CT examinations. Methods: Seven materials were classified for segmentation: background, lung/internal gas, fat, muscle, solid organ parenchyma, blood/contrast, and bone using Matlab and the Trainable Weka Segmentation (TWS) plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance each evaluated over a pixel radius of 2n, (n = 0–4). Also noise reduction and edge preserving filters, Gaussian, bilateral, Kuwahara, and anisotropic diffusion, were evaluated. The algorithm used 200 trees with 2 features per node. A training data set was established using an anonymized patient’s (male, 20 yr, 72 kg) chest-abdomen-pelvis CT examination. To establish segmentation ground truth, the training data were manually segmented using Eclipse planning software, and an intra-observer reproducibility test was conducted. Six additional patient data sets were segmented based on classifier data generated from the training data. Accuracy of segmentation was determined by calculating the Dice similarity coefficient (DSC) between manual and auto segmented images. Results: The optimized autosegmentation algorithm resulted in 16 features calculated using maximum, mean, variance, and Gaussian blur filters with kernel radii of 1, 2, and 4 pixels, in addition to the original CT number, and Kuwahara filter (linear kernel of 19 pixels). Ground truth had a DSC of 0.94 (range: 0.90–0.99) for adult and 0.92 (range: 0.85–0.99) for pediatric data sets across all seven segmentation classes. The automated algorithm produced segmentation with an average DSC of 0.85 ± 0.04 (range: 0.81–1.00) for the adult patients, and 0.86 ± 0.03 (range: 0.80–0.99) for the pediatric patients. Conclusion: The TWS Random Forest auto-segmentation algorithm was optimized for CT environment, and able to segment seven material classes over a range of body habitus and CT
SU-C-207B-05: Tissue Segmentation of Computed Tomography Images Using a Random Forest Algorithm: A Feasibility Study

Energy Technology Data Exchange (ETDEWEB)

Polan, D [University of Michigan, Ann Arbor, MI (United States); Brady, S; Kaufman, R [St. Jude Children’s Research Hospital, Memphis, TN (United States)

2016-06-15

Purpose: Develop an automated Random Forest algorithm for tissue segmentation of CT examinations. Methods: Seven materials were classified for segmentation: background, lung/internal gas, fat, muscle, solid organ parenchyma, blood/contrast, and bone using Matlab and the Trainable Weka Segmentation (TWS) plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance each evaluated over a pixel radius of 2n, (n = 0–4). Also noise reduction and edge preserving filters, Gaussian, bilateral, Kuwahara, and anisotropic diffusion, were evaluated. The algorithm used 200 trees with 2 features per node. A training data set was established using an anonymized patient’s (male, 20 yr, 72 kg) chest-abdomen-pelvis CT examination. To establish segmentation ground truth, the training data were manually segmented using Eclipse planning software, and an intra-observer reproducibility test was conducted. Six additional patient data sets were segmented based on classifier data generated from the training data. Accuracy of segmentation was determined by calculating the Dice similarity coefficient (DSC) between manual and auto segmented images. Results: The optimized autosegmentation algorithm resulted in 16 features calculated using maximum, mean, variance, and Gaussian blur filters with kernel radii of 1, 2, and 4 pixels, in addition to the original CT number, and Kuwahara filter (linear kernel of 19 pixels). Ground truth had a DSC of 0.94 (range: 0.90–0.99) for adult and 0.92 (range: 0.85–0.99) for pediatric data sets across all seven segmentation classes. The automated algorithm produced segmentation with an average DSC of 0.85 ± 0.04 (range: 0.81–1.00) for the adult patients, and 0.86 ± 0.03 (range: 0.80–0.99) for the pediatric patients. Conclusion: The TWS Random Forest auto-segmentation algorithm was optimized for CT environment, and able to segment seven material classes over a range of body habitus and CT
Semantic Segmentation of Convolutional Neural Network for Supervised Classification of Multispectral Remote Sensing

Science.gov (United States)

Xue, L.; Liu, C.; Wu, Y.; Li, H.

2018-04-01

Semantic segmentation is a fundamental research in remote sensing image processing. Because of the complex maritime environment, the classification of roads, vegetation, buildings and water from remote Sensing Imagery is a challenging task. Although the neural network has achieved excellent performance in semantic segmentation in the last years, there are a few of works using CNN for ground object segmentation and the results could be further improved. This paper used convolution neural network named U-Net, its structure has a contracting path and an expansive path to get high resolution output. In the network , We added BN layers, which is more conducive to the reverse pass. Moreover, after upsampling convolution , we add dropout layers to prevent overfitting. They are promoted to get more precise segmentation results. To verify this network architecture, we used a Kaggle dataset. Experimental results show that U-Net achieved good performance compared with other architectures, especially in high-resolution remote sensing imagery.
Automated segmentation of dental CBCT image with prior-guided sequential random forests

Energy Technology Data Exchange (ETDEWEB)

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-7513 (United States); Chen, Ken-Chung; Tang, Zhen [Surgical Planning Laboratory, Department of Oral and Maxillofacial Surgery, Houston Methodist Research Institute, Houston, Texas 77030 (United States); Xia, James J., E-mail: dgshen@med.unc.edu, E-mail: JXia@HoustonMethodist.org [Surgical Planning Laboratory, Department of Oral and Maxillofacial Surgery, Houston Methodist Research Institute, Houston, Texas 77030 (United States); Department of Surgery (Oral and Maxillofacial Surgery), Weill Medical College, Cornell University, New York, New York 10065 (United States); Department of Oral and Craniomaxillofacial Surgery, Shanghai Jiao Tong University School of Medicine, Shanghai Ninth People’s Hospital, Shanghai 200011 (China); Shen, Dinggang, E-mail: dgshen@med.unc.edu, E-mail: JXia@HoustonMethodist.org [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-7513 and Department of Brain and Cognitive Engineering, Korea University, Seoul 02841 (Korea, Republic of)

2016-01-15

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate 3D models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the image artifacts caused by beam hardening, imaging noise, inhomogeneity, truncation, and maximal intercuspation, it is difficult to segment the CBCT. Methods: In this paper, the authors present a new automatic segmentation method to address these problems. Specifically, the authors first employ a majority voting method to estimate the initial segmentation probability maps of both mandible and maxilla based on multiple aligned expert-segmented CBCT images. These probability maps provide an important prior guidance for CBCT segmentation. The authors then extract both the appearance features from CBCTs and the context features from the initial probability maps to train the first-layer of random forest classifier that can select discriminative features for segmentation. Based on the first-layer of trained classifier, the probability maps are updated, which will be employed to further train the next layer of random forest classifier. By iteratively training the subsequent random forest classifier using both the original CBCT features and the updated segmentation probability maps, a sequence of classifiers can be derived for accurate segmentation of CBCT images. Results: Segmentation results on CBCTs of 30 subjects were both quantitatively and qualitatively validated based on manually labeled ground truth. The average Dice ratios of mandible and maxilla by the authors’ method were 0.94 and 0.91, respectively, which are significantly better than the state-of-the-art method based on sparse representation (p-value < 0.001). Conclusions: The authors have developed and validated a novel fully automated method
Automated segmentation of dental CBCT image with prior-guided sequential random forests

International Nuclear Information System (INIS)

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Chen, Ken-Chung; Tang, Zhen; Xia, James J.; Shen, Dinggang

2016-01-01

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate 3D models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the image artifacts caused by beam hardening, imaging noise, inhomogeneity, truncation, and maximal intercuspation, it is difficult to segment the CBCT. Methods: In this paper, the authors present a new automatic segmentation method to address these problems. Specifically, the authors first employ a majority voting method to estimate the initial segmentation probability maps of both mandible and maxilla based on multiple aligned expert-segmented CBCT images. These probability maps provide an important prior guidance for CBCT segmentation. The authors then extract both the appearance features from CBCTs and the context features from the initial probability maps to train the first-layer of random forest classifier that can select discriminative features for segmentation. Based on the first-layer of trained classifier, the probability maps are updated, which will be employed to further train the next layer of random forest classifier. By iteratively training the subsequent random forest classifier using both the original CBCT features and the updated segmentation probability maps, a sequence of classifiers can be derived for accurate segmentation of CBCT images. Results: Segmentation results on CBCTs of 30 subjects were both quantitatively and qualitatively validated based on manually labeled ground truth. The average Dice ratios of mandible and maxilla by the authors’ method were 0.94 and 0.91, respectively, which are significantly better than the state-of-the-art method based on sparse representation (p-value < 0.001). Conclusions: The authors have developed and validated a novel fully automated method
Research on a Pulmonary Nodule Segmentation Method Combining Fast Self-Adaptive FCM and Classification

Directory of Open Access Journals (Sweden)

Hui Liu

2015-01-01

Full Text Available The key problem of computer-aided diagnosis (CAD of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO pulmonary nodules than other typical algorithms.
Deep learning of the sectional appearances of 3D CT images for anatomical structure segmentation based on an FCN voting method.

Science.gov (United States)

Zhou, Xiangrong; Takayama, Ryosuke; Wang, Song; Hara, Takeshi; Fujita, Hiroshi

2017-10-01

We propose a single network trained by pixel-to-label deep learning to address the general issue of automatic multiple organ segmentation in three-dimensional (3D) computed tomography (CT) images. Our method can be described as a voxel-wise multiple-class classification scheme for automatically assigning labels to each pixel/voxel in a 2D/3D CT image. We simplify the segmentation algorithms of anatomical structures (including multiple organs) in a CT image (generally in 3D) to a majority voting scheme over the semantic segmentation of multiple 2D slices drawn from different viewpoints with redundancy. The proposed method inherits the spirit of fully convolutional networks (FCNs) that consist of "convolution" and "deconvolution" layers for 2D semantic image segmentation, and expands the core structure with 3D-2D-3D transformations to adapt to 3D CT image segmentation. All parameters in the proposed network are trained pixel-to-label from a small number of CT cases with human annotations as the ground truth. The proposed network naturally fulfills the requirements of multiple organ segmentations in CT cases of different sizes that cover arbitrary scan regions without any adjustment. The proposed network was trained and validated using the simultaneous segmentation of 19 anatomical structures in the human torso, including 17 major organs and two special regions (lumen and content inside of stomach). Some of these structures have never been reported in previous research on CT segmentation. A database consisting of 240 (95% for training and 5% for testing) 3D CT scans, together with their manually annotated ground-truth segmentations, was used in our experiments. The results show that the 19 structures of interest were segmented with acceptable accuracy (88.1% and 87.9% voxels in the training and testing datasets, respectively, were labeled correctly) against the ground truth. We propose a single network based on pixel-to-label deep learning to address the challenging
Coronary arteries segmentation based on the 3D discrete wavelet transform and 3D neutrosophic transform.

Science.gov (United States)

Chen, Shuo-Tsung; Wang, Tzung-Dau; Lee, Wen-Jeng; Huang, Tsai-Wei; Hung, Pei-Kai; Wei, Cheng-Yu; Chen, Chung-Ming; Kung, Woon-Man

2015-01-01

Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband coefficients of the 3D DWT, was detected by the proposed vessel-texture discrimination algorithm. Based on the initial segmentation, 3D DWT integrated with the 3D neutrosophic transformation could accurately detect the coronary arteries. Each subbranch of the segmented coronary arteries was segmented correctly by the proposed method. The obtained results are compared with those ground truth values obtained from the commercial software from GE Healthcare and the level-set method proposed by Yang et al., 2007. Results indicate that the proposed method is better in terms of efficiency analyzed. Based on the initial segmentation of coronary arteries obtained from 3D region growing, one-level 3D DWT and 3D neutrosophic transformation can be applied to detect coronary pathologies accurately.
Ground Water Atlas of the United States: Segment 11, Delaware, Maryland, New Jersey, North Carolina, Pennsylvania, Virginia, West Virginia

Science.gov (United States)

Trapp, Henry; Horn, Marilee A.

1997-01-01

Segment 11 consists of the States of Delaware, Maryland, New Jersey, North Carolina, West Virginia, and the Commonwealths of Pennsylvania and Virginia. All but West Virginia border on the Atlantic Ocean or tidewater. Pennsylvania also borders on Lake Erie. Small parts of northwestern and north-central Pennsylvania drain to Lake Erie and Lake Ontario; the rest of the segment drains either to the Atlantic Ocean or the Gulf of Mexico. Major rivers include the Hudson, the Delaware, the Susquehanna, the Potomac, the Rappahannock, the James, the Chowan, the Neuse, the Tar, the Cape Fear, and the Yadkin-Peedee, all of which drain into the Atlantic Ocean, and the Ohio and its tributaries, which drain to the Gulf of Mexico. Although rivers are important sources of water supply for many cities, such as Trenton, N.J.; Philadelphia and Pittsburgh, Pa.; Baltimore, Md.; Washington, D.C.; Richmond, Va.; and Raleigh, N.C., one-fourth of the population, particularly the people who live on the Coastal Plain, depends on ground water for supply. Such cities as Camden, N.J.; Dover, Del.; Salisbury and Annapolis, Md.; Parkersburg and Weirton, W.Va.; Norfolk, Va.; and New Bern and Kinston, N.C., use ground water as a source of public supply. All the water in Segment 11 originates as precipitation. Average annual precipitation ranges from less than 36 inches in parts of Pennsylvania, Maryland, Virginia, and West Virginia to more than 80 inches in parts of southwestern North Carolina (fig. 1). In general, precipitation is greatest in mountainous areas (because water tends to condense from moisture-laden air masses as the air passes over the higher altitudes) and near the coast, where water vapor that has been evaporated from the ocean is picked up by onshore winds and falls as precipitation when it reaches the shoreline. Some of the precipitation returns to the atmosphere by evapotranspiration (evaporation plus transpiration by plants), but much of it either flows overland into streams as
Integration of sparse multi-modality representation and geometrical constraint for isointense infant brain segmentation.

Science.gov (United States)

Wang, Li; Shi, Feng; Li, Gang; Lin, Weili; Gilmore, John H; Shen, Dinggang

2013-01-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination process. During the first year of life, the signal contrast between white matter (WM) and gray matter (GM) in MR images undergoes inverse changes. In particular, the inversion of WM/GM signal contrast appears around 6-8 months of age, where brain tissues appear isointense and hence exhibit extremely low tissue contrast, posing significant challenges for automated segmentation. In this paper, we propose a novel segmentation method to address the above-mentioned challenge based on the sparse representation of the complementary tissue distribution information from T1, T2 and diffusion-weighted images. Specifically, we first derive an initial segmentation from a library of aligned multi-modality images with ground-truth segmentations by using sparse representation in a patch-based fashion. The segmentation is further refined by the integration of the geometrical constraint information. The proposed method was evaluated on 22 6-month-old training subjects using leave-one-out cross-validation, as well as 10 additional infant testing subjects, showing superior results in comparison to other state-of-the-art methods.
Grounded Object and Grasp Representations in a Cognitive Architecture

DEFF Research Database (Denmark)

Kraft, Dirk

developed. This work presents a system that is able to learn autonomously about objects and applicable grasps in an unknown environment through exploratory manipulation and to then use this grounded knowledge in a planning setup to address complex tasks. A set of different subsystems is needed to achieve....... The topics are ordered so that we proceed from the more general integration works towards the works describing the individual components. The first chapter gives an overview over the system that is able to learn a grounded visual object representation and a grounded grasp representation. In the following...... part, we describe how this grounding procedures can be embedded in a three cognitive level architecture. Our initial work to use a tactile sensor to enrichen the object representations as well as allow for more complex actions is presented here as well. Since our system is concerned with learning about...
Fluorescence Image Segmentation by using Digitally Reconstructed Fluorescence Images

OpenAIRE

Blumer, Clemens; Vivien, Cyprien; Oertner, Thomas G; Vetter, Thomas

2011-01-01

In biological experiments fluorescence imaging is used to image living and stimulated neurons. But the analysis of fluorescence images is a difficult task. It is not possible to conclude the shape of an object from fluorescence images alone. Therefore, it is not feasible to get good manual segmented nor ground truth data from fluorescence images. Supervised learning approaches are not possible without training data. To overcome this issues we propose to synthesize fluorescence images and call...
Level set segmentation of bovine corpora lutea in ex situ ovarian ultrasound images

Directory of Open Access Journals (Sweden)

Adams Gregg P

2008-08-01

Full Text Available Abstract Background The objective of this study was to investigate the viability of level set image segmentation methods for the detection of corpora lutea (corpus luteum, CL boundaries in ultrasonographic ovarian images. It was hypothesized that bovine CL boundaries could be located within 1–2 mm by a level set image segmentation methodology. Methods Level set methods embed a 2D contour in a 3D surface and evolve that surface over time according to an image-dependent speed function. A speed function suitable for segmentation of CL's in ovarian ultrasound images was developed. An initial contour was manually placed and contour evolution was allowed to proceed until the rate of change of the area was sufficiently small. The method was tested on ovarian ultrasonographic images (n = 8 obtained ex situ. A expert in ovarian ultrasound interpretation delineated CL boundaries manually to serve as a "ground truth". Accuracy of the level set segmentation algorithm was determined by comparing semi-automatically determined contours with ground truth contours using the mean absolute difference (MAD, root mean squared difference (RMSD, Hausdorff distance (HD, sensitivity, and specificity metrics. Results and discussion The mean MAD was 0.87 mm (sigma = 0.36 mm, RMSD was 1.1 mm (sigma = 0.47 mm, and HD was 3.4 mm (sigma = 2.0 mm indicating that, on average, boundaries were accurate within 1–2 mm, however, deviations in excess of 3 mm from the ground truth were observed indicating under- or over-expansion of the contour. Mean sensitivity and specificity were 0.814 (sigma = 0.171 and 0.990 (sigma = 0.00786, respectively, indicating that CLs were consistently undersegmented but rarely did the contour interior include pixels that were judged by the human expert not to be part of the CL. It was observed that in localities where gradient magnitudes within the CL were strong due to high contrast speckle, contour expansion stopped too early. Conclusion The
Consolidated Ground Segment Requirements for a UHF Radar for the ESSAS

Science.gov (United States)

Muller, Florent; Vera, Juan

2009-03-01

ESA has launched a nine months long study to define the requirements associated to the ground segment of a UHF (300-3000 MHz) radar system. The study has been awarded in open competition to a consortium led by Onera, associated to the Spanish companies Indra and its sub-contractor Deimos. After a phase of consolidation of the requirements, different monostatic and bistatic concepts of radars will be proposed and evaluated. Two concepts will be selected for further design studies. ESA will then select the best one, for detailed design as well as cost and performance evaluation. The aim of this paper is to present the results of the first phase of the study concerning the consolidation of the radar system requirements. The main mission for the system is to be able to build and maintain a catalogue of the objects in low Earth orbit (apogee lower than 2000km) in an autonomous way, for different sizes of objects, depending on the future successive development phases of the project. The final step must give the capability of detecting and tracking 10cm objects, with a possible upgrade to 5 cm objects. A demonstration phase must be defined for 1 m objects. These different steps will be considered during all the phases of the study. Taking this mission and the different steps of the study as a starting point, the first phase will define a set of requirements for the radar system. It was finished at the end of January 2009. First part will describe the constraints derived from the targets and their environment. Orbiting objects have a given distribution in space, and their observability and detectability are based on it. It is also related to the location of the radar system But they are also dependant on the natural propagation phenomenon, especially ionospheric issues, and the characteristics of the objects. Second part will focus on the mission itself. To carry out the mission, objects must be detected and tracked regularly to refresh the associated orbital parameters
SU-F-J-111: A Novel Distance-Dose Weighting Method for Label Fusion in Multi- Atlas Segmentation for Prostate Radiation Therapy

International Nuclear Information System (INIS)

Chang, J; Gu, X; Lu, W; Jiang, S; Song, T

2016-01-01

Purpose: A novel distance-dose weighting method for label fusion was developed to increase segmentation accuracy in dosimetrically important regions for prostate radiation therapy. Methods: Label fusion as implemented in the original SIMPLE (OS) for multi-atlas segmentation relies iteratively on the majority vote to generate an estimated ground truth and DICE similarity measure to screen candidates. The proposed distance-dose weighting puts more values on dosimetrically important regions when calculating similarity measure. Specifically, we introduced distance-to-dose error (DDE), which converts distance to dosimetric importance, in performance evaluation. The DDE calculates an estimated DE error derived from surface distance differences between the candidate and estimated ground truth label by multiplying a regression coefficient. To determine the coefficient at each simulation point on the rectum, we fitted DE error with respect to simulated voxel shift. The DEs were calculated by the multi-OAR geometry-dosimetry training model previously developed in our research group. Results: For both the OS and the distance-dose weighted SIMPLE (WS) results, the evaluation metrics for twenty patients were calculated using the ground truth segmentation. The mean difference of DICE, Hausdorff distance, and mean absolute distance (MAD) between OS and WS have shown 0, 0.10, and 0.11, respectively. In partial MAD of WS which calculates MAD within a certain PTV expansion voxel distance, the lower MADs were observed at the closer distances from 1 to 8 than those of OS. The DE results showed that the segmentation from WS produced more accurate results than OS. The mean DE error of V75, V70, V65, and V60 were decreased by 1.16%, 1.17%, 1.14%, and 1.12%, respectively. Conclusion: We have demonstrated that the method can increase the segmentation accuracy in rectum regions adjacent to PTV. As a result, segmentation using WS have shown improved dosimetric accuracy than OS. The WS will
SU-F-J-111: A Novel Distance-Dose Weighting Method for Label Fusion in Multi- Atlas Segmentation for Prostate Radiation Therapy

Energy Technology Data Exchange (ETDEWEB)

Chang, J; Gu, X; Lu, W; Jiang, S [UT Southwestern Medical Center, Dallas, TX (United States); Song, T [Southern Medical University, Guangzhou, Guangdong (China)

2016-06-15

Purpose: A novel distance-dose weighting method for label fusion was developed to increase segmentation accuracy in dosimetrically important regions for prostate radiation therapy. Methods: Label fusion as implemented in the original SIMPLE (OS) for multi-atlas segmentation relies iteratively on the majority vote to generate an estimated ground truth and DICE similarity measure to screen candidates. The proposed distance-dose weighting puts more values on dosimetrically important regions when calculating similarity measure. Specifically, we introduced distance-to-dose error (DDE), which converts distance to dosimetric importance, in performance evaluation. The DDE calculates an estimated DE error derived from surface distance differences between the candidate and estimated ground truth label by multiplying a regression coefficient. To determine the coefficient at each simulation point on the rectum, we fitted DE error with respect to simulated voxel shift. The DEs were calculated by the multi-OAR geometry-dosimetry training model previously developed in our research group. Results: For both the OS and the distance-dose weighted SIMPLE (WS) results, the evaluation metrics for twenty patients were calculated using the ground truth segmentation. The mean difference of DICE, Hausdorff distance, and mean absolute distance (MAD) between OS and WS have shown 0, 0.10, and 0.11, respectively. In partial MAD of WS which calculates MAD within a certain PTV expansion voxel distance, the lower MADs were observed at the closer distances from 1 to 8 than those of OS. The DE results showed that the segmentation from WS produced more accurate results than OS. The mean DE error of V75, V70, V65, and V60 were decreased by 1.16%, 1.17%, 1.14%, and 1.12%, respectively. Conclusion: We have demonstrated that the method can increase the segmentation accuracy in rectum regions adjacent to PTV. As a result, segmentation using WS have shown improved dosimetric accuracy than OS. The WS will
Kinematics and strain analyses of the eastern segment of the Pernicana Fault (Mt. Etna, Italy derived from geodetic techniques (1997-2005

Directory of Open Access Journals (Sweden)

M. Mattia

2006-06-01

Full Text Available This paper analyses the ground deformations occurring on the eastern part of the Pernicana Fault from 1997 to 2005. This segment of the fault was monitored with three local networks based on GPS and EDM techniques. More than seventy GPS and EDM surveys were carried out during the considered period, in order to achieve a higher temporal detail of ground deformation affecting the structure. We report the comparisons among GPS and EDM surveys in terms of absolute horizontal displacements of each GPS benchmark and in terms of strain parameters for each GPS and EDM network. Ground deformation measurements detected a continuous left-lateral movement of the Pernicana Fault. We conclude that, on the easternmost part of the Pernicana Fault, where it branches out into two segments, the deformation is transferred entirely SE-wards by a splay fault.

Event-Based Color Segmentation With a High Dynamic Range Sensor

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Alexandre Marcireau

2018-04-01

Full Text Available This paper introduces a color asynchronous neuromorphic event-based camera and a methodology to process color output from the device to perform color segmentation and tracking at the native temporal resolution of the sensor (down to one microsecond. Our color vision sensor prototype is a combination of three Asynchronous Time-based Image Sensors, sensitive to absolute color information. We devise a color processing algorithm leveraging this information. It is designed to be computationally cheap, thus showing how low level processing benefits from asynchronous acquisition and high temporal resolution data. The resulting color segmentation and tracking performance is assessed both with an indoor controlled scene and two outdoor uncontrolled scenes. The tracking's mean error to the ground truth for the objects of the outdoor scenes ranges from two to twenty pixels.
Ground Systems Development and Operations (GSDO) Education 101: Exploration Begins Here [Grades 9-12

Science.gov (United States)

Hill, Trudy

2012-01-01

Presentation to inform the non-NASA general public and school children of ground systems development and operations activities at Kennedy Space Center, particularly on what GSDO is and does, in a high level overview.
Overview and status of the prototype project for Wendelstein 7-X control system

Energy Technology Data Exchange (ETDEWEB)

Schacht, Joerg [Max-Planck-Institut fuer Plasmaphysik, EURATOM Association, Teilinstitut Greifswald, Wendelsteinstrasse 1, D-17491 Greifswald (Germany)], E-mail: joerg.schacht@ipp.mpg.de; Bluhm, Torsten; Herbst, Uwe; Hennig, Christine; Heinrich, Stefan; Kuehner, Georg; Koester, Erik; Laqua, Heike; Lewerentz, Marc; Marquardt, Mirco; Meyer, Christiane; Mueller, Ina; Pingel, Steffen; Sachtleben, Juergen; Spring, Anett; Werner, Andreas; Woelk, Andreas [Max-Planck-Institut fuer Plasmaphysik, EURATOM Association, Teilinstitut Greifswald, Wendelsteinstrasse 1, D-17491 Greifswald (Germany)

2009-06-15

This contribution gives an overview of the project 'Prototype W7-X control system'. The objective of this prototype project is to demonstrate the applicability of the segment orientated control system at a running fusion experiment including steady-state operation, interaction of all relevant components, real time control, data acquisition and on-line data analysis. Furthermore, the W7-X safety concept will be implemented at WEGA and tested.
Rail freight vibration impact sleep and community response: An overview of CargoVibes

NARCIS (Netherlands)

Persson Waye, K.; Janssen, S.A.; Waddington, D.; Groll, W.; Croy, I.; Hammar, O.; Koopman, A.; Moorhouse, A.; Peris, E.; Sharp, C.; Sica, G.; Smith, M.G.; Vos, H.; Woodcock, J.; Ogren, M.

2014-01-01

The European Union funded project: CargoVibes involving ten partners from eight nations has aimed to examine ground-borne vibration affecting residents close to freight railway lines. The paper presents an overview of the work package investigating human response to vibration, with particular focus
Automatic segmentation of Leishmania parasite in microscopic images using a modified CV level set method

Science.gov (United States)

Farahi, Maria; Rabbani, Hossein; Talebi, Ardeshir; Sarrafzadeh, Omid; Ensafi, Shahab

2015-12-01

Visceral Leishmaniasis is a parasitic disease that affects liver, spleen and bone marrow. According to World Health Organization report, definitive diagnosis is possible just by direct observation of the Leishman body in the microscopic image taken from bone marrow samples. We utilize morphological and CV level set method to segment Leishman bodies in digital color microscopic images captured from bone marrow samples. Linear contrast stretching method is used for image enhancement and morphological method is applied to determine the parasite regions and wipe up unwanted objects. Modified global and local CV level set methods are proposed for segmentation and a shape based stopping factor is used to hasten the algorithm. Manual segmentation is considered as ground truth to evaluate the proposed method. This method is tested on 28 samples and achieved 10.90% mean of segmentation error for global model and 9.76% for local model.
IXV re-entry demonstrator: Mission overview, system challenges and flight reward

Science.gov (United States)

Angelini, Roberto; Denaro, Angelo

2016-07-01

The Intermediate eXperimental Vehicle (IXV) is an advanced re-entry demonstrator vehicle aimed to perform in-flight experimentation of atmospheric re-entry enabling systems and technologies. The IXV integrates key technologies at the system level, with significant advancements on Europe's previous flying test-beds. The project builds on previous achievements at system and technology levels, and provides a unique and concrete way of establishing and consolidating Europe's autonomous position in the strategic field of atmospheric re-entry. The IXV mission and system objectives are the design, development, manufacturing, assembling and on-ground to in-flight verification of an autonomous European lifting and aerodynamically controlled reentry system, integrating critical re-entry technologies at system level. Among such critical technologies of interest, special attention is paid to aerodynamic and aerothermodynamics experimentation, including advanced instrumentation for aerothermodynamics phenomena investigations, thermal protections and hot-structures, guidance, navigation and flight control through combined jets and aerodynamic surfaces (i.e. flaps), in particular focusing on the technologies integration at system level for flight. Following the extensive detailed design, manufacturing, qualification, integration and testing of the flight segment and ground segment elements, IXV has performed a full successful flight on February 11th 2015. After the launch with the VEGA launcher form the CSG spaceport in French Guyana, IXV has performed a full nominal mission ending with a successful splashdown in the Pacific Ocean. During Flight Phase, the IXV space and ground segments worked perfectly, implementing the whole flight program in line with the commanded maneuvers and trajectory prediction, performing an overall flight of 34.400 km including 7.600 km with hot atmospheric re-entry in automatic guidance, concluding with successful precision landing at a distance of ~1
Altered figure-ground perception in monkeys with an extra-striate lesion.

Science.gov (United States)

Supèr, Hans; Lamme, Victor A F

2007-11-05

The visual system binds and segments the elements of an image into coherent objects and their surroundings. Recent findings demonstrate that primary visual cortex is involved in this process of figure-ground organization. In the primary visual cortex the late part of a neural response to a stimulus correlates with figure-ground segregation and perception. Such a late onset indicates an involvement of feedback projections from higher visual areas. To investigate the possible role of feedback in figure-ground perception we removed dorsal extra-striate areas of the monkey visual cortex. The findings show that figure-ground perception is reduced when the figure is presented in the lesioned hemifield and perception is normal when the figure appeared in the intact hemifield. In conclusion, our observations show the importance for recurrent processing in visual perception.
The application of grounded theory and symbolic interactionism.

Science.gov (United States)

Jeon, Yun-Hee

2004-09-01

This paper describes the methodological and theoretical context and underpinnings of a study that examined community psychiatric nurses' work with family caregivers of older people with depression. The study used grounded theory research methods, with its theoretical foundations drawn from symbolic interactionism. The aims of the study were to describe and conceptualize the processes involved when community nurses work and interact with family caregivers and to develop an explanatory theory of these processes. This paper begins with an explanation of the rationale for using grounded theory as the method of choice, followed by a discussion of the theoretical underpinnings of the study, including a brief summary of the nature and origins of symbolic interactionism. Key premises of symbolic interactionism regarded as central to the study are outlined and an analytical overview of the grounded theory method is provided. The paper concludes with a commentary on some of the issues and debates in the use of grounded theory in nursing research. The main purpose of this paper is to provide a methodical and critical review of symbolic interactionism and grounded theory that can help readers, particularly those who are intending to use grounded theory, better understand the processes involved in applying this method to their research.
Coronary Arteries Segmentation Based on the 3D Discrete Wavelet Transform and 3D Neutrosophic Transform

Directory of Open Access Journals (Sweden)

Shuo-Tsung Chen

2015-01-01

Full Text Available Purpose. Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies. Methods. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband coefficients of the 3D DWT, was detected by the proposed vessel-texture discrimination algorithm. Based on the initial segmentation, 3D DWT integrated with the 3D neutrosophic transformation could accurately detect the coronary arteries. Results. Each subbranch of the segmented coronary arteries was segmented correctly by the proposed method. The obtained results are compared with those ground truth values obtained from the commercial software from GE Healthcare and the level-set method proposed by Yang et al., 2007. Results indicate that the proposed method is better in terms of efficiency analyzed. Conclusion. Based on the initial segmentation of coronary arteries obtained from 3D region growing, one-level 3D DWT and 3D neutrosophic transformation can be applied to detect coronary pathologies accurately.
The planned Alaska SAR Facility - An overview

Science.gov (United States)

Carsey, Frank; Weeks, Wilford

1987-01-01

The Alaska SAR Facility (ASF) is described in an overview fashion. The facility consists of three major components, a Receiving Ground System, a SAR Processing System and an Analysis and Archiving System; the ASF Program also has a Science Working Team and the requisite management and operations systems. The ASF is now an approved and fully funded activity; detailed requirements and science background are presented for the facility to be implemented for data from the European ERS-1, the Japanese ERS-1 and Radarsat.
Brookhaven segment interconnect

International Nuclear Information System (INIS)

Morse, W.M.; Benenson, G.; Leipuner, L.B.

1983-01-01

We have performed a high energy physics experiment using a multisegment Brookhaven FASTBUS system. The system was composed of three crate segments and two cable segments. We discuss the segment interconnect module which permits communication between the various segments
Linked statistical shape models for multi-modal segmentation: application to prostate CT-MR segmentation in radiotherapy planning

Science.gov (United States)

Chowdhury, Najeeb; Chappelow, Jonathan; Toth, Robert; Kim, Sung; Hahn, Stephen; Vapiwala, Neha; Lin, Haibo; Both, Stefan; Madabhushi, Anant

2011-03-01

We present a novel framework for building a linked statistical shape model (LSSM), a statistical shape model (SSM) that links the shape variation of a structure of interest (SOI) across multiple imaging modalities. This framework is particularly relevant in scenarios where accurate delineations of a SOI's boundary on one of the modalities may not be readily available, or difficult to obtain, for training a SSM. We apply the LSSM in the context of multi-modal prostate segmentation for radiotherapy planning, where we segment the prostate on MRI and CT simultaneously. Prostate capsule segmentation is a critical step in prostate radiotherapy planning, where dose plans have to be formulated on CT. Since accurate delineations of the prostate boundary are very difficult to obtain on CT, pre-treatment MRI is now beginning to be acquired at several medical centers. Delineation of the prostate on MRI is acknowledged as being significantly simpler to do compared to CT. Hence, our framework incorporates multi-modal registration of MRI and CT to map 2D boundary delineations of prostate (obtained from an expert radiation oncologist) on MR training images onto corresponding CT images. The delineations of the prostate capsule on MRI and CT allows for 3D reconstruction of the prostate shape which facilitates the building of the LSSM. We acquired 7 MRI-CT patient studies and used the leave-one-out strategy to train and evaluate our LSSM (fLSSM), built using expert ground truth delineations on MRI and MRI-CT fusion derived capsule delineations on CT. A unique attribute of our fLSSM is that it does not require expert delineations of the capsule on CT. In order to perform prostate MRI segmentation using the fLSSM, we employed a regionbased approach where we deformed the evolving prostate boundary to optimize a mutual information based cost criterion, which took into account region-based intensity statistics of the image being segmented. The final prostate segmentation was then
Active Segmentation.

Science.gov (United States)

Mishra, Ajay; Aloimonos, Yiannis

2009-01-01

The human visual system observes and understands a scene/image by making a series of fixations. Every fixation point lies inside a particular region of arbitrary shape and size in the scene which can either be an object or just a part of it. We define as a basic segmentation problem the task of segmenting that region containing the fixation point. Segmenting the region containing the fixation is equivalent to finding the enclosing contour- a connected set of boundary edge fragments in the edge map of the scene - around the fixation. This enclosing contour should be a depth boundary.We present here a novel algorithm that finds this bounding contour and achieves the segmentation of one object, given the fixation. The proposed segmentation framework combines monocular cues (color/intensity/texture) with stereo and/or motion, in a cue independent manner. The semantic robots of the immediate future will be able to use this algorithm to automatically find objects in any environment. The capability of automatically segmenting objects in their visual field can bring the visual processing to the next level. Our approach is different from current approaches. While existing work attempts to segment the whole scene at once into many areas, we segment only one image region, specifically the one containing the fixation point. Experiments with real imagery collected by our active robot and from the known databases 1 demonstrate the promise of the approach.
A fourth order PDE based fuzzy c- means approach for segmentation of microscopic biopsy images in presence of Poisson noise for cancer detection.

Science.gov (United States)

Kumar, Rajesh; Srivastava, Subodh; Srivastava, Rajeev

2017-07-01

For cancer detection from microscopic biopsy images, image segmentation step used for segmentation of cells and nuclei play an important role. Accuracy of segmentation approach dominate the final results. Also the microscopic biopsy images have intrinsic Poisson noise and if it is present in the image the segmentation results may not be accurate. The objective is to propose an efficient fuzzy c-means based segmentation approach which can also handle the noise present in the image during the segmentation process itself i.e. noise removal and segmentation is combined in one step. To address the above issues, in this paper a fourth order partial differential equation (FPDE) based nonlinear filter adapted to Poisson noise with fuzzy c-means segmentation method is proposed. This approach is capable of effectively handling the segmentation problem of blocky artifacts while achieving good tradeoff between Poisson noise removals and edge preservation of the microscopic biopsy images during segmentation process for cancer detection from cells. The proposed approach is tested on breast cancer microscopic biopsy data set with region of interest (ROI) segmented ground truth images. The microscopic biopsy data set contains 31 benign and 27 malignant images of size 896 × 768. The region of interest selected ground truth of all 58 images are also available for this data set. Finally, the result obtained from proposed approach is compared with the results of popular segmentation algorithms; fuzzy c-means, color k-means, texture based segmentation, and total variation fuzzy c-means approaches. The experimental results shows that proposed approach is providing better results in terms of various performance measures such as Jaccard coefficient, dice index, Tanimoto coefficient, area under curve, accuracy, true positive rate, true negative rate, false positive rate, false negative rate, random index, global consistency error, and variance of information as compared to other
TU-F-17A-03: A 4D Lung Phantom for Coupled Registration/Segmentation Evaluation

International Nuclear Information System (INIS)

Markel, D; El Naqa, I; Levesque, I

2014-01-01

Purpose: Coupling the processes of segmentation and registration (regmentation) is a recent development that allows improved efficiency and accuracy for both steps and may improve the clinical feasibility of online adaptive radiotherapy. Presented is a multimodality animal tissue model designed specifically to provide a ground truth to simultaneously evaluate segmentation and registration errors during respiratory motion. Methods: Tumor surrogates were constructed from vacuum sealed hydrated natural sea sponges with catheters used for the injection of PET radiotracer. These contained two compartments allowing for two concentrations of radiotracer mimicking both tumor and background signals. The lungs were inflated to different volumes using an air pump and flow valve and scanned using PET/CT and MRI. Anatomical landmarks were used to evaluate the registration accuracy using an automated bifurcation tracking pipeline for reproducibility. The bifurcation tracking accuracy was assessed using virtual deformations of 2.6 cm, 5.2 cm and 7.8 cm of a CT scan of a corresponding human thorax. Bifurcations were detected in the deformed dataset and compared to known deformation coordinates for 76 points. Results: The bifurcation tracking accuracy was found to have a mean error of −0.94, 0.79 and −0.57 voxels in the left-right, anterior-posterior and inferior-superior axes using a 1×1×5 mm3 resolution after the CT volume was deformed 7.8 cm. The tumor surrogates provided a segmentation ground truth after being registered to the phantom image. Conclusion: A swine lung model in conjunction with vacuum sealed sponges and a bifurcation tracking algorithm is presented that is MRI, PET and CT compatible and anatomically and kinetically realistic. Corresponding software for tracking anatomical landmarks within the phantom shows sub-voxel accuracy. Vacuum sealed sponges provide realistic tumor surrogate with a known boundary. A ground truth with minimal uncertainty is thus
Use of segmented constrained layer damping treatment for improved helicopter aeromechanical stability

Science.gov (United States)

Liu, Qiang; Chattopadhyay, Aditi; Gu, Haozhong; Liu, Qiang; Chattopadhyay, Aditi; Zhou, Xu

2000-08-01

The use of a special type of smart material, known as segmented constrained layer (SCL) damping, is investigated for improved rotor aeromechanical stability. The rotor blade load-carrying member is modeled using a composite box beam with arbitrary wall thickness. The SCLs are bonded to the upper and lower surfaces of the box beam to provide passive damping. A finite-element model based on a hybrid displacement theory is used to accurately capture the transverse shear effects in the composite primary structure and the viscoelastic and the piezoelectric layers within the SCL. Detailed numerical studies are presented to assess the influence of the number of actuators and their locations for improved aeromechanical stability. Ground and air resonance analysis models are implemented in the rotor blade built around the composite box beam with segmented SCLs. A classic ground resonance model and an air resonance model are used in the rotor-body coupled stability analysis. The Pitt dynamic inflow model is used in the air resonance analysis under hover condition. Results indicate that the surface bonded SCLs significantly increase rotor lead-lag regressive modal damping in the coupled rotor-body system.
GeoSegmenter: A statistically learned Chinese word segmenter for the geoscience domain

Science.gov (United States)

Huang, Lan; Du, Youfu; Chen, Gongyang

2015-03-01

Unlike English, the Chinese language has no space between words. Segmenting texts into words, known as the Chinese word segmentation (CWS) problem, thus becomes a fundamental issue for processing Chinese documents and the first step in many text mining applications, including information retrieval, machine translation and knowledge acquisition. However, for the geoscience subject domain, the CWS problem remains unsolved. Although a generic segmenter can be applied to process geoscience documents, they lack the domain specific knowledge and consequently their segmentation accuracy drops dramatically. This motivated us to develop a segmenter specifically for the geoscience subject domain: the GeoSegmenter. We first proposed a generic two-step framework for domain specific CWS. Following this framework, we built GeoSegmenter using conditional random fields, a principled statistical framework for sequence learning. Specifically, GeoSegmenter first identifies general terms by using a generic baseline segmenter. Then it recognises geoscience terms by learning and applying a model that can transform the initial segmentation into the goal segmentation. Empirical experimental results on geoscience documents and benchmark datasets showed that GeoSegmenter could effectively recognise both geoscience terms and general terms.
The microelectronics and photonics test bed (MPTB) space, ground test and modeling experiments

International Nuclear Information System (INIS)

Campbell, A.

1999-01-01

This paper is an overview of the MPTB (microelectronics and photonics test bed) experiment, a combination of a space experiment, ground test and modeling programs looking at the response of advanced electronic and photonic technologies to the natural radiation environment of space. (author)
DeepCotton: in-field cotton segmentation using deep fully convolutional network

Science.gov (United States)

Li, Yanan; Cao, Zhiguo; Xiao, Yang; Cremers, Armin B.

2017-09-01

Automatic ground-based in-field cotton (IFC) segmentation is a challenging task in precision agriculture, which has not been well addressed. Nearly all the existing methods rely on hand-crafted features. Their limited discriminative power results in unsatisfactory performance. To address this, a coarse-to-fine cotton segmentation method termed "DeepCotton" is proposed. It contains two modules, fully convolutional network (FCN) stream and interference region removal stream. First, FCN is employed to predict initially coarse map in an end-to-end manner. The convolutional networks involved in FCN guarantee powerful feature description capability, simultaneously, the regression analysis ability of neural network assures segmentation accuracy. To our knowledge, we are the first to introduce deep learning to IFC segmentation. Second, our proposed "UP" algorithm composed of unary brightness transformation and pairwise region comparison is used for obtaining interference map, which is executed to refine the coarse map. The experiments on constructed IFC dataset demonstrate that our method outperforms other state-of-the-art approaches, either in different common scenarios or single/multiple plants. More remarkable, the "UP" algorithm greatly improves the property of the coarse result, with the average amplifications of 2.6%, 2.4% on accuracy and 8.1%, 5.5% on intersection over union for common scenarios and multiple plants, separately.
Single-segment and double-segment INTACS for post-LASIK ectasia.

Directory of Open Access Journals (Sweden)

Hassan Hashemi

2014-09-01

Full Text Available The objective of the present study was to compare single segment and double segment INTACS rings in the treatment of post-LASIK ectasia. In this interventional study, 26 eyes with post-LASIK ectasia were assessed. Ectasia was defined as progressive myopia regardless of astigmatism, along with topographic evidence of inferior steepening of the cornea after LASIK. We excluded those with a history of intraocular surgery, certain eye conditions, and immune disorders, as well as monocular, pregnant and lactating patients. A total of 11 eyes had double ring and 15 eyes had single ring implantation. Visual and refractive outcomes were compared with preoperative values based on the number of implanted INTACS rings. Pre and postoperative spherical equivalent were -3.92 and -2.29 diopter (P=0.007. The spherical equivalent decreased by 1 ± 3.2 diopter in the single-segment group and 2.56 ± 1.58 diopter in the double-segment group (P=0.165. Mean preoperative astigmatism was 2.38 ± 1.93 diopter which decreased to 2.14 ± 1.1 diopter after surgery (P=0.508; 0.87 ± 1.98 diopter decrease in the single-segment group and 0.67 ± 1.2 diopter increase in the double-segment group (P=0.025. Nineteen patients (75% gained one or two lines, and only three, who were all in the double-segment group, lost one or two lines of best corrected visual acuity. The spherical equivalent and vision significantly decreased in all patients. In these post-LASIK ectasia patients, the spherical equivalent was corrected better with two segments compared to single segment implantation; nonetheless, the level of astigmatism in the single-segment group was significantly better than that in the double-segment group.

Low-Grade Glioma Segmentation Based on CNN with Fully Connected CRF

Directory of Open Access Journals (Sweden)

Zeju Li

2017-01-01

Full Text Available This work proposed a novel automatic three-dimensional (3D magnetic resonance imaging (MRI segmentation method which would be widely used in the clinical diagnosis of the most common and aggressive brain tumor, namely, glioma. The method combined a multipathway convolutional neural network (CNN and fully connected conditional random field (CRF. Firstly, 3D information was introduced into the CNN which makes more accurate recognition of glioma with low contrast. Then, fully connected CRF was added as a postprocessing step which purposed more delicate delineation of glioma boundary. The method was applied to T2flair MRI images of 160 low-grade glioma patients. With 59 cases of data training and manual segmentation as the ground truth, the Dice similarity coefficient (DSC of our method was 0.85 for the test set of 101 MRI images. The results of our method were better than those of another state-of-the-art CNN method, which gained the DSC of 0.76 for the same dataset. It proved that our method could produce better results for the segmentation of low-grade gliomas.
Influence of Segmentation of Ring-Shaped NdFeB Magnets with Parallel Magnetization on Cylindrical Actuators

Directory of Open Access Journals (Sweden)

Paulo Roberto Eckert

2014-07-01

Full Text Available This work analyses the effects of segmentation followed by parallel magnetization of ring-shaped NdFeB permanent magnets used in slotless cylindrical linear actuators. The main purpose of the work is to evaluate the effects of that segmentation on the performance of the actuator and to present a general overview of the influence of parallel magnetization by varying the number of segments and comparing the results with ideal radially magnetized rings. The analysis is first performed by modelling mathematically the radial and circumferential components of magnetization for both radial and parallel magnetizations, followed by an analysis carried out by means of the 3D finite element method. Results obtained from the models are validated by measuring radial and tangential components of magnetic flux distribution in the air gap on a prototype which employs magnet rings with eight segments each with parallel magnetization. The axial force produced by the actuator was also measured and compared with the results obtained from numerical models. Although this analysis focused on a specific topology of cylindrical actuator, the observed effects on the topology could be extended to others in which surface-mounted permanent magnets are employed, including rotating electrical machines.
Influence of segmentation of ring-shaped NdFeB magnets with parallel magnetization on cylindrical actuators.

Science.gov (United States)

Eckert, Paulo Roberto; Goltz, Evandro Claiton; Flores Filho, Aly Ferreira

2014-07-21

This work analyses the effects of segmentation followed by parallel magnetization of ring-shaped NdFeB permanent magnets used in slotless cylindrical linear actuators. The main purpose of the work is to evaluate the effects of that segmentation on the performance of the actuator and to present a general overview of the influence of parallel magnetization by varying the number of segments and comparing the results with ideal radially magnetized rings. The analysis is first performed by modelling mathematically the radial and circumferential components of magnetization for both radial and parallel magnetizations, followed by an analysis carried out by means of the 3D finite element method. Results obtained from the models are validated by measuring radial and tangential components of magnetic flux distribution in the air gap on a prototype which employs magnet rings with eight segments each with parallel magnetization. The axial force produced by the actuator was also measured and compared with the results obtained from numerical models. Although this analysis focused on a specific topology of cylindrical actuator, the observed effects on the topology could be extended to others in which surface-mounted permanent magnets are employed, including rotating electrical machines.
Finite Element Based Response Surface Methodology to Optimize Segmental Tunnel Lining

Directory of Open Access Journals (Sweden)

A. Rastbood

2017-04-01

Full Text Available The main objective of this paper is to optimize the geometrical and engineering characteristics of concrete segments of tunnel lining using Finite Element (FE based Response Surface Methodology (RSM. Input data for RSM statistical analysis were obtained using FEM. In RSM analysis, thickness (t and elasticity modulus of concrete segments (E, tunnel height (H, horizontal to vertical stress ratio (K and position of key segment in tunnel lining ring (θ were considered as input independent variables. Maximum values of Mises and Tresca stresses and tunnel ring displacement (UMAX were set as responses. Analysis of variance (ANOVA was carried out to investigate the influence of each input variable on the responses. Second-order polynomial equations in terms of influencing input variables were obtained for each response. It was found that elasticity modulus and key segment position variables were not included in yield stresses and ring displacement equations, and only tunnel height and stress ratio variables were included in ring displacement equation. Finally optimization analysis of tunnel lining ring was performed. Due to absence of elasticity modulus and key segment position variables in equations, their values were kept to average level and other variables were floated in related ranges. Response parameters were set to minimum. It was concluded that to obtain optimum values for responses, ring thickness and tunnel height must be near to their maximum and minimum values, respectively and ground state must be similar to hydrostatic conditions.
An Archeological Overview and Management Plan for the Dugway Proving Ground.

Science.gov (United States)

1984-03-29

niches, particulary the lacustrine environment of the Great Basin (Baumhoff and Heizer 1965, Butler 1978, Heizer and Krieger 1956, Heizer and Harper...power that would capture the animals souls, rendering them docile and stupid (Steward 1970:34). Other large game was present, but were not numerous...uni versity. Baum, Bernard. 1947. Dugway Proving Ground. Aberdeen: U.S. Army Chemical Corps.* Bailmhoff, W.A. and R.F. Heizer . 1965. Postglacial
Computer-Aided Segmentation and Volumetry of Artificial Ground-Glass Nodules at Chest CT

NARCIS (Netherlands)

Scholten, Ernst Th.; Jacobs, Colin; van Ginneken, Bram; Willemink, Martin J.; Kuhnigk, Jan-Martin; van Ooijen, Peter M. A.; Oudkerk, Matthijs; Mali, Willem P. Th. M.; de Jong, Pim A.

OBJECTIVE. The purpose of this study was to investigate a new software program for semiautomatic measurement of the volume and mass of ground-glass nodules (GGNs) in a chest phantom and to investigate the influence of CT scanner, reconstruction filter, tube voltage, and tube current. MATERIALS AND
Ground-Based Telescope Parametric Cost Model

Science.gov (United States)

Stahl, H. Philip; Rowell, Ginger Holmes

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis, The model includes both engineering and performance parameters. While diameter continues to be the dominant cost driver, other significant factors include primary mirror radius of curvature and diffraction limited wavelength. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e.. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter are derived. This analysis indicates that recent mirror technology advances have indeed reduced the historical telescope cost curve.
Aortic root segmentation in 4D transesophageal echocardiography

Science.gov (United States)

Chechani, Shubham; Suresh, Rahul; Patwardhan, Kedar A.

2018-02-01

The Aortic Valve (AV) is an important anatomical structure which lies on the left side of the human heart. The AV regulates the flow of oxygenated blood from the Left Ventricle (LV) to the rest of the body through aorta. Pathologies associated with the AV manifest themselves in structural and functional abnormalities of the valve. Clinical management of pathologies often requires repair, reconstruction or even replacement of the valve through surgical intervention. Assessment of these pathologies as well as determination of specific intervention procedure requires quantitative evaluation of the valvular anatomy. 4D (3D + t) Transesophageal Echocardiography (TEE) is a widely used imaging technique that clinicians use for quantitative assessment of cardiac structures. However, manual quantification of 3D structures is complex, time consuming and suffers from inter-observer variability. Towards this goal, we present a semiautomated approach for segmentation of the aortic root (AR) structure. Our approach requires user-initialized landmarks in two reference frames to provide AR segmentation for full cardiac cycle. We use `coarse-to-fine' B-spline Explicit Active Surface (BEAS) for AR segmentation and Masked Normalized Cross Correlation (NCC) method for AR tracking. Our method results in approximately 0.51 mm average localization error in comparison with ground truth annotation performed by clinical experts on 10 real patient cases (139 3D volumes).
Feedback from Westinghouse experience on segmentation of reactor vessel internals - 59013

International Nuclear Information System (INIS)

Kreitman, Paul J.; Boucau, Joseph; Segerud, Per; Fallstroem, Stefan

2012-01-01

successful reactor vessel internals segmentation and packaging project. The purpose of this paper is to provide an overview of the Westinghouse reactor internals segmentation experience by illustrating projects related to various types of reactors and providing feedback from project execution. (authors)
Segmental and Kinetic Contributions in Vertical Jumps Performed with and without an Arm Swing

Science.gov (United States)

Feltner, Michael E.; Bishop, Elijah J.; Perez, Cassandra M.

2004-01-01

To determine the contributions of the motions of the body segments to the vertical ground reaction force ([F.sub.z]), the joint torques produced by the leg muscles, and the time course of vertical velocity generation during a vertical jump, 15 men were videotaped performing countermovement vertical jumps from a force plate with and without an arm…
Status of advanced ground-based laser interferometers for gravitational-wave detection

Science.gov (United States)

Dooley, K. L.; Akutsu, T.; Dwyer, S.; Puppo, P.

2015-05-01

Ground-based laser interferometers for gravitational-wave (GW) detection were first constructed starting 20 years ago and as of 2010 collection of several years’ worth of science data at initial design sensitivities was completed. Upgrades to the initial detectors together with construction of brand new detectors are ongoing and feature advanced technologies to improve the sensitivity to GWs. This conference proceeding provides an overview of the common design features of ground-based laser interferometric GW detectors and establishes the context for the status updates of each of the four gravitational-wave detectors around the world: Advanced LIGO, Advanced Virgo, GEO 600 and KAGRA.
Accounting for segment correlations in segmented gamma-ray scans

International Nuclear Information System (INIS)

Sheppard, G.A.; Prettyman, T.H.; Piquette, E.C.

1994-01-01

In a typical segmented gamma-ray scanner (SGS), the detector's field of view is collimated so that a complete horizontal slice or segment of the desired thickness is visible. Ordinarily, the collimator is not deep enough to exclude gamma rays emitted from sample volumes above and below the segment aligned with the collimator. This can lead to assay biases, particularly for certain radioactive-material distributions. Another consequence of the collimator's low aspect ratio is that segment assays at the top and bottom of the sample are biased low because the detector's field of view is not filled. This effect is ordinarily countered by placing the sample on a low-Z pedestal and scanning one or more segment thicknesses below and above the sample. This takes extra time, however, We have investigated a number of techniques that both account for correlated segments and correct for end effects in SGS assays. Also, we have developed an algorithm that facilitates estimates of assay precision. Six calculation methods have been compared by evaluating the results of thousands of simulated, assays for three types of gamma-ray source distribution and ten masses. We will report on these computational studies and their experimental verification
Clinical evaluation of semi-automatic open-source algorithmic software segmentation of the mandibular bone: Practical feasibility and assessment of a new course of action.

Science.gov (United States)

Wallner, Jürgen; Hochegger, Kerstin; Chen, Xiaojun; Mischak, Irene; Reinbacher, Knut; Pau, Mauro; Zrnc, Tomislav; Schwenzer-Zimmerer, Katja; Zemann, Wolfgang; Schmalstieg, Dieter; Egger, Jan

2018-01-01

Computer assisted technologies based on algorithmic software segmentation are an increasing topic of interest in complex surgical cases. However-due to functional instability, time consuming software processes, personnel resources or licensed-based financial costs many segmentation processes are often outsourced from clinical centers to third parties and the industry. Therefore, the aim of this trial was to assess the practical feasibility of an easy available, functional stable and licensed-free segmentation approach to be used in the clinical practice. In this retrospective, randomized, controlled trail the accuracy and accordance of the open-source based segmentation algorithm GrowCut was assessed through the comparison to the manually generated ground truth of the same anatomy using 10 CT lower jaw data-sets from the clinical routine. Assessment parameters were the segmentation time, the volume, the voxel number, the Dice Score and the Hausdorff distance. Overall semi-automatic GrowCut segmentation times were about one minute. Mean Dice Score values of over 85% and Hausdorff Distances below 33.5 voxel could be achieved between the algorithmic GrowCut-based segmentations and the manual generated ground truth schemes. Statistical differences between the assessment parameters were not significant (p 0.94) for any of the comparison made between the two groups. Complete functional stable and time saving segmentations with high accuracy and high positive correlation could be performed by the presented interactive open-source based approach. In the cranio-maxillofacial complex the used method could represent an algorithmic alternative for image-based segmentation in the clinical practice for e.g. surgical treatment planning or visualization of postoperative results and offers several advantages. Due to an open-source basis the used method could be further developed by other groups or specialists. Systematic comparisons to other segmentation approaches or with a
Automated vessel shadow segmentation of fovea-centered spectral-domain images from multiple OCT devices

Science.gov (United States)

Wu, Jing; Gerendas, Bianca S.; Waldstein, Sebastian M.; Simader, Christian; Schmidt-Erfurth, Ursula

2014-03-01

ground truth vessel shadow regions identified by expert graders at the Vienna Reading Center (VRC). The results presented here are intended to show the feasibility of this method for the accurate and precise extraction of suitable retinal vessel shadows from multiple vendor 3D SD-OCT scans for use in intra-vendor and cross-vendor 3D OCT registration, 2D fundus registration and actual retinal vessel segmentation. The resulting percentage of true vessel shadow segments to false positive segments identified by the proposed system compared to mean grader ground truth is 95%.
Promon's participation in the Brasilsat program: first & second generations

Science.gov (United States)

Depaiva, Ricardo N.

This paper presents an overview of the Brasilsat program, space and ground segments, developed by Hughes and Promon. Promon is a Brazilian engineering company that has been actively participating in the Brasilsat Satellite Telecommunications Program since its beginning. During the first generation, as subcontractor of the Spar/Hughes/SED consortium, Promon had a significant participation in the site installation of the Ground Segment, including the antennas. During the second generation, as partner of a consortium with Hughes, Promon participated in the upgrade of Brasilsat's Ground Segment systems: the TT&C (TCR1, TCR2, and SCC) and the COCC (Communications and Operations Control Center). This upgrade consisted of the design and development of hardware and software to support the second generation requirements, followed by integration and tests, factory acceptance tests, transport to site, site installation, site acceptance tests and warranty support. The upgraded systems are distributed over four sites with remote access to the main ground station. The solutions adopted provide a high level of automation, and easy operator interaction. The hardware and software technologies were selected to provide the flexibility to incorporate new technologies and services from the demanding satellite telecommunications market.
Effects of Strike-Slip Fault Segmentation on Earthquake Energy and Seismic Hazard

Science.gov (United States)

Madden, E. H.; Cooke, M. L.; Savage, H. M.; McBeck, J.

2014-12-01

Many major strike-slip faults are segmented along strike, including those along plate boundaries in California and Turkey. Failure of distinct fault segments at depth may be the source of multiple pulses of seismic radiation observed for single earthquakes. However, how and when segmentation affects fault behavior and energy release is the basis of many outstanding questions related to the physics of faulting and seismic hazard. These include the probability for a single earthquake to rupture multiple fault segments and the effects of segmentation on earthquake magnitude, radiated seismic energy, and ground motions. Using numerical models, we quantify components of the earthquake energy budget, including the tectonic work acting externally on the system, the energy of internal rock strain, the energy required to overcome fault strength and initiate slip, the energy required to overcome frictional resistance during slip, and the radiated seismic energy. We compare the energy budgets of systems of two en echelon fault segments with various spacing that include both releasing and restraining steps. First, we allow the fault segments to fail simultaneously and capture the effects of segmentation geometry on the earthquake energy budget and on the efficiency with which applied displacement is accommodated. Assuming that higher efficiency correlates with higher probability for a single, larger earthquake, this approach has utility for assessing the seismic hazard of segmented faults. Second, we nucleate slip along a weak portion of one fault segment and let the quasi-static rupture propagate across the system. Allowing fractures to form near faults in these models shows that damage develops within releasing steps and promotes slip along the second fault, while damage develops outside of restraining steps and can prohibit slip along the second fault. Work is consumed in both the propagation of and frictional slip along these new fractures, impacting the energy available
Transitory and steady analysis of grounding structures using the LN-FDTD method

Energy Technology Data Exchange (ETDEWEB)

Oliveira, Rodrigo Melo e Silva de; Souza Sobrinho, Carlos Leonidas da S. [Federal University of Para (UFPA), Belem, PA (Brazil). Electrical and Computer Engineering Dept.], Emails: rodrigo@lane.ufpa.br, leonidas@ufpa.br

2007-07-01

This work presents an overview of the LN-FDTD method (FDTD in local and non orthogonal coordinate system) to solve Maxwell's Equations. This method has been used to simulate curved grounding structures. Results are obtained by employing the presented methodology and they are compared to reference equations available in literature. (author)
Overview of the relations earthquake source parameters and the specification of strong ground motion for design purposes

International Nuclear Information System (INIS)

Bernreuter, D.L.

1977-08-01

One of the most important steps in the seismic design process is the specification of the appropriate ground motion to be input into the design analysis. From the point-of-view of engineering design analysis, the important parameters are peak ground acceleration, spectral shape and peak spectral levels. In a few cases, ground displacement is a useful parameter. The earthquake is usually specified by giving its magnitude and either the epicentral distance or the distance of the closest point on the causitive fault to the site. Typically, the appropriate ground motion parameters are obtained using the specified magnitude and distance in equations obtained from regression analysis among the appropriate variables. Two major difficulties with such an approach are: magnitude is not the best parameter to use to define the strength of an earthquake, and little near-field data is available to establish the appropriate form for the attenuation of the ground motion with distance, source size and strength. These difficulties are important for designing a critical facility; i.e., one for which a very low risk of exceeding the design ground motion is required. Examples of such structures are nuclear power plants, schools and hospitals. for such facilities, a better understanding of the relation between the ground motion and the important earthquake source parameters could be very useful for several reasons
Ultrasound Common Carotid Artery Segmentation Based on Active Shape Model

Science.gov (United States)

Yang, Xin; Jin, Jiaoying; Xu, Mengling; Wu, Huihui; He, Wanji; Yuchi, Ming; Ding, Mingyue

2013-01-01

Carotid atherosclerosis is a major reason of stroke, a leading cause of death and disability. In this paper, a segmentation method based on Active Shape Model (ASM) is developed and evaluated to outline common carotid artery (CCA) for carotid atherosclerosis computer-aided evaluation and diagnosis. The proposed method is used to segment both media-adventitia-boundary (MAB) and lumen-intima-boundary (LIB) on transverse views slices from three-dimensional ultrasound (3D US) images. The data set consists of sixty-eight, 17 × 2 × 2, 3D US volume data acquired from the left and right carotid arteries of seventeen patients (eight treated with 80 mg atorvastatin and nine with placebo), who had carotid stenosis of 60% or more, at baseline and after three months of treatment. Manually outlined boundaries by expert are adopted as the ground truth for evaluation. For the MAB and LIB segmentations, respectively, the algorithm yielded Dice Similarity Coefficient (DSC) of 94.4% ± 3.2% and 92.8% ± 3.3%, mean absolute distances (MAD) of 0.26 ± 0.18 mm and 0.33 ± 0.21 mm, and maximum absolute distances (MAXD) of 0.75 ± 0.46 mm and 0.84 ± 0.39 mm. It took 4.3 ± 0.5 mins to segment single 3D US images, while it took 11.7 ± 1.2 mins for manual segmentation. The method would promote the translation of carotid 3D US to clinical care for the monitoring of the atherosclerotic disease progression and regression. PMID:23533535
Ultrasound Common Carotid Artery Segmentation Based on Active Shape Model

Directory of Open Access Journals (Sweden)

Xin Yang

2013-01-01

Full Text Available Carotid atherosclerosis is a major reason of stroke, a leading cause of death and disability. In this paper, a segmentation method based on Active Shape Model (ASM is developed and evaluated to outline common carotid artery (CCA for carotid atherosclerosis computer-aided evaluation and diagnosis. The proposed method is used to segment both media-adventitia-boundary (MAB and lumen-intima-boundary (LIB on transverse views slices from three-dimensional ultrasound (3D US images. The data set consists of sixty-eight, 17 × 2 × 2, 3D US volume data acquired from the left and right carotid arteries of seventeen patients (eight treated with 80 mg atorvastatin and nine with placebo, who had carotid stenosis of 60% or more, at baseline and after three months of treatment. Manually outlined boundaries by expert are adopted as the ground truth for evaluation. For the MAB and LIB segmentations, respectively, the algorithm yielded Dice Similarity Coefficient (DSC of 94.4% ± 3.2% and 92.8% ± 3.3%, mean absolute distances (MAD of 0.26 ± 0.18 mm and 0.33 ± 0.21 mm, and maximum absolute distances (MAXD of 0.75 ± 0.46 mm and 0.84 ± 0.39 mm. It took 4.3 ± 0.5 mins to segment single 3D US images, while it took 11.7 ± 1.2 mins for manual segmentation. The method would promote the translation of carotid 3D US to clinical care for the monitoring of the atherosclerotic disease progression and regression.

Hydrophilic segmented block copolymers based on poly(ethylene oxide) and monodisperse amide segments

NARCIS (Netherlands)

Husken, D.; Feijen, Jan; Gaymans, R.J.

2007-01-01

Segmented block copolymers based on poly(ethylene oxide) (PEO) flexible segments and monodisperse crystallizable bisester tetra-amide segments were made via a polycondensation reaction. The molecular weight of the PEO segments varied from 600 to 4600 g/mol and a bisester tetra-amide segment (T6T6T)
Automatic segmentation of the right ventricle from cardiac MRI using a learning-based approach.

Science.gov (United States)

Avendi, Michael R; Kheradvar, Arash; Jafarkhani, Hamid

2017-12-01

This study aims to accurately segment the right ventricle (RV) from cardiac MRI using a fully automatic learning-based method. The proposed method uses deep learning algorithms, i.e., convolutional neural networks and stacked autoencoders, for automatic detection and initial segmentation of the RV chamber. The initial segmentation is then combined with the deformable models to improve the accuracy and robustness of the process. We trained our algorithm using 16 cardiac MRI datasets of the MICCAI 2012 RV Segmentation Challenge database and validated our technique using the rest of the dataset (32 subjects). An average Dice metric of 82.5% along with an average Hausdorff distance of 7.85 mm were achieved for all the studied subjects. Furthermore, a high correlation and level of agreement with the ground truth contours for end-diastolic volume (0.98), end-systolic volume (0.99), and ejection fraction (0.93) were observed. Our results show that deep learning algorithms can be effectively used for automatic segmentation of the RV. Computed quantitative metrics of our method outperformed that of the existing techniques participated in the MICCAI 2012 challenge, as reported by the challenge organizers. Magn Reson Med 78:2439-2448, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Spinal segmental dysgenesis

Directory of Open Access Journals (Sweden)

N Mahomed

2009-06-01

Full Text Available Spinal segmental dysgenesis is a rare congenital spinal abnormality , seen in neonates and infants in which a segment of the spine and spinal cord fails to develop normally . The condition is segmental with normal vertebrae above and below the malformation. This condition is commonly associated with various abnormalities that affect the heart, genitourinary, gastrointestinal tract and skeletal system. We report two cases of spinal segmental dysgenesis and the associated abnormalities.
Ocular Drug Delivery Barriers—Role of Nanocarriers in the Treatment of Anterior Segment Ocular Diseases

Science.gov (United States)

Bachu, Rinda Devi; Chowdhury, Pallabitha; Al-Saedi, Zahraa H. F.; Karla, Pradeep K.; Boddu, Sai H. S.

2018-01-01

Ocular drug delivery is challenging due to the presence of anatomical and physiological barriers. These barriers can affect drug entry into the eye following multiple routes of administration (e.g., topical, systemic, and injectable). Topical administration in the form of eye drops is preferred for treating anterior segment diseases, as it is convenient and provides local delivery of drugs. Major concerns with topical delivery include poor drug absorption and low bioavailability. To improve the bioavailability of topically administered drugs, novel drug delivery systems are being investigated. Nanocarrier delivery systems demonstrate enhanced drug permeation and prolonged drug release. This review provides an overview of ocular barriers to anterior segment delivery, along with ways to overcome these barriers using nanocarrier systems. The disposition of nanocarriers following topical administration, their safety, toxicity and clinical trials involving nanocarrier systems are also discussed. PMID:29495528
Overview of recent developments in attenuation models

International Nuclear Information System (INIS)

Riera, J.D.

2001-01-01

Attenuation equations predict features of the seismic motion, such as the horizontal and vertical peak ground accelerations (PGA), the peak ground velocities (PGV) and the 5% damped spectral acceleration response (SA), in terms of the earthquake magnitude and distance from source to site. Occasionally other factors, like the type of faulting, are considered in the attenuation expressions. An overview of recent developments in this field is presented in the paper, including a discussion of the applicability of various models for short source to site distances. In such a case, i.e. in the neighbourhood of the epicentral region, which is of utmost importance in Nuclear Power Plant applications, the use of two parameters to define the earthquake size is suggested, instead of the single parameter, a magnitude scale. Recent evidence of the importance in such situations of so-called directivity effects, which require a more complete description of the focal mechanism, completes the paper. (author)
A joint model of word segmentation and meaning acquisition through cross-situational learning.

Science.gov (United States)

Räsänen, Okko; Rasilo, Heikki

2015-10-01

Human infants learn meanings for spoken words in complex interactions with other people, but the exact learning mechanisms are unknown. Among researchers, a widely studied learning mechanism is called cross-situational learning (XSL). In XSL, word meanings are learned when learners accumulate statistical information between spoken words and co-occurring objects or events, allowing the learner to overcome referential uncertainty after having sufficient experience with individually ambiguous scenarios. Existing models in this area have mainly assumed that the learner is capable of segmenting words from speech before grounding them to their referential meaning, while segmentation itself has been treated relatively independently of the meaning acquisition. In this article, we argue that XSL is not just a mechanism for word-to-meaning mapping, but that it provides strong cues for proto-lexical word segmentation. If a learner directly solves the correspondence problem between continuous speech input and the contextual referents being talked about, segmentation of the input into word-like units emerges as a by-product of the learning. We present a theoretical model for joint acquisition of proto-lexical segments and their meanings without assuming a priori knowledge of the language. We also investigate the behavior of the model using a computational implementation, making use of transition probability-based statistical learning. Results from simulations show that the model is not only capable of replicating behavioral data on word learning in artificial languages, but also shows effective learning of word segments and their meanings from continuous speech. Moreover, when augmented with a simple familiarity preference during learning, the model shows a good fit to human behavioral data in XSL tasks. These results support the idea of simultaneous segmentation and meaning acquisition and show that comprehensive models of early word segmentation should take referential word
The vertebrate Hox gene regulatory network for hindbrain segmentation: Evolution and diversification: Coupling of a Hox gene regulatory network to hindbrain segmentation is an ancient trait originating at the base of vertebrates.

Science.gov (United States)

Parker, Hugo J; Bronner, Marianne E; Krumlauf, Robb

2016-06-01

Hindbrain development is orchestrated by a vertebrate gene regulatory network that generates segmental patterning along the anterior-posterior axis via Hox genes. Here, we review analyses of vertebrate and invertebrate chordate models that inform upon the evolutionary origin and diversification of this network. Evidence from the sea lamprey reveals that the hindbrain regulatory network generates rhombomeric compartments with segmental Hox expression and an underlying Hox code. We infer that this basal feature was present in ancestral vertebrates and, as an evolutionarily constrained developmental state, is fundamentally important for patterning of the vertebrate hindbrain across diverse lineages. Despite the common ground plan, vertebrates exhibit neuroanatomical diversity in lineage-specific patterns, with different vertebrates revealing variations of Hox expression in the hindbrain that could underlie this diversification. Invertebrate chordates lack hindbrain segmentation but exhibit some conserved aspects of this network, with retinoic acid signaling playing a role in establishing nested domains of Hox expression. © 2016 WILEY Periodicals, Inc.
Simulation of spatially varying ground motions including incoherence, wave‐passage and differential site‐response effects

DEFF Research Database (Denmark)

Konakli, Katerina; Der Kiureghian, Armen

2012-01-01

A method is presented for simulating arrays of spatially varying ground motions, incorporating the effects of incoherence, wave passage, and differential site response. Non‐stationarity is accounted for by considering the motions as consisting of stationary segments. Two approaches are developed....
Automatic Melody Segmentation

NARCIS (Netherlands)

Rodríguez López, Marcelo

2016-01-01

The work presented in this dissertation investigates music segmentation. In the field of Musicology, segmentation refers to a score analysis technique, whereby notated pieces or passages of these pieces are divided into “units” referred to as sections, periods, phrases, and so on. Segmentation
Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization

Directory of Open Access Journals (Sweden)

Philipp Kainz

2017-10-01

Full Text Available Segmentation of histopathology sections is a necessary preprocessing step for digital pathology. Due to the large variability of biological tissue, machine learning techniques have shown superior performance over conventional image processing methods. Here we present our deep neural network-based approach for segmentation and classification of glands in tissue of benign and malignant colorectal cancer, which was developed to participate in the GlaS@MICCAI2015 colon gland segmentation challenge. We use two distinct deep convolutional neural networks (CNN for pixel-wise classification of Hematoxylin-Eosin stained images. While the first classifier separates glands from background, the second classifier identifies gland-separating structures. In a subsequent step, a figure-ground segmentation based on weighted total variation produces the final segmentation result by regularizing the CNN predictions. We present both quantitative and qualitative segmentation results on the recently released and publicly available Warwick-QU colon adenocarcinoma dataset associated with the GlaS@MICCAI2015 challenge and compare our approach to the simultaneously developed other approaches that participated in the same challenge. On two test sets, we demonstrate our segmentation performance and show that we achieve a tissue classification accuracy of 98% and 95%, making use of the inherent capability of our system to distinguish between benign and malignant tissue. Our results show that deep learning approaches can yield highly accurate and reproducible results for biomedical image analysis, with the potential to significantly improve the quality and speed of medical diagnoses.
Design and validation of Segment - freely available software for cardiovascular image analysis

International Nuclear Information System (INIS)

Heiberg, Einar; Sjögren, Jane; Ugander, Martin; Carlsson, Marcus; Engblom, Henrik; Arheden, Håkan

2010-01-01

Commercially available software for cardiovascular image analysis often has limited functionality and frequently lacks the careful validation that is required for clinical studies. We have already implemented a cardiovascular image analysis software package and released it as freeware for the research community. However, it was distributed as a stand-alone application and other researchers could not extend it by writing their own custom image analysis algorithms. We believe that the work required to make a clinically applicable prototype can be reduced by making the software extensible, so that researchers can develop their own modules or improvements. Such an initiative might then serve as a bridge between image analysis research and cardiovascular research. The aim of this article is therefore to present the design and validation of a cardiovascular image analysis software package (Segment) and to announce its release in a source code format. Segment can be used for image analysis in magnetic resonance imaging (MRI), computed tomography (CT), single photon emission computed tomography (SPECT) and positron emission tomography (PET). Some of its main features include loading of DICOM images from all major scanner vendors, simultaneous display of multiple image stacks and plane intersections, automated segmentation of the left ventricle, quantification of MRI flow, tools for manual and general object segmentation, quantitative regional wall motion analysis, myocardial viability analysis and image fusion tools. Here we present an overview of the validation results and validation procedures for the functionality of the software. We describe a technique to ensure continued accuracy and validity of the software by implementing and using a test script that tests the functionality of the software and validates the output. The software has been made freely available for research purposes in a source code format on the project home page (http://segment.heiberg.se). Segment
A comparative study of automatic image segmentation algorithms for target tracking in MR‐IGRT

Science.gov (United States)

Feng, Yuan; Kawrakow, Iwan; Olsen, Jeff; Parikh, Parag J.; Noel, Camille; Wooten, Omar; Du, Dongsu; Mutic, Sasa

2016-01-01

On‐board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real‐time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames per second) acquired using a MR image‐guided radiotherapy (MR‐IGRT) system. Manual contours of the kidney, bladder, duodenum, and a liver tumor by an experienced radiation oncologist were used as the ground truth for performance evaluation. Besides the manual segmentation, images were automatically segmented using thresholding, fuzzy k‐means (FKM), k‐harmonic means (KHM), and reaction‐diffusion level set evolution (RD‐LSE) algorithms, as well as the tissue tracking algorithm provided by the ViewRay treatment planning and delivery system (VR‐TPDS). The performance of the five algorithms was evaluated quantitatively by comparing with the manual segmentation using the Dice coefficient and target registration error (TRE) measured as the distance between the centroid of the manual ROI and the centroid of the automatically segmented ROI. All methods were able to successfully segment the bladder and the kidney, but only FKM, KHM, and VR‐TPDS were able to segment the liver tumor and the duodenum. The performance of the thresholding, FKM, KHM, and RD‐LSE algorithms degraded as the local image contrast decreased, whereas the performance of the VP‐TPDS method was nearly independent of local image contrast due to the reference registration algorithm. For segmenting high‐contrast images (i.e., kidney), the thresholding method provided the best speed (<1 ms) with a satisfying accuracy (Dice=0.95). When the image contrast was low, the VR‐TPDS method had the best automatic contour. Results suggest an image quality determination procedure before segmentation and
A comparative study of automatic image segmentation algorithms for target tracking in MR-IGRT.

Science.gov (United States)

Feng, Yuan; Kawrakow, Iwan; Olsen, Jeff; Parikh, Parag J; Noel, Camille; Wooten, Omar; Du, Dongsu; Mutic, Sasa; Hu, Yanle

2016-03-01

On-board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real-time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames per second) acquired using a MR image-guided radiotherapy (MR-IGRT) system. Manual contours of the kidney, bladder, duodenum, and a liver tumor by an experienced radiation oncologist were used as the ground truth for performance evaluation. Besides the manual segmentation, images were automatically segmented using thresholding, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE) algorithms, as well as the tissue tracking algorithm provided by the ViewRay treatment planning and delivery system (VR-TPDS). The performance of the five algorithms was evaluated quantitatively by comparing with the manual segmentation using the Dice coefficient and target registration error (TRE) measured as the distance between the centroid of the manual ROI and the centroid of the automatically segmented ROI. All methods were able to successfully segment the bladder and the kidney, but only FKM, KHM, and VR-TPDS were able to segment the liver tumor and the duodenum. The performance of the thresholding, FKM, KHM, and RD-LSE algorithms degraded as the local image contrast decreased, whereas the performance of the VP-TPDS method was nearly independent of local image contrast due to the reference registration algorithm. For segmenting high-contrast images (i.e., kidney), the thresholding method provided the best speed (<1 ms) with a satisfying accuracy (Dice=0.95). When the image contrast was low, the VR-TPDS method had the best automatic contour. Results suggest an image quality determination procedure before segmentation and a combination of different
Segmented trapped vortex cavity

Science.gov (United States)

Grammel, Jr., Leonard Paul (Inventor); Pennekamp, David Lance (Inventor); Winslow, Jr., Ralph Henry (Inventor)

2010-01-01

An annular trapped vortex cavity assembly segment comprising includes a cavity forward wall, a cavity aft wall, and a cavity radially outer wall there between defining a cavity segment therein. A cavity opening extends between the forward and aft walls at a radially inner end of the assembly segment. Radially spaced apart pluralities of air injection first and second holes extend through the forward and aft walls respectively. The segment may include first and second expansion joint features at distal first and second ends respectively of the segment. The segment may include a forward subcomponent including the cavity forward wall attached to an aft subcomponent including the cavity aft wall. The forward and aft subcomponents include forward and aft portions of the cavity radially outer wall respectively. A ring of the segments may be circumferentially disposed about an axis to form an annular segmented vortex cavity assembly.
Performance Analysis of Segmentation of Hyperspectral Images Based on Color Image Segmentation

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Praveen Agarwal

2017-06-01

Full Text Available Image segmentation is a fundamental approach in the field of image processing and based on user’s application .This paper propose an original and simple segmentation strategy based on the EM approach that resolves many informatics problems about hyperspectral images which are observed by airborne sensors. In a first step, to simplify the input color textured image into a color image without texture. The final segmentation is simply achieved by a spatially color segmentation using feature vector with the set of color values contained around the pixel to be classified with some mathematical equations. The spatial constraint allows taking into account the inherent spatial relationships of any image and its color. This approach provides effective PSNR for the segmented image. These results have the better performance as the segmented images are compared with Watershed & Region Growing Algorithm and provide effective segmentation for the Spectral Images & Medical Images.
Leading Players of the Global Oil and Gas Industry. Overview of Groups - SWOTs - Benchmarking - Company Profiles and Financials

International Nuclear Information System (INIS)

2017-07-01

This study presents: The medium-term and mega trends of the industry market developments and geographical segments; The competitive landscape and the main corporate rankings; The main conclusions of the report, summarised in 10 analytical slides. Content: 1. Overview: The Sector, Ranking, Performance Analysis; 2. Company Profiles: Sinopec, PetroChina, Shell, ExxonMobil, BP, Total, Chevron, Gazprom, Lukoil, Eni; 3. Sources; 4. Annexes
Pacifist approaches to conflict resolution: an overview of the principled pacifism

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Oliveira, Gilberto Carvalho de

2017-05-01

Full Text Available This article explores pacifist approaches to conflict resolution based on principles, justifying the pacifist standard grounded in actors' belief systems (spiritual and ethical principles. This article gives a brief overview of the history of the main traditions that shape the debate on pacifism and non-violence, highlighting the central references of principled pacifism (Mahatma Ghandi and Martin Luther King and its main techniques and methods of conflict resolution.
Leading Players of the Global Petrochemical Industry. Overview of Groups - SWOTs - Benchmarking - Company Profiles and Financials

International Nuclear Information System (INIS)

2017-02-01

This study presents: The medium-term and mega trends of the industry market developments and geographical segments; The competitive landscape and the main corporate rankings; The main conclusions of the report, summarised in 10 analytical slides. Content: 1. Overview: The Sector, Ranking, Performance Analysis; 2. Company Profiles: ExxonMobil, Total, BASF, Dow Chemical, Reliance Industries, Sabic, LyondellBasell, Mitsubishi Chemical, LG Chem, Sumitomo Chemical; 3. Sources; 4. Annexes
Status of advanced ground-based laser interferometers for gravitational-wave detection

International Nuclear Information System (INIS)

Dooley, K L; Akutsu, T; Dwyer, S; Puppo, P

2015-01-01

Ground-based laser interferometers for gravitational-wave (GW) detection were first constructed starting 20 years ago and as of 2010 collection of several years’ worth of science data at initial design sensitivities was completed. Upgrades to the initial detectors together with construction of brand new detectors are ongoing and feature advanced technologies to improve the sensitivity to GWs. This conference proceeding provides an overview of the common design features of ground-based laser interferometric GW detectors and establishes the context for the status updates of each of the four gravitational-wave detectors around the world: Advanced LIGO, Advanced Virgo, GEO 600 and KAGRA. (paper)
Segmental Vitiligo.

Science.gov (United States)

van Geel, Nanja; Speeckaert, Reinhart

2017-04-01

Segmental vitiligo is characterized by its early onset, rapid stabilization, and unilateral distribution. Recent evidence suggests that segmental and nonsegmental vitiligo could represent variants of the same disease spectrum. Observational studies with respect to its distribution pattern point to a possible role of cutaneous mosaicism, whereas the original stated dermatomal distribution seems to be a misnomer. Although the exact pathogenic mechanism behind the melanocyte destruction is still unknown, increasing evidence has been published on the autoimmune/inflammatory theory of segmental vitiligo. Copyright © 2016 Elsevier Inc. All rights reserved.

Effects of the addition of functional electrical stimulation to ground level gait training with body weight support after chronic stroke.

Science.gov (United States)

Prado-Medeiros, Christiane L; Sousa, Catarina O; Souza, Andréa S; Soares, Márcio R; Barela, Ana M F; Salvini, Tania F

2011-01-01

The addition of functional electrical stimulation (FES) to treadmill gait training with partial body weight support (BWS) has been proposed as a strategy to facilitate gait training in people with hemiparesis. However, there is a lack of studies that evaluate the effectiveness of FES addition on ground level gait training with BWS, which is the most common locomotion surface. To investigate the additional effects of commum peroneal nerve FES combined with gait training and BWS on ground level, on spatial-temporal gait parameters, segmental angles, and motor function. Twelve people with chronic hemiparesis participated in the study. An A1-B-A2 design was applied. A1 and A2 corresponded to ground level gait training using BWS, and B corresponded to the same training with the addition of FES. The assessments were performed using the Modified Ashworth Scale (MAS), Functional Ambulation Category (FAC), Rivermead Motor Assessment (RMA), and filming. The kinematics analyzed variables were mean walking speed of locomotion; step length; stride length, speed and duration; initial and final double support duration; single-limb support duration; swing period; range of motion (ROM), maximum and minimum angles of foot, leg, thigh, and trunk segments. There were not changes between phases for the functional assessment of RMA, for the spatial-temporal gait variables and segmental angles, no changes were observed after the addition of FES. The use of FES on ground level gait training with BWS did not provide additional benefits for all assessed parameters.
Segmental vitiligo with segmental morphea: An autoimmune link?

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Pravesh Yadav

2014-01-01

Full Text Available An 18-year old girl with segmental vitiligo involving the left side of the trunk and left upper limb with segmental morphea involving the right side of trunk and right upper limb without any deeper involvement is illustrated. There was no history of preceding drug intake, vaccination, trauma, radiation therapy, infection, or hormonal therapy. Family history of stable vitiligo in her brother and a history of type II diabetes mellitus in the father were elicited. Screening for autoimmune diseases and antithyroid antibody was negative. An autoimmune link explaining the co-occurrence has been proposed. Cutaneous mosiacism could explain the presence of both the pathologies in a segmental distribution.
Trace organic chemicals contamination in ground water recharge.

Science.gov (United States)

Díaz-Cruz, M Silvia; Barceló, Damià

2008-06-01

Population growth and unpredictable climate changes will pose high demands on water resources in the future. Even at present, surface water is certainly not enough to cope with the water requirement for agricultural, industrial, recreational and drinking purposes. In this context, the usage of ground water has become essential, therefore, their quality and quantity has to be carefully managed. Regarding quantity, artificial recharge can guarantee a sustainable level of ground water, whilst the strict quality control of the waters intended for recharge will minimize contamination of both the ground water and aquifer area. However, all water resources in the planet are threatened by multiple sources of contamination coming from the extended use of chemicals worldwide. In this respect, the environmental occurrence of organic micropollutants such as pesticides, pharmaceuticals, industrial chemicals and their metabolites has experienced fast growing interest. In this paper an overview of the priority and emerging organic micropollutants in the different source waters used for artificial aquifer recharge purposes and in the recovered water is presented. Besides, some considerations regarding fate and removal of such compounds are also addressed.
Market Segmentation in Business Technology Base: The Case of Segmentation of Sparkling

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Valéria Riscarolli

2014-08-01

Full Text Available A common market segmentation premise for products and services rules consumer behavior as the segmentation center piece. Would this be the logic for segmentation used by small technology based companies? In this article we target at determining the principles of market segmentation used by a vitiwinery company, as research object. This company is recognized by its products excellence, either in domestic as well as in the foreign market, among 13 distinct countries. The research method used is a case study, through information from the company’s CEOs and crossed by primary information from observation and formal registries and documents of the company. In this research we look at sparkling wines market segmentation. Main results indicate that the winery studied considers only technological elements as the basis to build a market segment. One may conclude that a market segmentation for this company is based upon technological dominion of sparkling wines production, aligned with a premium-price policy. In the company, directorship believes that as sparkling wines market is still incipient in the country, sparkling wine market segments will form and consolidate after the evolution of consumers tasting preferences, depending on technologies that boost sparkling wines quality.
Detection and Segmentation of Small Trees in the Forest-Tundra Ecotone Using Airborne Laser Scanning

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Marius Hauglin

2016-05-01

Full Text Available Due to expected climate change and increased focus on forests as a potential carbon sink, it is of interest to map and monitor even marginal forests where trees exist close to their tolerance limits, such as small pioneer trees in the forest-tundra ecotone. Such small trees might indicate tree line migrations and expansion of the forests into treeless areas. Airborne laser scanning (ALS has been suggested and tested as a tool for this purpose and in the present study a novel procedure for identification and segmentation of small trees is proposed. The study was carried out in the Rollag municipality in southeastern Norway, where ALS data and field measurements of individual trees were acquired. The point density of the ALS data was eight points per m2, and the field tree heights ranged from 0.04 to 6.3 m, with a mean of 1.4 m. The proposed method is based on an allometric model relating field-measured tree height to crown diameter, and another model relating field-measured tree height to ALS-derived height. These models are calibrated with local field data. Using these simple models, every positive above-ground height derived from the ALS data can be related to a crown diameter, and by assuming a circular crown shape, this crown diameter can be extended to a crown segment. Applying this model to all ALS echoes with a positive above-ground height value yields an initial map of possible circular crown segments. The final crown segments were then derived by applying a set of simple rules to this initial “map” of segments. The resulting segments were validated by comparison with field-measured crown segments. Overall, 46% of the field-measured trees were successfully detected. The detection rate increased with tree size. For trees with height >3 m the detection rate was 80%. The relatively large detection errors were partly due to the inherent limitations in the ALS data; a substantial fraction of the smaller trees was hit by no or just a few
Fluence map segmentation

International Nuclear Information System (INIS)

Rosenwald, J.-C.

2008-01-01

The lecture addressed the following topics: 'Interpreting' the fluence map; The sequencer; Reasons for difference between desired and actual fluence map; Principle of 'Step and Shoot' segmentation; Large number of solutions for given fluence map; Optimizing 'step and shoot' segmentation; The interdigitation constraint; Main algorithms; Conclusions on segmentation algorithms (static mode); Optimizing intensity levels and monitor units; Sliding window sequencing; Synchronization to avoid the tongue-and-groove effect; Accounting for physical characteristics of MLC; Importance of corrections for leaf transmission and offset; Accounting for MLC mechanical constraints; The 'complexity' factor; Incorporating the sequencing into optimization algorithm; Data transfer to the treatment machine; Interface between R and V and accelerator; and Conclusions on fluence map segmentation (Segmentation is part of the overall inverse planning procedure; 'Step and Shoot' and 'Dynamic' options are available for most TPS (depending on accelerator model; The segmentation phase tends to come into the optimization loop; The physical characteristics of the MLC have a large influence on final dose distribution; The IMRT plans (MU and relative dose distribution) must be carefully validated). (P.A.)
Strategic market segmentation

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Maričić Branko R.

2015-01-01

Full Text Available Strategic planning of marketing activities is the basis of business success in modern business environment. Customers are not homogenous in their preferences and expectations. Formulating an adequate marketing strategy, focused on realization of company's strategic objectives, requires segmented approach to the market that appreciates differences in expectations and preferences of customers. One of significant activities in strategic planning of marketing activities is market segmentation. Strategic planning imposes a need to plan marketing activities according to strategically important segments on the long term basis. At the same time, there is a need to revise and adapt marketing activities on the short term basis. There are number of criteria based on which market segmentation is performed. The paper will consider effectiveness and efficiency of different market segmentation criteria based on empirical research of customer expectations and preferences. The analysis will include traditional criteria and criteria based on behavioral model. The research implications will be analyzed from the perspective of selection of the most adequate market segmentation criteria in strategic planning of marketing activities.
Why segmentation matters: Experience-driven segmentation errors impair "morpheme" learning.

Science.gov (United States)

Finn, Amy S; Hudson Kam, Carla L

2015-09-01

We ask whether an adult learner's knowledge of their native language impedes statistical learning in a new language beyond just word segmentation (as previously shown). In particular, we examine the impact of native-language word-form phonotactics on learners' ability to segment words into their component morphemes and learn phonologically triggered variation of morphemes. We find that learning is impaired when words and component morphemes are structured to conflict with a learner's native-language phonotactic system, but not when native-language phonotactics do not conflict with morpheme boundaries in the artificial language. A learner's native-language knowledge can therefore have a cascading impact affecting word segmentation and the morphological variation that relies upon proper segmentation. These results show that getting word segmentation right early in learning is deeply important for learning other aspects of language, even those (morphology) that are known to pose a great difficulty for adult language learners. (c) 2015 APA, all rights reserved).
Characterization of Personal Privacy Devices (PPD) radiation pattern impact on the ground and airborne segments of the local area augmentation system (LAAS) at GPS L1 frequency

Science.gov (United States)

Alkhateeb, Abualkair M. Khair

Personal Privacy Devices (PPDs) are radio-frequency transmitters that intentionally transmit in a frequency band used by other devices for the intent purpose of denying service to those devices. These devices have shown the potential to interfere with the ground and air sub-systems of the Local Area Augmentation Systems (LAAS), a GPS-based navigation aids at commercial airports. The Federal Aviation Administration (FAA) is concerned by the potential impact of these devices to GPS navigation aids at airports and has commenced an activity to determine the severity of this threat. In support of this situation, the research in this dissertation has been conducted under (FAA) Cooperative Agreement 2011-G-012, to investigate the impact of these devices on the LAAS. In order to investigate the impact of PPDs Radio Frequency Interference (RFI) on the ground and air sub-systems of the LAAS, the work presented in phase one of this research is intended to characterize the vehicle's impact on the PPD's Effective Isotropic Radiated Power (EIRP). A study was conceived in this research to characterize PPD performance by examining the on-vehicle radiation patterns as a function of vehicle type, jammer type, jammer location inside a vehicle and jammer orientation at each location. Phase two was to characterize the GPS Radiation Pattern on Multipath Limiting Antenna. MLA has to meet stringent requirements for acceptable signal detection and multipath rejection. The ARL-2100 is the most recent MLA antenna proposed to be used in the LAAS ground segment. The ground-based antenna's radiation pattern was modeled. This was achieved via (HFSS) a commercial-off the shelf CAD-based modeling code with a full-wave electromagnetic software simulation package that uses the Finite Element Analysis. Phase three of this work has been conducted to study the characteristics of the GPS Radiation Pattern on Commercial Aircraft. The airborne GPS antenna was modeled and the resulting radiation pattern on
Gestalt Principles for Attention and Segmentation in Natural and Artificial Vision Systems

OpenAIRE

Kootstra, Gert; Bergström, Niklas; Kragic, Danica

2011-01-01

Gestalt psychology studies how the human visual system organizes the complex visual input into unitary elements. In this paper we show how the Gestalt principles for perceptual grouping and for figure-ground segregation can be used in computer vision. A number of studies will be shown that demonstrate the applicability of Gestalt principles for the prediction of human visual attention and for the automatic detection and segmentation of unknown objects by a robotic system. QC 20111115 E...
Locally excitatory, globally inhibitory oscillator networks: theory and application to scene segmentation

Science.gov (United States)

Wang, DeLiang; Terman, David

1995-01-01

A novel class of locally excitatory, globally inhibitory oscillator networks (LEGION) is proposed and investigated analytically and by computer simulation. The model of each oscillator corresponds to a standard relaxation oscillator with two time scales. The network exhibits a mechanism of selective gating, whereby an oscillator jumping up to its active phase rapidly recruits the oscillators stimulated by the same pattern, while preventing other oscillators from jumping up. We show analytically that with the selective gating mechanism the network rapidly achieves both synchronization within blocks of oscillators that are stimulated by connected regions and desynchronization between different blocks. Computer simulations demonstrate LEGION's promising ability for segmenting multiple input patterns in real time. This model lays a physical foundation for the oscillatory correlation theory of feature binding, and may provide an effective computational framework for scene segmentation and figure/ground segregation.
Multivariable Parametric Cost Model for Ground Optical Telescope Assembly

Science.gov (United States)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2005-01-01

A parametric cost model for ground-based telescopes is developed using multivariable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction-limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature are examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e., multi-telescope phased-array systems). Additionally, single variable models Based on aperture diameter are derived.
Multivariable Parametric Cost Model for Ground Optical: Telescope Assembly

Science.gov (United States)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature were examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter were derived.
Research of Obstacle Recognition Technology in Cross-Country Environment for Unmanned Ground Vehicle

Directory of Open Access Journals (Sweden)

Zhao Yibing

2014-01-01

Full Text Available Being aimed at the obstacle recognition problem of unmanned ground vehicles in cross-country environment, this paper uses monocular vision sensor to realize the obstacle recognition of typical obstacles. Firstly, median filtering algorithm is applied during image preprocessing that can eliminate the noise. Secondly, image segmentation method based on the Fisher criterion function is used to segment the region of interest. Then, morphological method is used to process the segmented image, which is preparing for the subsequent analysis. The next step is to extract the color feature S, color feature a and edge feature “verticality” of image are extracted based on the HSI color space, the Lab color space, and two value images. Finally multifeature fusion algorithm based on Bayes classification theory is used for obstacle recognition. Test results show that the algorithm has good robustness and accuracy.
Combining multiple FDG-PET radiotherapy target segmentation methods to reduce the effect of variable performance of individual segmentation methods

Energy Technology Data Exchange (ETDEWEB)

McGurk, Ross J. [Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 (United States); Bowsher, James; Das, Shiva K. [Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Lee, John A [Molecular Imaging and Experimental Radiotherapy Unit, Universite Catholique de Louvain, 1200 Brussels (Belgium)

2013-04-15

Purpose: Many approaches have been proposed to segment high uptake objects in 18F-fluoro-deoxy-glucose positron emission tomography images but none provides consistent performance across the large variety of imaging situations. This study investigates the use of two methods of combining individual segmentation methods to reduce the impact of inconsistent performance of the individual methods: simple majority voting and probabilistic estimation. Methods: The National Electrical Manufacturers Association image quality phantom containing five glass spheres with diameters 13-37 mm and two irregularly shaped volumes (16 and 32 cc) formed by deforming high-density polyethylene bottles in a hot water bath were filled with 18-fluoro-deoxyglucose and iodine contrast agent. Repeated 5-min positron emission tomography (PET) images were acquired at 4:1 and 8:1 object-to-background contrasts for spherical objects and 4.5:1 and 9:1 for irregular objects. Five individual methods were used to segment each object: 40% thresholding, adaptive thresholding, k-means clustering, seeded region-growing, and a gradient based method. Volumes were combined using a majority vote (MJV) or Simultaneous Truth And Performance Level Estimate (STAPLE) method. Accuracy of segmentations relative to CT ground truth volumes were assessed using the Dice similarity coefficient (DSC) and the symmetric mean absolute surface distances (SMASDs). Results: MJV had median DSC values of 0.886 and 0.875; and SMASD of 0.52 and 0.71 mm for spheres and irregular shapes, respectively. STAPLE provided similar results with median DSC of 0.886 and 0.871; and median SMASD of 0.50 and 0.72 mm for spheres and irregular shapes, respectively. STAPLE had significantly higher DSC and lower SMASD values than MJV for spheres (DSC, p < 0.0001; SMASD, p= 0.0101) but MJV had significantly higher DSC and lower SMASD values compared to STAPLE for irregular shapes (DSC, p < 0.0001; SMASD, p= 0.0027). DSC was not significantly
Reversing the attention effect in figure-ground perception.

Science.gov (United States)

Huang, Liqiang; Pashler, Harold

2009-10-01

Human visual perception is sometimes ambiguous, switching between different perceptual structures, and shifts of attention sometimes favor one perceptual structure over another. It has been proposed that, in figure-ground segmentation, attention to certain regions tends to cause those regions to be perceived as closer to the observer. Here, we show that this attention effect can be reversed under certain conditions. To account for these phenomena, we propose an alternative principle: The visual system chooses the interpretation that maximizes simplicity of the attended regions.
SU-E-J-208: Fast and Accurate Auto-Segmentation of Abdominal Organs at Risk for Online Adaptive Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Gupta, V; Wang, Y; Romero, A; Heijmen, B; Hoogeman, M [Erasmus MC Cancer Institute, Rotterdam (Netherlands); Myronenko, A; Jordan, P [Accuray Incorporated, Sunnyvale, United States. (United States)

2014-06-01

Purpose: Various studies have demonstrated that online adaptive radiotherapy by real-time re-optimization of the treatment plan can improve organs-at-risk (OARs) sparing in the abdominal region. Its clinical implementation, however, requires fast and accurate auto-segmentation of OARs in CT scans acquired just before each treatment fraction. Autosegmentation is particularly challenging in the abdominal region due to the frequently observed large deformations. We present a clinical validation of a new auto-segmentation method that uses fully automated non-rigid registration for propagating abdominal OAR contours from planning to daily treatment CT scans. Methods: OARs were manually contoured by an expert panel to obtain ground truth contours for repeat CT scans (3 per patient) of 10 patients. For the non-rigid alignment, we used a new non-rigid registration method that estimates the deformation field by optimizing local normalized correlation coefficient with smoothness regularization. This field was used to propagate planning contours to repeat CTs. To quantify the performance of the auto-segmentation, we compared the propagated and ground truth contours using two widely used metrics- Dice coefficient (Dc) and Hausdorff distance (Hd). The proposed method was benchmarked against translation and rigid alignment based auto-segmentation. Results: For all organs, the auto-segmentation performed better than the baseline (translation) with an average processing time of 15 s per fraction CT. The overall improvements ranged from 2% (heart) to 32% (pancreas) in Dc, and 27% (heart) to 62% (spinal cord) in Hd. For liver, kidneys, gall bladder, stomach, spinal cord and heart, Dc above 0.85 was achieved. Duodenum and pancreas were the most challenging organs with both showing relatively larger spreads and medians of 0.79 and 2.1 mm for Dc and Hd, respectively. Conclusion: Based on the achieved accuracy and computational time we conclude that the investigated auto-segmentation
SU-E-J-208: Fast and Accurate Auto-Segmentation of Abdominal Organs at Risk for Online Adaptive Radiotherapy

International Nuclear Information System (INIS)

Gupta, V; Wang, Y; Romero, A; Heijmen, B; Hoogeman, M; Myronenko, A; Jordan, P

2014-01-01

Purpose: Various studies have demonstrated that online adaptive radiotherapy by real-time re-optimization of the treatment plan can improve organs-at-risk (OARs) sparing in the abdominal region. Its clinical implementation, however, requires fast and accurate auto-segmentation of OARs in CT scans acquired just before each treatment fraction. Autosegmentation is particularly challenging in the abdominal region due to the frequently observed large deformations. We present a clinical validation of a new auto-segmentation method that uses fully automated non-rigid registration for propagating abdominal OAR contours from planning to daily treatment CT scans. Methods: OARs were manually contoured by an expert panel to obtain ground truth contours for repeat CT scans (3 per patient) of 10 patients. For the non-rigid alignment, we used a new non-rigid registration method that estimates the deformation field by optimizing local normalized correlation coefficient with smoothness regularization. This field was used to propagate planning contours to repeat CTs. To quantify the performance of the auto-segmentation, we compared the propagated and ground truth contours using two widely used metrics- Dice coefficient (Dc) and Hausdorff distance (Hd). The proposed method was benchmarked against translation and rigid alignment based auto-segmentation. Results: For all organs, the auto-segmentation performed better than the baseline (translation) with an average processing time of 15 s per fraction CT. The overall improvements ranged from 2% (heart) to 32% (pancreas) in Dc, and 27% (heart) to 62% (spinal cord) in Hd. For liver, kidneys, gall bladder, stomach, spinal cord and heart, Dc above 0.85 was achieved. Duodenum and pancreas were the most challenging organs with both showing relatively larger spreads and medians of 0.79 and 2.1 mm for Dc and Hd, respectively. Conclusion: Based on the achieved accuracy and computational time we conclude that the investigated auto-segmentation
Leading Players of the European Power and Gas Industry Overview of Groups - SWOTs - Benchmarking - Company Profiles and Financials

International Nuclear Information System (INIS)

2017-09-01

This study presents: The medium-term and mega trends of the industry market developments and geographical segments; The competitive landscape and the main corporate rankings; The main conclusions of the report, summarised in 10 analytical slides. Content: 1. Overview: The Sector, Ranking, Performance Analysis; 2. Company Profiles: EDF, Enel, Engie, RWE, E.ON, SSE, Iberdrola, Gas Natural Fenosa, Vattenfall, EDP; 3. Sources; 4. Annexes
Comparison of manual and automatic segmentation methods for brain structures in the presence of space-occupying lesions: a multi-expert study

International Nuclear Information System (INIS)

Deeley, M A; Cmelak, A J; Malcolm, A W; Moretti, L; Jaboin, J; Niermann, K; Yang, Eddy S; Yu, David S; Ding, G X; Chen, A; Datteri, R; Noble, J H; Dawant, B M; Donnelly, E F; Yei, F; Koyama, T

2011-01-01

The purpose of this work was to characterize expert variation in segmentation of intracranial structures pertinent to radiation therapy, and to assess a registration-driven atlas-based segmentation algorithm in that context. Eight experts were recruited to segment the brainstem, optic chiasm, optic nerves, and eyes, of 20 patients who underwent therapy for large space-occupying tumors. Performance variability was assessed through three geometric measures: volume, Dice similarity coefficient, and Euclidean distance. In addition, two simulated ground truth segmentations were calculated via the simultaneous truth and performance level estimation algorithm and a novel application of probability maps. The experts and automatic system were found to generate structures of similar volume, though the experts exhibited higher variation with respect to tubular structures. No difference was found between the mean Dice similarity coefficient (DSC) of the automatic and expert delineations as a group at a 5% significance level over all cases and organs. The larger structures of the brainstem and eyes exhibited mean DSC of approximately 0.8-0.9, whereas the tubular chiasm and nerves were lower, approximately 0.4-0.5. Similarly low DSCs have been reported previously without the context of several experts and patient volumes. This study, however, provides evidence that experts are similarly challenged. The average maximum distances (maximum inside, maximum outside) from a simulated ground truth ranged from (-4.3, +5.4) mm for the automatic system to (-3.9, +7.5) mm for the experts considered as a group. Over all the structures in a rank of true positive rates at a 2 mm threshold from the simulated ground truth, the automatic system ranked second of the nine raters. This work underscores the need for large scale studies utilizing statistically robust numbers of patients and experts in evaluating quality of automatic algorithms.

Implications of ground water chemistry and flow patterns for earthquake studies.

Science.gov (United States)

Guangcai, Wang; Zuochen, Zhang; Min, Wang; Cravotta, Charles A; Chenglong, Liu

2005-01-01

Ground water can facilitate earthquake development and respond physically and chemically to tectonism. Thus, an understanding of ground water circulation in seismically active regions is important for earthquake prediction. To investigate the roles of ground water in the development and prediction of earthquakes, geological and hydrogeological monitoring was conducted in a seismogenic area in the Yanhuai Basin, China. This study used isotopic and hydrogeochemical methods to characterize ground water samples from six hot springs and two cold springs. The hydrochemical data and associated geological and geophysical data were used to identify possible relations between ground water circulation and seismically active structural features. The data for delta18O, deltaD, tritium, and 14C indicate ground water from hot springs is of meteoric origin with subsurface residence times of 50 to 30,320 years. The reservoir temperature and circulation depths of the hot ground water are 57 degrees C to 160 degrees C and 1600 to 5000 m, respectively, as estimated by quartz and chalcedony geothermometers and the geothermal gradient. Various possible origins of noble gases dissolved in the ground water also were evaluated, indicating mantle and deep crust sources consistent with tectonically active segments. A hard intercalated stratum, where small to moderate earthquakes frequently originate, is present between a deep (10 to 20 km), high-electrical conductivity layer and the zone of active ground water circulation. The ground water anomalies are closely related to the structural peculiarity of each monitoring point. These results could have implications for ground water and seismic studies in other seismogenic areas.
Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late Gadolinium enhancement MR images.

Science.gov (United States)

Karim, Rashed; Bhagirath, Pranav; Claus, Piet; James Housden, R; Chen, Zhong; Karimaghaloo, Zahra; Sohn, Hyon-Mok; Lara Rodríguez, Laura; Vera, Sergio; Albà, Xènia; Hennemuth, Anja; Peitgen, Heinz-Otto; Arbel, Tal; Gonzàlez Ballester, Miguel A; Frangi, Alejandro F; Götte, Marco; Razavi, Reza; Schaeffter, Tobias; Rhode, Kawal

2016-05-01

Studies have demonstrated the feasibility of late Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging for guiding the management of patients with sequelae to myocardial infarction, such as ventricular tachycardia and heart failure. Clinical implementation of these developments necessitates a reproducible and reliable segmentation of the infarcted regions. It is challenging to compare new algorithms for infarct segmentation in the left ventricle (LV) with existing algorithms. Benchmarking datasets with evaluation strategies are much needed to facilitate comparison. This manuscript presents a benchmarking evaluation framework for future algorithms that segment infarct from LGE CMR of the LV. The image database consists of 30 LGE CMR images of both humans and pigs that were acquired from two separate imaging centres. A consensus ground truth was obtained for all data using maximum likelihood estimation. Six widely-used fixed-thresholding methods and five recently developed algorithms are tested on the benchmarking framework. Results demonstrate that the algorithms have better overlap with the consensus ground truth than most of the n-SD fixed-thresholding methods, with the exception of the Full-Width-at-Half-Maximum (FWHM) fixed-thresholding method. Some of the pitfalls of fixed thresholding methods are demonstrated in this work. The benchmarking evaluation framework, which is a contribution of this work, can be used to test and benchmark future algorithms that detect and quantify infarct in LGE CMR images of the LV. The datasets, ground truth and evaluation code have been made publicly available through the website: https://www.cardiacatlas.org/web/guest/challenges. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Characterization of porosity in a 19th century painting ground by synchrotron radiation X-ray tomography

Energy Technology Data Exchange (ETDEWEB)

Gervais, Claire [Swiss Institute for Art Research (SIK-ISEA), Zuerich (Switzerland); Bern University of the Arts, Bern (Switzerland); Boon, Jaap J. [Swiss Institute for Art Research (SIK-ISEA), Zuerich (Switzerland); JAAP Enterprise for MOLART Advice, Amsterdam (Netherlands); Marone, Federica [Paul Scherrer Institute, Swiss Light Source (SLS), Villigen (Switzerland); Ferreira, Ester S.B. [Swiss Institute for Art Research (SIK-ISEA), Zuerich (Switzerland)

2013-04-15

The study of the early oeuvre of the Swiss painter Cuno Amiet (1868-1961) has revealed that, up to 1907, many of his grounds were hand applied and are mainly composed of chalk, bound in protein. These grounds are not only lean and absorbent, but also, as Synchrotron radiation X-ray microtomography has shown, porous. Our approach to the characterization of pore structure and quantity, their connectivity, and homogeneity is based on image segmentation and application of a clustering algorithm to high-resolution X-ray tomographic data. The issues associated with the segmentation of the different components of a ground sample based on X-ray imaging data are discussed. The approach applied to a sample taken from ''Portrait of Max Leu'' (1899) by Amiet revealed the presence of three sublayers within the ground with distinct porosity features, which had not been observed optically in cross-section. The upper and lower layers are highly porous with important connectivity and thus prone to water uptake/storage. The middle layer however shows low and nonconnected porosity at the resolution level of the X-ray tomography images, so that few direct water absorption paths through the entire sample exist. The potential of the method to characterize porosity and to understand moisture-related issues in paint layer degradation are discussed. (orig.)
Characterization of porosity in a 19th century painting ground by synchrotron radiation X-ray tomography

International Nuclear Information System (INIS)

Gervais, Claire; Boon, Jaap J.; Marone, Federica; Ferreira, Ester S.B.

2013-01-01

The study of the early oeuvre of the Swiss painter Cuno Amiet (1868-1961) has revealed that, up to 1907, many of his grounds were hand applied and are mainly composed of chalk, bound in protein. These grounds are not only lean and absorbent, but also, as Synchrotron radiation X-ray microtomography has shown, porous. Our approach to the characterization of pore structure and quantity, their connectivity, and homogeneity is based on image segmentation and application of a clustering algorithm to high-resolution X-ray tomographic data. The issues associated with the segmentation of the different components of a ground sample based on X-ray imaging data are discussed. The approach applied to a sample taken from ''Portrait of Max Leu'' (1899) by Amiet revealed the presence of three sublayers within the ground with distinct porosity features, which had not been observed optically in cross-section. The upper and lower layers are highly porous with important connectivity and thus prone to water uptake/storage. The middle layer however shows low and nonconnected porosity at the resolution level of the X-ray tomography images, so that few direct water absorption paths through the entire sample exist. The potential of the method to characterize porosity and to understand moisture-related issues in paint layer degradation are discussed. (orig.)
Deformable meshes for medical image segmentation accurate automatic segmentation of anatomical structures

CERN Document Server

Kainmueller, Dagmar

2014-01-01

? Segmentation of anatomical structures in medical image data is an essential task in clinical practice. Dagmar Kainmueller introduces methods for accurate fully automatic segmentation of anatomical structures in 3D medical image data. The author's core methodological contribution is a novel deformation model that overcomes limitations of state-of-the-art Deformable Surface approaches, hence allowing for accurate segmentation of tip- and ridge-shaped features of anatomical structures. As for practical contributions, she proposes application-specific segmentation pipelines for a range of anatom
Stacking denoising auto-encoders in a deep network to segment the brainstem on MRI in brain cancer patients: A clinical study.

Science.gov (United States)

Dolz, Jose; Betrouni, Nacim; Quidet, Mathilde; Kharroubi, Dris; Leroy, Henri A; Reyns, Nicolas; Massoptier, Laurent; Vermandel, Maximilien

2016-09-01

Delineation of organs at risk (OARs) is a crucial step in surgical and treatment planning in brain cancer, where precise OARs volume delineation is required. However, this task is still often manually performed, which is time-consuming and prone to observer variability. To tackle these issues a deep learning approach based on stacking denoising auto-encoders has been proposed to segment the brainstem on magnetic resonance images in brain cancer context. Additionally to classical features used in machine learning to segment brain structures, two new features are suggested. Four experts participated in this study by segmenting the brainstem on 9 patients who underwent radiosurgery. Analysis of variance on shape and volume similarity metrics indicated that there were significant differences (p<0.05) between the groups of manual annotations and automatic segmentations. Experimental evaluation also showed an overlapping higher than 90% with respect to the ground truth. These results are comparable, and often higher, to those of the state of the art segmentation methods but with a considerably reduction of the segmentation time. Copyright © 2016 Elsevier Ltd. All rights reserved.
Structural and functional intermetallics - an overview

International Nuclear Information System (INIS)

Varin, R.A.

2000-01-01

This overview presents the current status of the research and development of both structural and functional intermetallics. On the one hand, the discussion is focused on commercialization and existing industrial applications of intermetallics. Within this frame the applications of titanium aluminides (TiAl) for turbocharger rotors and exhaust valves in automotive industry are being discussed. Advances in the applications of TiAl alloys for the next generation of turbine blades in aerospace/aircraft segment are also presented. The entire spectrum of nickel and iron aluminide alloys developed commercially by the Oak Ridge national Laboratory (USA) and the examples of their application in various segments of industry are thoroughly discussed. Some inroads made in the application of directionally solidified (DS) multiphase niobium silicides (Nb 3 Si+Nb 5 Si 3 ) in situ intermetallic composites with the goal of pushing the service temperature envelope of turbine blades to ∼ 1200-1300 o C are also discussed. On the other hand, various topics in basic or curiosity driven research of titanium aluminides and trialuminides, iron aluminides and high temperature structural silicides are discussed. Some very recent findings on the improvements in fracture toughness and strength of titanium trialuminides and magnetic behaviour of unconventionally cold - worked iron aluminides are highlighted. The topic of functional intermetallics is limited to the systems must suitable for hydrogen storage applications. A perspective on the directions of future research and development of intermetallics is also provided. (author)
The ventral nerve cord in Cephalocarida (Crustacea): new insights into the ground pattern of Tetraconata.

Science.gov (United States)

Stegner, Martin E J; Brenneis, Georg; Richter, Stefan

2014-03-01

Cephalocarida are Crustacea with many anatomical features that have been interpreted as plesiomorphic with respect to crustaceans or Tetraconata. While the ventral nerve cord (VNC) has been investigated in many other arthropods to address phylogenetic and evolutionary questions, the few studies that exist on the cephalocarid VNC date back 20 years, and data pertaining to neuroactive substances in particular are too sparse for comparison. We reinvestigated the VNC of adult Hutchinsoniella macracantha in detail, combining immunolabeling (tubulin, serotonin, RFamide, histamine) and nuclear stains with confocal laser microscopy, complemented by 3D-reconstructions based on serial semithin sections. The subesophageal ganglion in Cephalocarida comprises three segmental neuromeres (Md, Mx1, Mx2), while a separate ganglion occurs in all thoracic segments and abdominal segments 1-8. Abdominal segments 9 and 10 and the telson are free of ganglia. The maxillar neuromere and the thoracic ganglia correspond closely in their limb innervation pattern, their pattern of mostly four segmental commissures and in displaying up to six individually identified serotonin-like immunoreactive neurons per body side, which exceeds the number found in most other tetraconates. Only two commissures and two serotonin-like immunoreactive neurons per side are present in abdominal ganglia. The stomatogastric nervous system in H. macracantha corresponds to that in other crustaceans and includes, among other structures, a pair of lateral neurite bundles. These innervate the gut as well as various trunk muscles and are, uniquely, linked to the unpaired median neurite bundle. We propose that most features of the cephalocarid ventral nerve cord (VNC) are plesiomorphic with respect to the tetraconate ground pattern. Further, we suggest that this ground pattern includes more serotonin-like neurons than hitherto assumed, and argue that a sister-group relationship between Cephalocarida and Remipedia, as
Speaker segmentation and clustering

OpenAIRE

Kotti, M; Moschou, V; Kotropoulos, C

2008-01-01

07.08.13 KB. Ok to add the accepted version to Spiral, Elsevier says ok whlile mandate not enforced. This survey focuses on two challenging speech processing topics, namely: speaker segmentation and speaker clustering. Speaker segmentation aims at finding speaker change points in an audio stream, whereas speaker clustering aims at grouping speech segments based on speaker characteristics. Model-based, metric-based, and hybrid speaker segmentation algorithms are reviewed. Concerning speaker...
Preliminary Results on Earthquake Recurrence Intervals, Rupture Segmentation, and Potential Earthquake Moment Magnitudes along the Tahoe-Sierra Frontal Fault Zone, Lake Tahoe, California

Science.gov (United States)

Howle, J.; Bawden, G. W.; Schweickert, R. A.; Hunter, L. E.; Rose, R.

2012-12-01

Utilizing high-resolution bare-earth LiDAR topography, field observations, and earlier results of Howle et al. (2012), we estimate latest Pleistocene/Holocene earthquake-recurrence intervals, propose scenarios for earthquake-rupture segmentation, and estimate potential earthquake moment magnitudes for the Tahoe-Sierra frontal fault zone (TSFFZ), west of Lake Tahoe, California. We have developed a new technique to estimate the vertical separation for the most recent and the previous ground-rupturing earthquakes at five sites along the Echo Peak and Mt. Tallac segments of the TSFFZ. At these sites are fault scarps with two bevels separated by an inflection point (compound fault scarps), indicating that the cumulative vertical separation (VS) across the scarp resulted from two events. This technique, modified from the modeling methods of Howle et al. (2012), uses the far-field plunge of the best-fit footwall vector and the fault-scarp morphology from high-resolution LiDAR profiles to estimate the per-event VS. From this data, we conclude that the adjacent and overlapping Echo Peak and Mt. Tallac segments have ruptured coseismically twice during the Holocene. The right-stepping, en echelon range-front segments of the TSFFZ show progressively greater VS rates and shorter earthquake-recurrence intervals from southeast to northwest. Our preliminary estimates suggest latest Pleistocene/ Holocene earthquake-recurrence intervals of 4.8±0.9x103 years for a coseismic rupture of the Echo Peak and Mt. Tallac segments, located at the southeastern end of the TSFFZ. For the Rubicon Peak segment, northwest of the Echo Peak and Mt. Tallac segments, our preliminary estimate of the maximum earthquake-recurrence interval is 2.8±1.0x103 years, based on data from two sites. The correspondence between high VS rates and short recurrence intervals suggests that earthquake sequences along the TSFFZ may initiate in the northwest part of the zone and then occur to the southeast with a lower
Segmentation of the Infant Food Market

OpenAIRE

Hrůzová, Daniela

2015-01-01

The theoretical part covers general market segmentation, namely the marketing importance of differences among consumers, the essence of market segmentation, its main conditions and the process of segmentation, which consists of four consecutive phases - defining the market, determining important criteria, uncovering segments and developing segment profiles. The segmentation criteria, segmentation approaches, methods and techniques for the process of market segmentation are also described in t...
Pancreas and cyst segmentation

Science.gov (United States)

Dmitriev, Konstantin; Gutenko, Ievgeniia; Nadeem, Saad; Kaufman, Arie

2016-03-01

Accurate segmentation of abdominal organs from medical images is an essential part of surgical planning and computer-aided disease diagnosis. Many existing algorithms are specialized for the segmentation of healthy organs. Cystic pancreas segmentation is especially challenging due to its low contrast boundaries, variability in shape, location and the stage of the pancreatic cancer. We present a semi-automatic segmentation algorithm for pancreata with cysts. In contrast to existing automatic segmentation approaches for healthy pancreas segmentation which are amenable to atlas/statistical shape approaches, a pancreas with cysts can have even higher variability with respect to the shape of the pancreas due to the size and shape of the cyst(s). Hence, fine results are better attained with semi-automatic steerable approaches. We use a novel combination of random walker and region growing approaches to delineate the boundaries of the pancreas and cysts with respective best Dice coefficients of 85.1% and 86.7%, and respective best volumetric overlap errors of 26.0% and 23.5%. Results show that the proposed algorithm for pancreas and pancreatic cyst segmentation is accurate and stable.
Phasing multi-segment undulators

International Nuclear Information System (INIS)

Chavanne, J.; Elleaume, P.; Vaerenbergh, P. Van

1996-01-01

An important issue in the manufacture of multi-segment undulators as a source of synchrotron radiation or as a free-electron laser (FEL) is the phasing between successive segments. The state of the art is briefly reviewed, after which a novel pure permanent magnet phasing section that is passive and does not require any current is presented. The phasing section allows the introduction of a 6 mm longitudinal gap between each segment, resulting in complete mechanical independence and reduced magnetic interaction between segments. The tolerance of the longitudinal positioning of one segment with respect to the next is found to be 2.8 times lower than that of conventional phasing. The spectrum at all gaps and useful harmonics is almost unchanged when compared with a single-segment undulator of the same total length. (au) 3 refs
FRAMEWORK FOR COMPARING SEGMENTATION ALGORITHMS

Directory of Open Access Journals (Sweden)

G. Sithole

2015-05-01

Full Text Available The notion of a ‘Best’ segmentation does not exist. A segmentation algorithm is chosen based on the features it yields, the properties of the segments (point sets it generates, and the complexity of its algorithm. The segmentation is then assessed based on a variety of metrics such as homogeneity, heterogeneity, fragmentation, etc. Even after an algorithm is chosen its performance is still uncertain because the landscape/scenarios represented in a point cloud have a strong influence on the eventual segmentation. Thus selecting an appropriate segmentation algorithm is a process of trial and error. Automating the selection of segmentation algorithms and their parameters first requires methods to evaluate segmentations. Three common approaches for evaluating segmentation algorithms are ‘goodness methods’, ‘discrepancy methods’ and ‘benchmarks’. Benchmarks are considered the most comprehensive method of evaluation. This paper shortcomings in current benchmark methods are identified and a framework is proposed that permits both a visual and numerical evaluation of segmentations for different algorithms, algorithm parameters and evaluation metrics. The concept of the framework is demonstrated on a real point cloud. Current results are promising and suggest that it can be used to predict the performance of segmentation algorithms.
Why segmentation matters: experience-driven segmentation errors impair “morpheme” learning

Science.gov (United States)

Finn, Amy S.; Hudson Kam, Carla L.

2015-01-01

We ask whether an adult learner’s knowledge of their native language impedes statistical learning in a new language beyond just word segmentation (as previously shown). In particular, we examine the impact of native-language word-form phonotactics on learners’ ability to segment words into their component morphemes and learn phonologically triggered variation of morphemes. We find that learning is impaired when words and component morphemes are structured to conflict with a learner’s native-language phonotactic system, but not when native-language phonotactics do not conflict with morpheme boundaries in the artificial language. A learner’s native-language knowledge can therefore have a cascading impact affecting word segmentation and the morphological variation that relies upon proper segmentation. These results show that getting word segmentation right early in learning is deeply important for learning other aspects of language, even those (morphology) that are known to pose a great difficulty for adult language learners. PMID:25730305
Estimation of foot joint kinetics in three and four segment foot models using an existing proportionality scheme: Application in paediatric barefoot walking.

Science.gov (United States)

Deschamps, Kevin; Eerdekens, Maarten; Desmet, Dirk; Matricali, Giovanni Arnoldo; Wuite, Sander; Staes, Filip

2017-08-16

Recent studies which estimated foot segment kinetic patterns were found to have inconclusive data on one hand, and did not dissociate the kinetics of the chopart and lisfranc joint. The current study aimed therefore at reproducing independent, recently published three-segment foot kinetic data (Study 1) and in a second stage expand the estimation towards a four-segment model (Study 2). Concerning the reproducibility study, two recently published three segment foot models (Bruening et al., 2014; Saraswat et al., 2014) were reproduced and kinetic parameters were incorporated in order to calculate joint moments and powers of paediatric cohorts during gait. Ground reaction forces were measured with an integrated force/pressure plate measurement set-up and a recently published proportionality scheme was applied to determine subarea total ground reaction forces. Regarding Study 2, moments and powers were estimated with respect to the Instituto Ortopedico Rizzoli four-segment model. The proportionality scheme was expanded in this study and the impact of joint centre location on kinetic data was evaluated. Findings related to Study 1 showed in general good agreement with the kinetic data published by Bruening et al. (2014). Contrarily, the peak ankle, midfoot and hallux powers published by Saraswat et al. (2014) are disputed. Findings of Study 2 revealed that the chopart joint encompasses both power absorption and generation, whereas the Lisfranc joint mainly contributes to power generation. The results highlights the necessity for further studies in the field of foot kinetic models and provides a first estimation of the kinetic behaviour of the Lisfranc joint. Copyright © 2017 Elsevier Ltd. All rights reserved.
Segment-Tube: Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation

OpenAIRE

Le Wang; Xuhuan Duan; Qilin Zhang; Zhenxing Niu; Gang Hua; Nanning Zheng

2018-01-01

Inspired by the recent spatio-temporal action localization efforts with tubelets (sequences of bounding boxes), we present a new spatio-temporal action localization detector Segment-tube, which consists of sequences of per-frame segmentation masks. The proposed Segment-tube detector can temporally pinpoint the starting/ending frame of each action category in the presence of preceding/subsequent interference actions in untrimmed videos. Simultaneously, the Segment-tube detector produces per-fr...
Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric Analysis.

Science.gov (United States)

Lee, Hyunkwang; Troschel, Fabian M; Tajmir, Shahein; Fuchs, Georg; Mario, Julia; Fintelmann, Florian J; Do, Synho

2017-08-01

Pretreatment risk stratification is key for personalized medicine. While many physicians rely on an "eyeball test" to assess whether patients will tolerate major surgery or chemotherapy, "eyeballing" is inherently subjective and difficult to quantify. The concept of morphometric age derived from cross-sectional imaging has been found to correlate well with outcomes such as length of stay, morbidity, and mortality. However, the determination of the morphometric age is time intensive and requires highly trained experts. In this study, we propose a fully automated deep learning system for the segmentation of skeletal muscle cross-sectional area (CSA) on an axial computed tomography image taken at the third lumbar vertebra. We utilized a fully automated deep segmentation model derived from an extended implementation of a fully convolutional network with weight initialization of an ImageNet pre-trained model, followed by post processing to eliminate intramuscular fat for a more accurate analysis. This experiment was conducted by varying window level (WL), window width (WW), and bit resolutions in order to better understand the effects of the parameters on the model performance. Our best model, fine-tuned on 250 training images and ground truth labels, achieves 0.93 ± 0.02 Dice similarity coefficient (DSC) and 3.68 ± 2.29% difference between predicted and ground truth muscle CSA on 150 held-out test cases. Ultimately, the fully automated segmentation system can be embedded into the clinical environment to accelerate the quantification of muscle and expanded to volume analysis of 3D datasets.
Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.

Science.gov (United States)

Hu, Peijun; Wu, Fa; Peng, Jialin; Bao, Yuanyuan; Chen, Feng; Kong, Dexing

2017-03-01

Multi-organ segmentation from CT images is an essential step for computer-aided diagnosis and surgery planning. However, manual delineation of the organs by radiologists is tedious, time-consuming and poorly reproducible. Therefore, we propose a fully automatic method for the segmentation of multiple organs from three-dimensional abdominal CT images. The proposed method employs deep fully convolutional neural networks (CNNs) for organ detection and segmentation, which is further refined by a time-implicit multi-phase evolution method. Firstly, a 3D CNN is trained to automatically localize and delineate the organs of interest with a probability prediction map. The learned probability map provides both subject-specific spatial priors and initialization for subsequent fine segmentation. Then, for the refinement of the multi-organ segmentation, image intensity models, probability priors as well as a disjoint region constraint are incorporated into an unified energy functional. Finally, a novel time-implicit multi-phase level-set algorithm is utilized to efficiently optimize the proposed energy functional model. Our method has been evaluated on 140 abdominal CT scans for the segmentation of four organs (liver, spleen and both kidneys). With respect to the ground truth, average Dice overlap ratios for the liver, spleen and both kidneys are 96.0, 94.2 and 95.4%, respectively, and average symmetric surface distance is less than 1.3 mm for all the segmented organs. The computation time for a CT volume is 125 s in average. The achieved accuracy compares well to state-of-the-art methods with much higher efficiency. A fully automatic method for multi-organ segmentation from abdominal CT images was developed and evaluated. The results demonstrated its potential in clinical usage with high effectiveness, robustness and efficiency.
Calculation of Equivalent Resistance for Ground Wires Twined with Armor Rods in Contact Terminals

Directory of Open Access Journals (Sweden)

Gang Liu

2018-03-01

Full Text Available Ground wire breakage accidents can destroy the stable operation of overhead lines. The excessive temperature increase arising from the contact resistance between the ground wire and armor rod in the contact terminal is one of the main reasons causing the breakage of ground wires. Therefore, it is necessary to calculate the equivalent resistance for ground wires twined with armor rods in contact terminals. According to the actual distribution characteristics of the contact points in the contact terminal, a three-dimensional electromagnetic field simulation model of the contact terminal was established. Based on the model, the current distribution in the contact terminal was obtained. Subsequently, the equivalent resistance of a ground wire twined with the armor rod in the contact terminal was calculated. The effects of the factors influencing the equivalent resistance were also discussed. The corresponding verification experiments were conducted on a real ground wire on a contact terminal. The measurement results of the equivalent resistance for the armor rod segment showed good agreement with the electromagnetic modeling results.

Leading Players of the Global Renewable Energy Equipment Industry. Overview of Groups - SWOTs - Benchmarking - Company Profiles and Financials

International Nuclear Information System (INIS)

2017-06-01

This study presents: The medium-term and mega trends of the industry market developments and geographical segments; The competitive landscape and the main corporate rankings; The main conclusions of the report, summarised in 10 analytical slides. Content: 1. Overview: The Sector, Ranking, Performance Analysis; 2. Company Profiles: Toshiba, Vestas, Dong Energy, GE Renewable Energy, Siemens, Goldwind, First Solar, SunPower, Andritz, Yingli Green Energy; 3. Sources; 4. Annexes
Preliminary evaluation of ground-water contamination by coal-tar derivatives, St. Louis Park area, Minnesota

Science.gov (United States)

Hult, Marc F.; Schoenberg, Michael E.

1984-01-01

Operation of a coal-tar distillation and wood-preserving plant from 1918 to 1972 in St. Louis Park, a suburb of Minneapolis, Minn., resulted in ground-water contamination. This preliminary evaluation presents an overview of the problem based on the results of the first year (1979) of an ongoing study.
Secondary Focal Segmental Glomerulosclerosis: From Podocyte Injury to Glomerulosclerosis

Directory of Open Access Journals (Sweden)

Jae Seok Kim

2016-01-01

Full Text Available Focal segmental glomerulosclerosis (FSGS is a common cause of proteinuria and nephrotic syndrome leading to end stage renal disease (ESRD. There are two types of FSGS, primary (idiopathic and secondary forms. Secondary FSGS shows less severe clinical features compared to those of the primary one. However, secondary FSGS has an important clinical significance because a variety of renal diseases progress to ESRD thorough the form of secondary FSGS. The defining feature of FSGS is proteinuria. The key event of FSGS is podocyte injury which is caused by multiple factors. Unanswered questions about how these factors act on podocytes to cause secondary FSGS are various and ill-defined. In this review, we provide brief overview and new insights into FSGS, podocyte injury, and their potential linkage suggesting clues to answer for treatment of the disease.
An overview of surgery-first approach: Recent advances in orthognathic surgery.

Science.gov (United States)

Sharma, Vipul Kumar; Yadav, Kirti; Tandon, Pradeep

2015-01-01

The disadvantages of having orthodontic interventions both before and after orthognathic surgery include a long treatment time of 7-47 months and temporary worsening of facial appearance. Nowadays, the concept of surgery-first, followed by orthodontic treatment is applied to orthognathic surgery cases in different orthodontic centers in the world. This concept and technique is called "surgery-first-orthognathic-approach" or "surgery-first approach" (SFA) rigid fixation (skeletal anchorage system) of the bony segments and regional acceleratory phenomenon were keys to broad implementation of the SFA. This article is intended to provide an overview of SFA including indications, general and specific guidelines, different protocol variations, success rate and potential problems.
Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry

Science.gov (United States)

Meier, Raphael; Knecht, Urspeter; Loosli, Tina; Bauer, Stefan; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio

2016-03-01

Information about the size of a tumor and its temporal evolution is needed for diagnosis as well as treatment of brain tumor patients. The aim of the study was to investigate the potential of a fully-automatic segmentation method, called BraTumIA, for longitudinal brain tumor volumetry by comparing the automatically estimated volumes with ground truth data acquired via manual segmentation. Longitudinal Magnetic Resonance (MR) Imaging data of 14 patients with newly diagnosed glioblastoma encompassing 64 MR acquisitions, ranging from preoperative up to 12 month follow-up images, was analysed. Manual segmentation was performed by two human raters. Strong correlations (R = 0.83-0.96, p < 0.001) were observed between volumetric estimates of BraTumIA and of each of the human raters for the contrast-enhancing (CET) and non-enhancing T2-hyperintense tumor compartments (NCE-T2). A quantitative analysis of the inter-rater disagreement showed that the disagreement between BraTumIA and each of the human raters was comparable to the disagreement between the human raters. In summary, BraTumIA generated volumetric trend curves of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments comparable to estimates of human raters. These findings suggest the potential of automated longitudinal tumor segmentation to substitute manual volumetric follow-up of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments.
Hypersonic Inflatable Aerodynamic Decelerator Ground Test Development

Science.gov (United States)

Del Corso, Jospeh A.; Hughes, Stephen; Cheatwood, Neil; Johnson, Keith; Calomino, Anthony

2015-01-01

Hypersonic Inflatable Aerodynamic Decelerator (HIAD) technology readiness levels have been incrementally matured by NASA over the last thirteen years, with most recent support from NASA's Space Technology Mission Directorate (STMD) Game Changing Development Program (GCDP). Recently STMD GCDP has authorized funding and support through fiscal year 2015 (FY15) for continued HIAD ground developments which support a Mars Entry, Descent, and Landing (EDL) study. The Mars study will assess the viability of various EDL architectures to enable a Mars human architecture pathfinder mission planned for mid-2020. At its conclusion in November 2014, NASA's first HIAD ground development effort had demonstrated success with fabricating a 50 W/cm2 modular thermal protection system, a 400 C capable inflatable structure, a 10-meter scale aeroshell manufacturing capability, together with calibrated thermal and structural models. Despite the unquestionable success of the first HIAD ground development effort, it was recognized that additional investment was needed in order to realize the full potential of the HIAD technology capability to enable future flight opportunities. The second HIAD ground development effort will focus on extending performance capability in key technology areas that include thermal protection system, lifting-body structures, inflation systems, flight control, stage transitions, and 15-meter aeroshell scalability. This paper presents an overview of the accomplishments under the baseline HIAD development effort and current plans for a follow-on development effort focused on extending those critical technologies needed to enable a Mars Pathfinder mission.
Outdoor Illegal Construction Identification Algorithm Based on 3D Point Cloud Segmentation

Science.gov (United States)

An, Lu; Guo, Baolong

2018-03-01

Recently, various illegal constructions occur significantly in our surroundings, which seriously restrict the orderly development of urban modernization. The 3D point cloud data technology is used to identify the illegal buildings, which could address the problem above effectively. This paper proposes an outdoor illegal construction identification algorithm based on 3D point cloud segmentation. Initially, in order to save memory space and reduce processing time, a lossless point cloud compression method based on minimum spanning tree is proposed. Then, a ground point removing method based on the multi-scale filtering is introduced to increase accuracy. Finally, building clusters on the ground can be obtained using a region growing method, as a result, the illegal construction can be marked. The effectiveness of the proposed algorithm is verified using a publicly data set collected from the International Society for Photogrammetry and Remote Sensing (ISPRS).
Arase: mission overview and initial results

Science.gov (United States)

Miyoshi, Y.; Shinohara, I.; Takashima, T.; Asamura, K.; Wang, S. Y.; Kazama, Y.; Kasahara, S.; Yokota, S.; Mitani, T.; Higashio, N.; Kasahara, Y.; Kasaba, Y.; Yagitani, S.; Matsuoka, A.; Kojima, H.; Kazuo, S.; Seki, K.; Hori, T.; Shoji, M.; Teramoto, M.; Chang, T. F.; Kurita, S.; Matsuda, S.; Keika, K.; Miyashita, Y.; Hosokawa, K.; Ogawa, Y.; Kadokura, A.; Kataoka, R.; Ono, T.

2017-12-01

collaboration with other satellites; Van Allen Probes, THEMIS and MMS are realized. In this presentation, we will report overview and initial highlights for the first year and discuss importance of synergies of multi-satellites and ground-based observations that are realized by international collaborations.
Joint shape segmentation with linear programming

KAUST Repository

Huang, Qixing

2011-01-01

We present an approach to segmenting shapes in a heterogenous shape database. Our approach segments the shapes jointly, utilizing features from multiple shapes to improve the segmentation of each. The approach is entirely unsupervised and is based on an integer quadratic programming formulation of the joint segmentation problem. The program optimizes over possible segmentations of individual shapes as well as over possible correspondences between segments from multiple shapes. The integer quadratic program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape segmentation significantly outperforms single-shape segmentation techniques. © 2011 ACM.
Multilevel Thresholding Method Based on Electromagnetism for Accurate Brain MRI Segmentation to Detect White Matter, Gray Matter, and CSF

Directory of Open Access Journals (Sweden)

G. Sandhya

2017-01-01

Full Text Available This work explains an advanced and accurate brain MRI segmentation method. MR brain image segmentation is to know the anatomical structure, to identify the abnormalities, and to detect various tissues which help in treatment planning prior to radiation therapy. This proposed technique is a Multilevel Thresholding (MT method based on the phenomenon of Electromagnetism and it segments the image into three tissues such as White Matter (WM, Gray Matter (GM, and CSF. The approach incorporates skull stripping and filtering using anisotropic diffusion filter in the preprocessing stage. This thresholding method uses the force of attraction-repulsion between the charged particles to increase the population. It is the combination of Electromagnetism-Like optimization algorithm with the Otsu and Kapur objective functions. The results obtained by using the proposed method are compared with the ground-truth images and have given best values for the measures sensitivity, specificity, and segmentation accuracy. The results using 10 MR brain images proved that the proposed method has accurately segmented the three brain tissues compared to the existing segmentation methods such as K-means, fuzzy C-means, OTSU MT, Particle Swarm Optimization (PSO, Bacterial Foraging Algorithm (BFA, Genetic Algorithm (GA, and Fuzzy Local Gaussian Mixture Model (FLGMM.
Data on the quantitative assessment pulmonary ground-glass opacification from coronary computed tomography angiography datasets

DEFF Research Database (Denmark)

Kühl, J Tobias; Kristensen, Thomas S; Thomsen, Anna F

2017-01-01

We assessed the CT attenuation density of the pulmonary tissue adjacent to the heart in patients with acute non-ST segment elevation myocardial infarction (J.T. Kuhl, T.S. Kristensen, A.F. Thomsen et al., 2016) [1]. This data was related to the level of ground-glass opacification evaluated by a r...
Segmentation-DrivenTomographic Reconstruction

DEFF Research Database (Denmark)

Kongskov, Rasmus Dalgas

such that the segmentation subsequently can be carried out by use of a simple segmentation method, for instance just a thresholding method. We tested the advantages of going from a two-stage reconstruction method to a one stage segmentation-driven reconstruction method for the phase contrast tomography reconstruction......The tomographic reconstruction problem is concerned with creating a model of the interior of an object from some measured data, typically projections of the object. After reconstructing an object it is often desired to segment it, either automatically or manually. For computed tomography (CT...
Rediscovering market segmentation.

Science.gov (United States)

Yankelovich, Daniel; Meer, David

2006-02-01

In 1964, Daniel Yankelovich introduced in the pages of HBR the concept of nondemographic segmentation, by which he meant the classification of consumers according to criteria other than age, residence, income, and such. The predictive power of marketing studies based on demographics was no longer strong enough to serve as a basis for marketing strategy, he argued. Buying patterns had become far better guides to consumers' future purchases. In addition, properly constructed nondemographic segmentations could help companies determine which products to develop, which distribution channels to sell them in, how much to charge for them, and how to advertise them. But more than 40 years later, nondemographic segmentation has become just as unenlightening as demographic segmentation had been. Today, the technique is used almost exclusively to fulfill the needs of advertising, which it serves mainly by populating commercials with characters that viewers can identify with. It is true that psychographic types like "High-Tech Harry" and "Joe Six-Pack" may capture some truth about real people's lifestyles, attitudes, self-image, and aspirations. But they are no better than demographics at predicting purchase behavior. Thus they give corporate decision makers very little idea of how to keep customers or capture new ones. Now, Daniel Yankelovich returns to these pages, with consultant David Meer, to argue the case for a broad view of nondemographic segmentation. They describe the elements of a smart segmentation strategy, explaining how segmentations meant to strengthen brand identity differ from those capable of telling a company which markets it should enter and what goods to make. And they introduce their "gravity of decision spectrum", a tool that focuses on the form of consumer behavior that should be of the greatest interest to marketers--the importance that consumers place on a product or product category.
Adding Theoretical Grounding to Grounded Theory: Toward Multi-Grounded Theory

OpenAIRE

Göran Goldkuhl; Stefan Cronholm

2010-01-01

The purpose of this paper is to challenge some of the cornerstones of the grounded theory approach and propose an extended and alternative approach for data analysis and theory development, which the authors call multi-grounded theory (MGT). A multi-grounded theory is not only empirically grounded; it is also grounded in other ways. Three different grounding processes are acknowledged: theoretical, empirical, and internal grounding. The authors go beyond the pure inductivist approach in GT an...
Cross support overview and operations concept for future space missions

Science.gov (United States)

Stallings, William; Kaufeler, Jean-Francois

1994-01-01

Ground networks must respond to the requirements of future missions, which include smaller sizes, tighter budgets, increased numbers, and shorter development schedules. The Consultative Committee for Space Data Systems (CCSDS) is meeting these challenges by developing a general cross support concept, reference model, and service specifications for Space Link Extension services for space missions involving cross support among Space Agencies. This paper identifies and bounds the problem, describes the need to extend Space Link services, gives an overview of the operations concept, and introduces complimentary CCSDS work on standardizing Space Link Extension services.
Automatic lung lobe segmentation of COPD patients using iterative B-spline fitting

Science.gov (United States)

Shamonin, D. P.; Staring, M.; Bakker, M. E.; Xiao, C.; Stolk, J.; Reiber, J. H. C.; Stoel, B. C.

2012-02-01

We present an automatic lung lobe segmentation algorithm for COPD patients. The method enhances fissures, removes unlikely fissure candidates, after which a B-spline is fitted iteratively through the remaining candidate objects. The iterative fitting approach circumvents the need to classify each object as being part of the fissure or being noise, and allows the fissure to be detected in multiple disconnected parts. This property is beneficial for good performance in patient data, containing incomplete and disease-affected fissures. The proposed algorithm is tested on 22 COPD patients, resulting in accurate lobe-based densitometry, and a median overlap of the fissure (defined 3 voxels wide) with an expert ground truth of 0.65, 0.54 and 0.44 for the three main fissures. This compares to complete lobe overlaps of 0.99, 0.98, 0.98, 0.97 and 0.87 for the five main lobes, showing promise for lobe segmentation on data of patients with moderate to severe COPD.
Registration-based segmentation with articulated model from multipostural magnetic resonance images for hand bone motion animation.

Science.gov (United States)

Chen, Hsin-Chen; Jou, I-Ming; Wang, Chien-Kuo; Su, Fong-Chin; Sun, Yung-Nien

2010-06-01

The quantitative measurements of hand bones, including volume, surface, orientation, and position are essential in investigating hand kinematics. Moreover, within the measurement stage, bone segmentation is the most important step due to its certain influences on measuring accuracy. Since hand bones are small and tubular in shape, magnetic resonance (MR) imaging is prone to artifacts such as nonuniform intensity and fuzzy boundaries. Thus, greater detail is required for improving segmentation accuracy. The authors then propose using a novel registration-based method on an articulated hand model to segment hand bones from multipostural MR images. The proposed method consists of the model construction and registration-based segmentation stages. Given a reference postural image, the first stage requires construction of a drivable reference model characterized by hand bone shapes, intensity patterns, and articulated joint mechanism. By applying the reference model to the second stage, the authors initially design a model-based registration pursuant to intensity distribution similarity, MR bone intensity properties, and constraints of model geometry to align the reference model to target bone regions of the given postural image. The authors then refine the resulting surface to improve the superimposition between the registered reference model and target bone boundaries. For each subject, given a reference postural image, the proposed method can automatically segment all hand bones from all other postural images. Compared to the ground truth from two experts, the resulting surface image had an average margin of error within 1 mm (mm) only. In addition, the proposed method showed good agreement on the overlap of bone segmentations by dice similarity coefficient and also demonstrated better segmentation results than conventional methods. The proposed registration-based segmentation method can successfully overcome drawbacks caused by inherent artifacts in MR images and
Reflection symmetry-integrated image segmentation.

Science.gov (United States)

Sun, Yu; Bhanu, Bir

2012-09-01

This paper presents a new symmetry-integrated region-based image segmentation method. The method is developed to obtain improved image segmentation by exploiting image symmetry. It is realized by constructing a symmetry token that can be flexibly embedded into segmentation cues. Interesting points are initially extracted from an image by the SIFT operator and they are further refined for detecting the global bilateral symmetry. A symmetry affinity matrix is then computed using the symmetry axis and it is used explicitly as a constraint in a region growing algorithm in order to refine the symmetry of the segmented regions. A multi-objective genetic search finds the segmentation result with the highest performance for both segmentation and symmetry, which is close to the global optimum. The method has been investigated experimentally in challenging natural images and images containing man-made objects. It is shown that the proposed method outperforms current segmentation methods both with and without exploiting symmetry. A thorough experimental analysis indicates that symmetry plays an important role as a segmentation cue, in conjunction with other attributes like color and texture.
SU-E-J-142: Performance Study of Automatic Image-Segmentation Algorithms in Motion Tracking Via MR-IGRT

International Nuclear Information System (INIS)

Feng, Y; Olsen, J.; Parikh, P.; Noel, C; Wooten, H; Du, D; Mutic, S; Hu, Y; Kawrakow, I; Dempsey, J

2014-01-01

Purpose: Evaluate commonly used segmentation algorithms on a commercially available real-time MR image guided radiotherapy (MR-IGRT) system (ViewRay), compare the strengths and weaknesses of each method, with the purpose of improving motion tracking for more accurate radiotherapy. Methods: MR motion images of bladder, kidney, duodenum, and liver tumor were acquired for three patients using a commercial on-board MR imaging system and an imaging protocol used during MR-IGRT. A series of 40 frames were selected for each case to cover at least 3 respiratory cycles. Thresholding, Canny edge detection, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE), along with the ViewRay treatment planning and delivery system (TPDS) were included in the comparisons. To evaluate the segmentation results, an expert manual contouring of the organs or tumor from a physician was used as a ground-truth. Metrics value of sensitivity, specificity, Jaccard similarity, and Dice coefficient were computed for comparison. Results: In the segmentation of single image frame, all methods successfully segmented the bladder and kidney, but only FKM, KHM and TPDS were able to segment the liver tumor and the duodenum. For segmenting motion image series, the TPDS method had the highest sensitivity, Jarccard, and Dice coefficients in segmenting bladder and kidney, while FKM and KHM had a slightly higher specificity. A similar pattern was observed when segmenting the liver tumor and the duodenum. The Canny method is not suitable for consistently segmenting motion frames in an automated process, while thresholding and RD-LSE cannot consistently segment a liver tumor and the duodenum. Conclusion: The study compared six different segmentation methods and showed the effectiveness of the ViewRay TPDS algorithm in segmenting motion images during MR-IGRT. Future studies include a selection of conformal segmentation methods based on image/organ-specific information
SU-E-J-142: Performance Study of Automatic Image-Segmentation Algorithms in Motion Tracking Via MR-IGRT

Energy Technology Data Exchange (ETDEWEB)

Feng, Y; Olsen, J.; Parikh, P.; Noel, C; Wooten, H; Du, D; Mutic, S; Hu, Y [Washington University, St. Louis, MO (United States); Kawrakow, I; Dempsey, J [Washington University, St. Louis, MO (United States); ViewRay Co., Oakwood Village, OH (United States)

2014-06-01

Purpose: Evaluate commonly used segmentation algorithms on a commercially available real-time MR image guided radiotherapy (MR-IGRT) system (ViewRay), compare the strengths and weaknesses of each method, with the purpose of improving motion tracking for more accurate radiotherapy. Methods: MR motion images of bladder, kidney, duodenum, and liver tumor were acquired for three patients using a commercial on-board MR imaging system and an imaging protocol used during MR-IGRT. A series of 40 frames were selected for each case to cover at least 3 respiratory cycles. Thresholding, Canny edge detection, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE), along with the ViewRay treatment planning and delivery system (TPDS) were included in the comparisons. To evaluate the segmentation results, an expert manual contouring of the organs or tumor from a physician was used as a ground-truth. Metrics value of sensitivity, specificity, Jaccard similarity, and Dice coefficient were computed for comparison. Results: In the segmentation of single image frame, all methods successfully segmented the bladder and kidney, but only FKM, KHM and TPDS were able to segment the liver tumor and the duodenum. For segmenting motion image series, the TPDS method had the highest sensitivity, Jarccard, and Dice coefficients in segmenting bladder and kidney, while FKM and KHM had a slightly higher specificity. A similar pattern was observed when segmenting the liver tumor and the duodenum. The Canny method is not suitable for consistently segmenting motion frames in an automated process, while thresholding and RD-LSE cannot consistently segment a liver tumor and the duodenum. Conclusion: The study compared six different segmentation methods and showed the effectiveness of the ViewRay TPDS algorithm in segmenting motion images during MR-IGRT. Future studies include a selection of conformal segmentation methods based on image/organ-specific information

Segmentation of vessels cluttered with cells using a physics based model.

Science.gov (United States)

Schmugge, Stephen J; Keller, Steve; Nguyen, Nhat; Souvenir, Richard; Huynh, Toan; Clemens, Mark; Shin, Min C

2008-01-01

Segmentation of vessels in biomedical images is important as it can provide insight into analysis of vascular morphology, topology and is required for kinetic analysis of flow velocity and vessel permeability. Intravital microscopy is a powerful tool as it enables in vivo imaging of both vasculature and circulating cells. However, the analysis of vasculature in those images is difficult due to the presence of cells and their image gradient. In this paper, we provide a novel method of segmenting vessels with a high level of cell related clutter. A set of virtual point pairs ("vessel probes") are moved reacting to forces including Vessel Vector Flow (VVF) and Vessel Boundary Vector Flow (VBVF) forces. Incorporating the cell detection, the VVF force attracts the probes toward the vessel, while the VBVF force attracts the virtual points of the probes to localize the vessel boundary without being distracted by the image features of the cells. The vessel probes are moved according to Newtonian Physics reacting to the net of forces applied on them. We demonstrate the results on a set of five real in vivo images of liver vasculature cluttered by white blood cells. When compared against the ground truth prepared by the technician, the Root Mean Squared Error (RMSE) of segmentation with VVF and VBVF was 55% lower than the method without VVF and VBVF.
Protocol to assess the neurophysiology associated with multi-segmental postural coordination

International Nuclear Information System (INIS)

Lomond, Karen V; Henry, Sharon M; Jacobs, Jesse V; Hitt, Juvena R; Horak, Fay B; Cohen, Rajal G; Schwartz, Daniel; Dumas, Julie A; Naylor, Magdalena R; Watts, Richard; DeSarno, Michael J

2013-01-01

Anticipatory postural adjustments (APAs) stabilize potential disturbances to posture caused by movement. Impaired APAs are common with disease and injury. Brain functions associated with generating APAs remain uncertain due to a lack of paired tasks that require similar limb motion from similar postural orientations, but differ in eliciting an APA while also being compatible with brain imaging techniques (e.g., functional magnetic resonance imaging; fMRI). This study developed fMRI-compatible tasks differentiated by the presence or absence of APAs during leg movement. Eighteen healthy subjects performed two leg movement tasks, supported leg raise (SLR) and unsupported leg raise (ULR), to elicit isolated limb motion (no APA) versus multi-segmental coordination patterns (including APA), respectively. Ground reaction forces under the feet and electromyographic activation amplitudes were assessed to determine the coordination strategy elicited for each task. Results demonstrated that the ULR task elicited a multi-segmental coordination that was either minimized or absent in the SLR task, indicating that it would serve as an adequate control task for fMRI protocols. A pilot study with a single subject performing each task in an MRI scanner demonstrated minimal head movement in both tasks and brain activation patterns consistent with an isolated limb movement for the SLR task versus multi-segmental postural coordination for the ULR task. (note)
1997 annual ground control operating plan for the Waste Isolation Pilot Plant

International Nuclear Information System (INIS)

1997-02-01

This plan presents background information and a working guide to assist Mine Operations and Engineering in developing strategies for addressing ground control issues at the Waste Isolation Pilot Plant (WIPP). With the anticipated receipt of waste in late 1997, this document provides additional detail to Panel 1 activities and options. The plan also serves as a foundation document for development and revision of the annual long-term ground control plan. Section 2.0 documents the current status of all underground excavations with respect to location, geology, geometry, age, ground support, operational use, projected life, and physical conditions. Section 3.0 presents the methods used to evaluate ground conditions, including visual observations of the roof, ribs, and floor, inspection of observation holes, and review of instrumentation data. Section 4.0 lists several ground support options and specific applications of each. Section 5.0 discusses remedial ground control measures that have been implemented to date. Section 6.0 presents projections and recommendations for ground control actions based on the information in Sections 2.0 through 5.0 of this plan and on a rating of the critical nature of each specific area. Section 7.0 presents a summary statement, and Section 8.0 includes references. Appendix A provides an overview and critique of ground control systems that have been, or may be, used at the site. Because of the dynamic nature of the underground openings and associated geotechnical activities, this plan will be revised as additional data are incorporated
Lung segment geometry study: simulation of largest possible tumours that fit into bronchopulmonary segments.

Science.gov (United States)

Welter, S; Stöcker, C; Dicken, V; Kühl, H; Krass, S; Stamatis, G

2012-03-01

Segmental resection in stage I non-small cell lung cancer (NSCLC) has been well described and is considered to have similar survival rates as lobectomy but with increased rates of local tumour recurrence due to inadequate parenchymal margins. In consequence, today segmentectomy is only performed when the tumour is smaller than 2 cm. Three-dimensional reconstructions from 11 thin-slice CT scans of bronchopulmonary segments were generated, and virtual spherical tumours were placed over the segments, respecting all segmental borders. As a next step, virtual parenchymal safety margins of 2 cm and 3 cm were subtracted and the size of the remaining tumour calculated. The maximum tumour diameters with a 30-mm parenchymal safety margin ranged from 26.1 mm in right-sided segments 7 + 8 to 59.8 mm in the left apical segments 1-3. Using a three-dimensional reconstruction of lung CT scans, we demonstrated that segmentectomy or resection of segmental groups should be feasible with adequate margins, even for larger tumours in selected cases. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.
MO-AB-BRA-09: Temporally Realistic Manipulation a 4D Biomechanical Lung Phantom for Evaluation of Simultaneous Registration and Segmentation

Energy Technology Data Exchange (ETDEWEB)

Markel, D; Levesque, I R.; Larkin, J; Leger, P; El Naqa, I [McGill University, Montreal, QC (Canada)

2015-06-15

Purpose: To produce multi-modality compatible, realistic datasets for the joint evaluation of segmentation and registration with a reliable ground truth using a 4D biomechanical lung phantom. The further development of a computer controlled air flow system for recreation of real patient breathing patterns is incorporated for additional evaluation of motion prediction algorithms. Methods: A pair of preserved porcine lungs was pneumatically manipulated using an in-house computer controlled respirator. The respirator consisted of a set of bellows actuated by a 186 W computer controlled industrial motor. Patient breathing traces were recorded using a respiratory bellows belt during CT simulation and input into a control program incorporating a proportional-integral-derivative (PID) feedback controller in LabVIEW. Mock tumors were created using dual compartment vacuum sealed sea sponges. 65% iohexol,a gadolinium-based contrast agent and 18F-FDG were used to produce contrast and thus determine a segmentation ground truth. The intensity distributions of the compartments were then digitally matched for the final dataset. A bifurcation tracking pipeline provided a registration ground truth using the bronchi of the lung. The lungs were scanned using a GE Discovery-ST PET/CT scanner and a Phillips Panorama 0.23T MRI using a T1 weighted 3D fast field echo (FFE) protocol. Results: The standard deviation of the error between the patient breathing trace and the encoder feedback from the respirator was found to be ±4.2%. Bifurcation tracking error using CT (0.97×0.97×3.27 mm{sup 3} resolution) was found to be sub-voxel up to 7.8 cm displacement for human lungs and less than 1.32 voxel widths in any axis up to 2.3 cm for the porcine lungs. Conclusion: An MRI/PET/CT compatible anatomically and temporally realistic swine lung phantom was developed for the evaluation of simultaneous registration and segmentation algorithms. With the addition of custom software and mock tumors, the
Sipunculans and segmentation

DEFF Research Database (Denmark)

Wanninger, Andreas; Kristof, Alen; Brinkmann, Nora

2009-01-01

mechanisms may act on the level of gene expression, cell proliferation, tissue differentiation and organ system formation in individual segments. Accordingly, in some polychaete annelids the first three pairs of segmental peripheral neurons arise synchronously, while the metameric commissures of the ventral...
A state-of-the-art review on segmentation algorithms in intravascular ultrasound (IVUS) images.

Science.gov (United States)

Katouzian, Amin; Angelini, Elsa D; Carlier, Stéphane G; Suri, Jasjit S; Navab, Nassir; Laine, Andrew F

2012-09-01

Over the past two decades, intravascular ultrasound (IVUS) image segmentation has remained a challenge for researchers while the use of this imaging modality is rapidly growing in catheterization procedures and in research studies. IVUS provides cross-sectional grayscale images of the arterial wall and the extent of atherosclerotic plaques with high spatial resolution in real time. In this paper, we review recently developed image processing methods for the detection of media-adventitia and luminal borders in IVUS images acquired with different transducers operating at frequencies ranging from 20 to 45 MHz. We discuss methodological challenges, lack of diversity in reported datasets, and weaknesses of quantification metrics that make IVUS segmentation still an open problem despite all efforts. In conclusion, we call for a common reference database, validation metrics, and ground-truth definition with which new and existing algorithms could be benchmarked.
MR/PET quantification tools: Registration, segmentation, classification, and MR-based attenuation correction

Science.gov (United States)

Fei, Baowei; Yang, Xiaofeng; Nye, Jonathon A.; Aarsvold, John N.; Raghunath, Nivedita; Cervo, Morgan; Stark, Rebecca; Meltzer, Carolyn C.; Votaw, John R.

2012-01-01

Purpose: Combined MR/PET is a relatively new, hybrid imaging modality. A human MR/PET prototype system consisting of a Siemens 3T Trio MR and brain PET insert was installed and tested at our institution. Its present design does not offer measured attenuation correction (AC) using traditional transmission imaging. This study is the development of quantification tools including MR-based AC for quantification in combined MR/PET for brain imaging. Methods: The developed quantification tools include image registration, segmentation, classification, and MR-based AC. These components were integrated into a single scheme for processing MR/PET data. The segmentation method is multiscale and based on the Radon transform of brain MR images. It was developed to segment the skull on T1-weighted MR images. A modified fuzzy C-means classification scheme was developed to classify brain tissue into gray matter, white matter, and cerebrospinal fluid. Classified tissue is assigned an attenuation coefficient so that AC factors can be generated. PET emission data are then reconstructed using a three-dimensional ordered sets expectation maximization method with the MR-based AC map. Ten subjects had separate MR and PET scans. The PET with [11C]PIB was acquired using a high-resolution research tomography (HRRT) PET. MR-based AC was compared with transmission (TX)-based AC on the HRRT. Seventeen volumes of interest were drawn manually on each subject image to compare the PET activities between the MR-based and TX-based AC methods. Results: For skull segmentation, the overlap ratio between our segmented results and the ground truth is 85.2 ± 2.6%. Attenuation correction results from the ten subjects show that the difference between the MR and TX-based methods was <6.5%. Conclusions: MR-based AC compared favorably with conventional transmission-based AC. Quantitative tools including registration, segmentation, classification, and MR-based AC have been developed for use in combined MR
MR/PET quantification tools: Registration, segmentation, classification, and MR-based attenuation correction

Energy Technology Data Exchange (ETDEWEB)

Fei, Baowei, E-mail: bfei@emory.edu [Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1841 Clifton Road Northeast, Atlanta, Georgia 30329 (United States); Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia 30322 (United States); Department of Mathematics and Computer Sciences, Emory University, Atlanta, Georgia 30322 (United States); Yang, Xiaofeng; Nye, Jonathon A.; Raghunath, Nivedita; Votaw, John R. [Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia 30329 (United States); Aarsvold, John N. [Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia 30329 (United States); Nuclear Medicine Service, Atlanta Veterans Affairs Medical Center, Atlanta, Georgia 30033 (United States); Cervo, Morgan; Stark, Rebecca [The Medical Physics Graduate Program in the George W. Woodruff School, Georgia Institute of Technology, Atlanta, Georgia 30332 (United States); Meltzer, Carolyn C. [Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia 30329 (United States); Department of Neurology and Department of Psychiatry and Behavior Sciences, Emory University School of Medicine, Atlanta, Georgia 30322 (United States)

2012-10-15

Purpose: Combined MR/PET is a relatively new, hybrid imaging modality. A human MR/PET prototype system consisting of a Siemens 3T Trio MR and brain PET insert was installed and tested at our institution. Its present design does not offer measured attenuation correction (AC) using traditional transmission imaging. This study is the development of quantification tools including MR-based AC for quantification in combined MR/PET for brain imaging. Methods: The developed quantification tools include image registration, segmentation, classification, and MR-based AC. These components were integrated into a single scheme for processing MR/PET data. The segmentation method is multiscale and based on the Radon transform of brain MR images. It was developed to segment the skull on T1-weighted MR images. A modified fuzzy C-means classification scheme was developed to classify brain tissue into gray matter, white matter, and cerebrospinal fluid. Classified tissue is assigned an attenuation coefficient so that AC factors can be generated. PET emission data are then reconstructed using a three-dimensional ordered sets expectation maximization method with the MR-based AC map. Ten subjects had separate MR and PET scans. The PET with [{sup 11}C]PIB was acquired using a high-resolution research tomography (HRRT) PET. MR-based AC was compared with transmission (TX)-based AC on the HRRT. Seventeen volumes of interest were drawn manually on each subject image to compare the PET activities between the MR-based and TX-based AC methods. Results: For skull segmentation, the overlap ratio between our segmented results and the ground truth is 85.2 ± 2.6%. Attenuation correction results from the ten subjects show that the difference between the MR and TX-based methods was <6.5%. Conclusions: MR-based AC compared favorably with conventional transmission-based AC. Quantitative tools including registration, segmentation, classification, and MR-based AC have been developed for use in combined MR/PET.
MR/PET quantification tools: Registration, segmentation, classification, and MR-based attenuation correction

International Nuclear Information System (INIS)

Fei, Baowei; Yang, Xiaofeng; Nye, Jonathon A.; Raghunath, Nivedita; Votaw, John R.; Aarsvold, John N.; Cervo, Morgan; Stark, Rebecca; Meltzer, Carolyn C.

2012-01-01

Purpose: Combined MR/PET is a relatively new, hybrid imaging modality. A human MR/PET prototype system consisting of a Siemens 3T Trio MR and brain PET insert was installed and tested at our institution. Its present design does not offer measured attenuation correction (AC) using traditional transmission imaging. This study is the development of quantification tools including MR-based AC for quantification in combined MR/PET for brain imaging. Methods: The developed quantification tools include image registration, segmentation, classification, and MR-based AC. These components were integrated into a single scheme for processing MR/PET data. The segmentation method is multiscale and based on the Radon transform of brain MR images. It was developed to segment the skull on T1-weighted MR images. A modified fuzzy C-means classification scheme was developed to classify brain tissue into gray matter, white matter, and cerebrospinal fluid. Classified tissue is assigned an attenuation coefficient so that AC factors can be generated. PET emission data are then reconstructed using a three-dimensional ordered sets expectation maximization method with the MR-based AC map. Ten subjects had separate MR and PET scans. The PET with ["1"1C]PIB was acquired using a high-resolution research tomography (HRRT) PET. MR-based AC was compared with transmission (TX)-based AC on the HRRT. Seventeen volumes of interest were drawn manually on each subject image to compare the PET activities between the MR-based and TX-based AC methods. Results: For skull segmentation, the overlap ratio between our segmented results and the ground truth is 85.2 ± 2.6%. Attenuation correction results from the ten subjects show that the difference between the MR and TX-based methods was <6.5%. Conclusions: MR-based AC compared favorably with conventional transmission-based AC. Quantitative tools including registration, segmentation, classification, and MR-based AC have been developed for use in combined MR/PET.
Using Predictability for Lexical Segmentation.

Science.gov (United States)

Çöltekin, Çağrı

2017-09-01

This study investigates a strategy based on predictability of consecutive sub-lexical units in learning to segment a continuous speech stream into lexical units using computational modeling and simulations. Lexical segmentation is one of the early challenges during language acquisition, and it has been studied extensively through psycholinguistic experiments as well as computational methods. However, despite strong empirical evidence, the explicit use of predictability of basic sub-lexical units in models of segmentation is underexplored. This paper presents an incremental computational model of lexical segmentation for exploring the usefulness of predictability for lexical segmentation. We show that the predictability cue is a strong cue for segmentation. Contrary to earlier reports in the literature, the strategy yields state-of-the-art segmentation performance with an incremental computational model that uses only this particular cue in a cognitively plausible setting. The paper also reports an in-depth analysis of the model, investigating the conditions affecting the usefulness of the strategy. Copyright © 2016 Cognitive Science Society, Inc.
Efficient graph-cut tattoo segmentation

Science.gov (United States)

Kim, Joonsoo; Parra, Albert; Li, He; Delp, Edward J.

2015-03-01

Law enforcement is interested in exploiting tattoos as an information source to identify, track and prevent gang-related crimes. Many tattoo image retrieval systems have been described. In a retrieval system tattoo segmentation is an important step for retrieval accuracy since segmentation removes background information in a tattoo image. Existing segmentation methods do not extract the tattoo very well when the background includes textures and color similar to skin tones. In this paper we describe a tattoo segmentation approach by determining skin pixels in regions near the tattoo. In these regions graph-cut segmentation using a skin color model and a visual saliency map is used to find skin pixels. After segmentation we determine which set of skin pixels are connected with each other that form a closed contour including a tattoo. The regions surrounded by the closed contours are considered tattoo regions. Our method segments tattoos well when the background includes textures and color similar to skin.
3D ground‐motion simulations of Mw 7 earthquakes on the Salt Lake City segment of the Wasatch fault zone: Variability of long‐period (T≥1 s) ground motions and sensitivity to kinematic rupture parameters

Science.gov (United States)

Moschetti, Morgan P.; Hartzell, Stephen; Ramirez-Guzman, Leonardo; Frankel, Arthur; Angster, Stephen J.; Stephenson, William J.

2017-01-01

We examine the variability of long‐period (T≥1 s) earthquake ground motions from 3D simulations of Mw 7 earthquakes on the Salt Lake City segment of the Wasatch fault zone, Utah, from a set of 96 rupture models with varying slip distributions, rupture speeds, slip velocities, and hypocenter locations. Earthquake ruptures were prescribed on a 3D fault representation that satisfies geologic constraints and maintained distinct strands for the Warm Springs and for the East Bench and Cottonwood faults. Response spectral accelerations (SA; 1.5–10 s; 5% damping) were measured, and average distance scaling was well fit by a simple functional form that depends on the near‐source intensity level SA0(T) and a corner distance Rc:SA(R,T)=SA0(T)(1+(R/Rc))−1. Period‐dependent hanging‐wall effects manifested and increased the ground motions by factors of about 2–3, though the effects appeared partially attributable to differences in shallow site response for sites on the hanging wall and footwall of the fault. Comparisons with modern ground‐motion prediction equations (GMPEs) found that the simulated ground motions were generally consistent, except within deep sedimentary basins, where simulated ground motions were greatly underpredicted. Ground‐motion variability exhibited strong lateral variations and, at some sites, exceeded the ground‐motion variability indicated by GMPEs. The effects on the ground motions of changing the values of the five kinematic rupture parameters can largely be explained by three predominant factors: distance to high‐slip subevents, dynamic stress drop, and changes in the contributions from directivity. These results emphasize the need for further characterization of the underlying distributions and covariances of the kinematic rupture parameters used in 3D ground‐motion simulations employed in probabilistic seismic‐hazard analyses.
SU-C-BRA-06: Automatic Brain Tumor Segmentation for Stereotactic Radiosurgery Applications

Energy Technology Data Exchange (ETDEWEB)

Liu, Y; Stojadinovic, S; Jiang, S; Timmerman, R; Abdulrahman, R; Nedzi, L; Gu, X [UT Southwestern Medical Center, Dallas, TX (United States)

2016-06-15

Purpose: Stereotactic radiosurgery (SRS), which delivers a potent dose of highly conformal radiation to the target in a single fraction, requires accurate tumor delineation for treatment planning. We present an automatic segmentation strategy, that synergizes intensity histogram thresholding, super-voxel clustering, and level-set based contour evolving methods to efficiently and accurately delineate SRS brain tumors on contrast-enhance T1-weighted (T1c) Magnetic Resonance Images (MRI). Methods: The developed auto-segmentation strategy consists of three major steps. Firstly, tumor sites are localized through 2D slice intensity histogram scanning. Then, super voxels are obtained through clustering the corresponding voxels in 3D with reference to the similarity metrics composited from spatial distance and intensity difference. The combination of the above two could generate the initial contour surface. Finally, a localized region active contour model is utilized to evolve the surface to achieve the accurate delineation of the tumors. The developed method was evaluated on numerical phantom data, synthetic BRATS (Multimodal Brain Tumor Image Segmentation challenge) data, and clinical patients’ data. The auto-segmentation results were quantitatively evaluated by comparing to ground truths with both volume and surface similarity metrics. Results: DICE coefficient (DC) was performed as a quantitative metric to evaluate the auto-segmentation in the numerical phantom with 8 tumors. DCs are 0.999±0.001 without noise, 0.969±0.065 with Rician noise and 0.976±0.038 with Gaussian noise. DC, NMI (Normalized Mutual Information), SSIM (Structural Similarity) and Hausdorff distance (HD) were calculated as the metrics for the BRATS and patients’ data. Assessment of BRATS data across 25 tumor segmentation yield DC 0.886±0.078, NMI 0.817±0.108, SSIM 0.997±0.002, and HD 6.483±4.079mm. Evaluation on 8 patients with total 14 tumor sites yield DC 0.872±0.070, NMI 0.824±0
Nonlinear seismic behavior of a CANDU containment building subjected to near-field ground motions

International Nuclear Information System (INIS)

Choi, In Kil; Ahn, Seong Moon; Choun, Young Sun; Seo, Jeong Moon

2004-01-01

The standard response spectrum proposed by US NRC has been used as a design earthquake for the design of Korean nuclear power plant structures. A survey on some of the Quaternary fault segments near Korean nuclear power plants is ongoing. It is likely that these faults will be identified as active ones. If the faults are confirmed as active ones, it will be necessary to reevaluate the seismic safety of the nuclear power plants located near the fault. Near-fault ground motions are the ground motions that occur near an earthquake fault. In general, the near-fault ground motion records exhibit a distinctive long period pulse like time history with very high peak velocities. These features are induced by the slip of the earthquake fault. Near-fault ground motions, which have caused much of the damage in recent major earthquakes, can be characterized by a pulse-like motion that exposes the structure to a high input energy at the beginning of the motion. In this study, nonlinear dynamic time-history analyses were performed to investigate the seismic behavior of a CANDU containment structure subjected to various earthquake ground motions including the near-field ground motions
Unifying framework for multimodal brain MRI segmentation based on Hidden Markov Chains.

Science.gov (United States)

Bricq, S; Collet, Ch; Armspach, J P

2008-12-01

In the frame of 3D medical imaging, accurate segmentation of multimodal brain MR images is of interest for many brain disorders. However, due to several factors such as noise, imaging artifacts, intrinsic tissue variation and partial volume effects, tissue classification remains a challenging task. In this paper, we present a unifying framework for unsupervised segmentation of multimodal brain MR images including partial volume effect, bias field correction, and information given by a probabilistic atlas. Here-proposed method takes into account neighborhood information using a Hidden Markov Chain (HMC) model. Due to the limited resolution of imaging devices, voxels may be composed of a mixture of different tissue types, this partial volume effect is included to achieve an accurate segmentation of brain tissues. Instead of assigning each voxel to a single tissue class (i.e., hard classification), we compute the relative amount of each pure tissue class in each voxel (mixture estimation). Further, a bias field estimation step is added to the proposed algorithm to correct intensity inhomogeneities. Furthermore, atlas priors were incorporated using probabilistic brain atlas containing prior expectations about the spatial localization of different tissue classes. This atlas is considered as a complementary sensor and the proposed method is extended to multimodal brain MRI without any user-tunable parameter (unsupervised algorithm). To validate this new unifying framework, we present experimental results on both synthetic and real brain images, for which the ground truth is available. Comparison with other often used techniques demonstrates the accuracy and the robustness of this new Markovian segmentation scheme.
Towards a Multi-Variable Parametric Cost Model for Ground and Space Telescopes

Science.gov (United States)

Stahl, H. Philip; Henrichs, Todd

2016-01-01

Parametric cost models can be used by designers and project managers to perform relative cost comparisons between major architectural cost drivers and allow high-level design trades; enable cost-benefit analysis for technology development investment; and, provide a basis for estimating total project cost between related concepts. This paper hypothesizes a single model, based on published models and engineering intuition, for both ground and space telescopes: OTA Cost approximately (X) D(exp (1.75 +/- 0.05)) lambda(exp(-0.5 +/- 0.25) T(exp -0.25) e (exp (-0.04)Y). Specific findings include: space telescopes cost 50X to 100X more ground telescopes; diameter is the most important CER; cost is reduced by approximately 50% every 20 years (presumably because of technology advance and process improvements); and, for space telescopes, cost associated with wavelength performance is balanced by cost associated with operating temperature. Finally, duplication only reduces cost for the manufacture of identical systems (i.e. multiple aperture sparse arrays or interferometers). And, while duplication does reduce the cost of manufacturing the mirrors of segmented primary mirror, this cost savings does not appear to manifest itself in the final primary mirror assembly (presumably because the structure for a segmented mirror is more complicated than for a monolithic mirror).
Impulsive radon emanation on a creeping segment of the San Andreas fault, California

International Nuclear Information System (INIS)

King, C.-Y.

1984-01-01

Radon emanation was continuously monitored for several months at two locations along a creeping segment of the San Andreas fault in central California. The recorded emanations showed several impulsive increases that lasted as much as five hours with amplitudes considerably larger than meteorologically induced diurnal variations. Some of the radon increases were accompanied or followed by earthquakes or fault-creep events. They were possibly the result of some sudden outbursts of relatively radon-rich ground gas, sometimes triggered by crustal deformation or vibration. (Auth.)
Fold distributions at clover, crystal and segment levels for segmented clover detectors

International Nuclear Information System (INIS)

Kshetri, R; Bhattacharya, P

2014-01-01

Fold distributions at clover, crystal and segment levels have been extracted for an array of segmented clover detectors for various gamma energies. A simple analysis of the results based on a model independant approach has been presented. For the first time, the clover fold distribution of an array and associated array addback factor have been extracted. We have calculated the percentages of the number of crystals and segments that fire for a full energy peak event
Intercalary bone segment transport in treatment of segmental tibial defects

International Nuclear Information System (INIS)

Iqbal, A.; Amin, M.S.

2002-01-01

Objective: To evaluate the results and complications of intercalary bone segment transport in the treatment of segmental tibial defects. Design: This is a retrospective analysis of patients with segmental tibial defects who were treated with intercalary bone segment transport method. Place and Duration of Study: The study was carried out at Combined Military Hospital, Rawalpindi from September 1997 to April 2001. Subjects and methods: Thirteen patients were included in the study who had developed tibial defects either due to open fractures with bone loss or subsequent to bone debridement of infected non unions. The mean bone defect was 6.4 cms and there were eight associated soft tissue defects. Locally made unilateral 'Naseer-Awais' (NA) fixator was used for bone segment transport. The distraction was done at the rate of 1mm/day after 7-10 days of osteotomy. The patients were followed-up fortnightly during distraction and monthly thereafter. The mean follow-up duration was 18 months. Results: The mean time in external fixation was 9.4 months. The m ean healing index' was 1.47 months/cm. Satisfactory union was achieved in all cases. Six cases (46.2%) required bone grafting at target site and in one of them grafting was required at the level of regeneration as well. All the wounds healed well with no residual infection. There was no residual leg length discrepancy of more than 20 mm nd one angular deformity of more than 5 degrees. The commonest complication encountered was pin track infection seen in 38% of Shanz Screws applied. Loosening occurred in 6.8% of Shanz screws, requiring re-adjustment. Ankle joint contracture with equinus deformity and peroneal nerve paresis occurred in one case each. The functional results were graded as 'good' in seven, 'fair' in four, and 'poor' in two patients. Overall, thirteen patients had 31 (minor/major) complications with a ratio of 2.38 complications per patient. To treat the bone defects and associated complications, a mean of

Spacecraft System Integration and Test: SSTI Lewis critical design audit

Science.gov (United States)

Brooks, R. P.; Cha, K. K.

1995-01-01

The Critical Design Audit package is the final detailed design package which provides a comprehensive description of the SSTI mission. This package includes the program overview, the system requirements, the science and applications activities, the ground segment development, the assembly, integration and test description, the payload and technology demonstrations, and the spacecraft bus subsystems. Publication and presentation of this document marks the final requirements and design freeze for SSTI.
Rule-based land cover classification from very high-resolution satellite image with multiresolution segmentation

Science.gov (United States)

Haque, Md. Enamul; Al-Ramadan, Baqer; Johnson, Brian A.

2016-07-01

Multiresolution segmentation and rule-based classification techniques are used to classify objects from very high-resolution satellite images of urban areas. Custom rules are developed using different spectral, geometric, and textural features with five scale parameters, which exploit varying classification accuracy. Principal component analysis is used to select the most important features out of a total of 207 different features. In particular, seven different object types are considered for classification. The overall classification accuracy achieved for the rule-based method is 95.55% and 98.95% for seven and five classes, respectively. Other classifiers that are not using rules perform at 84.17% and 97.3% accuracy for seven and five classes, respectively. The results exploit coarse segmentation for higher scale parameter and fine segmentation for lower scale parameter. The major contribution of this research is the development of rule sets and the identification of major features for satellite image classification where the rule sets are transferable and the parameters are tunable for different types of imagery. Additionally, the individual objectwise classification and principal component analysis help to identify the required object from an arbitrary number of objects within images given ground truth data for the training.
Multicultural Ground Teams in Space Programs

Science.gov (United States)

Maier, M.

2012-01-01

In the early years of space flight only two countries had access to space. In the last twenty years, there have been major changes in how we conduct space business. With the fall of the iron curtain and the growing of the European Union, more and more players were able to join the space business and space science. By end of the last century, numerous countries, agencies and companies earned the right to be equal partners in space projects. This paper investigates the impact of multicultural teams in the space arena. Fortunately, in manned spaceflight, especially for long duration missions, there are several studies and simulations reporting on multicultural team impact. These data have not been as well explored on the team interactions within the ground crews. The focus of this paper are the teams working on the ISS project. Hypotheses will be drawn from the results of space crew research to determine parallels and differences for this vital segment of success in space missions. The key source of the data will be drawn from structured interviews with managers and other ground crews on the ISS project.
Market segmentation in behavioral perspective.

OpenAIRE

Wells, V.K.; Chang, S.W.; Oliveira-Castro, J.M.; Pallister, J.

2010-01-01

A segmentation approach is presented using both traditional demographic segmentation bases (age, social class/occupation, and working status) and a segmentation by benefits sought. The benefits sought in this case are utilitarian and informational reinforcement, variables developed from the Behavioral Perspective Model (BPM). Using data from 1,847 consumers and from a total of 76,682 individual purchases, brand choice and price and reinforcement responsiveness were assessed for each segment a...
The role of attention in figure-ground segregation in areas V1 and V4 of the visual cortex

NARCIS (Netherlands)

Poort, J.; Raudies, F.; Wannig, A.; Lamme, V.A.F.; Neumann, H.; Roelfsema, P.R.

2012-01-01

Our visual system segments images into objects and background. Figure-ground segregation relies on the detection of feature discontinuities that signal boundaries between the figures and the background and on a complementary region-filling process that groups together image regions with similar
A multimodality segmentation framework for automatic target delineation in head and neck radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Yang, Jinzhong; Aristophanous, Michalis, E-mail: MAristophanous@mdanderson.org [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States); Beadle, Beth M.; Garden, Adam S. [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States); Schwartz, David L. [Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, Texas 75390 (United States)

2015-09-15

Purpose: To develop an automatic segmentation algorithm integrating imaging information from computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI) to delineate target volume in head and neck cancer radiotherapy. Methods: Eleven patients with unresectable disease at the tonsil or base of tongue who underwent MRI, CT, and PET/CT within two months before the start of radiotherapy or chemoradiotherapy were recruited for the study. For each patient, PET/CT and T1-weighted contrast MRI scans were first registered to the planning CT using deformable and rigid registration, respectively, to resample the PET and magnetic resonance (MR) images to the planning CT space. A binary mask was manually defined to identify the tumor area. The resampled PET and MR images, the planning CT image, and the binary mask were fed into the automatic segmentation algorithm for target delineation. The algorithm was based on a multichannel Gaussian mixture model and solved using an expectation–maximization algorithm with Markov random fields. To evaluate the algorithm, we compared the multichannel autosegmentation with an autosegmentation method using only PET images. The physician-defined gross tumor volume (GTV) was used as the “ground truth” for quantitative evaluation. Results: The median multichannel segmented GTV of the primary tumor was 15.7 cm{sup 3} (range, 6.6–44.3 cm{sup 3}), while the PET segmented GTV was 10.2 cm{sup 3} (range, 2.8–45.1 cm{sup 3}). The median physician-defined GTV was 22.1 cm{sup 3} (range, 4.2–38.4 cm{sup 3}). The median difference between the multichannel segmented and physician-defined GTVs was −10.7%, not showing a statistically significant difference (p-value = 0.43). However, the median difference between the PET segmented and physician-defined GTVs was −19.2%, showing a statistically significant difference (p-value =0.0037). The median Dice similarity coefficient between the multichannel segmented
A multimodality segmentation framework for automatic target delineation in head and neck radiotherapy.

Science.gov (United States)

Yang, Jinzhong; Beadle, Beth M; Garden, Adam S; Schwartz, David L; Aristophanous, Michalis

2015-09-01

To develop an automatic segmentation algorithm integrating imaging information from computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI) to delineate target volume in head and neck cancer radiotherapy. Eleven patients with unresectable disease at the tonsil or base of tongue who underwent MRI, CT, and PET/CT within two months before the start of radiotherapy or chemoradiotherapy were recruited for the study. For each patient, PET/CT and T1-weighted contrast MRI scans were first registered to the planning CT using deformable and rigid registration, respectively, to resample the PET and magnetic resonance (MR) images to the planning CT space. A binary mask was manually defined to identify the tumor area. The resampled PET and MR images, the planning CT image, and the binary mask were fed into the automatic segmentation algorithm for target delineation. The algorithm was based on a multichannel Gaussian mixture model and solved using an expectation-maximization algorithm with Markov random fields. To evaluate the algorithm, we compared the multichannel autosegmentation with an autosegmentation method using only PET images. The physician-defined gross tumor volume (GTV) was used as the "ground truth" for quantitative evaluation. The median multichannel segmented GTV of the primary tumor was 15.7 cm(3) (range, 6.6-44.3 cm(3)), while the PET segmented GTV was 10.2 cm(3) (range, 2.8-45.1 cm(3)). The median physician-defined GTV was 22.1 cm(3) (range, 4.2-38.4 cm(3)). The median difference between the multichannel segmented and physician-defined GTVs was -10.7%, not showing a statistically significant difference (p-value = 0.43). However, the median difference between the PET segmented and physician-defined GTVs was -19.2%, showing a statistically significant difference (p-value =0.0037). The median Dice similarity coefficient between the multichannel segmented and physician-defined GTVs was 0.75 (range, 0.55-0.84), and the
A multimodality segmentation framework for automatic target delineation in head and neck radiotherapy

International Nuclear Information System (INIS)

Yang, Jinzhong; Aristophanous, Michalis; Beadle, Beth M.; Garden, Adam S.; Schwartz, David L.

2015-01-01

Purpose: To develop an automatic segmentation algorithm integrating imaging information from computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI) to delineate target volume in head and neck cancer radiotherapy. Methods: Eleven patients with unresectable disease at the tonsil or base of tongue who underwent MRI, CT, and PET/CT within two months before the start of radiotherapy or chemoradiotherapy were recruited for the study. For each patient, PET/CT and T1-weighted contrast MRI scans were first registered to the planning CT using deformable and rigid registration, respectively, to resample the PET and magnetic resonance (MR) images to the planning CT space. A binary mask was manually defined to identify the tumor area. The resampled PET and MR images, the planning CT image, and the binary mask were fed into the automatic segmentation algorithm for target delineation. The algorithm was based on a multichannel Gaussian mixture model and solved using an expectation–maximization algorithm with Markov random fields. To evaluate the algorithm, we compared the multichannel autosegmentation with an autosegmentation method using only PET images. The physician-defined gross tumor volume (GTV) was used as the “ground truth” for quantitative evaluation. Results: The median multichannel segmented GTV of the primary tumor was 15.7 cm"3 (range, 6.6–44.3 cm"3), while the PET segmented GTV was 10.2 cm"3 (range, 2.8–45.1 cm"3). The median physician-defined GTV was 22.1 cm"3 (range, 4.2–38.4 cm"3). The median difference between the multichannel segmented and physician-defined GTVs was −10.7%, not showing a statistically significant difference (p-value = 0.43). However, the median difference between the PET segmented and physician-defined GTVs was −19.2%, showing a statistically significant difference (p-value =0.0037). The median Dice similarity coefficient between the multichannel segmented and physician-defined GTVs was
Segmentation editing improves efficiency while reducing inter-expert variation and maintaining accuracy for normal brain tissues in the presence of space-occupying lesions

International Nuclear Information System (INIS)

Deeley, M A; Chen, A; Cmelak, A; Malcolm, A; Jaboin, J; Niermann, K; Yang, Eddy S; Yu, David S; Datteri, R D; Noble, J; Dawant, B M; Donnelly, E; Moretti, L

2013-01-01

Image segmentation has become a vital and often rate-limiting step in modern radiotherapy treatment planning. In recent years, the pace and scope of algorithm development, and even introduction into the clinic, have far exceeded evaluative studies. In this work we build upon our previous evaluation of a registration driven segmentation algorithm in the context of 8 expert raters and 20 patients who underwent radiotherapy for large space-occupying tumours in the brain. In this work we tested four hypotheses concerning the impact of manual segmentation editing in a randomized single-blinded study. We tested these hypotheses on the normal structures of the brainstem, optic chiasm, eyes and optic nerves using the Dice similarity coefficient, volume, and signed Euclidean distance error to evaluate the impact of editing on inter-rater variance and accuracy. Accuracy analyses relied on two simulated ground truth estimation methods: simultaneous truth and performance level estimation and a novel implementation of probability maps. The experts were presented with automatic, their own, and their peers’ segmentations from our previous study to edit. We found, independent of source, editing reduced inter-rater variance while maintaining or improving accuracy and improving efficiency with at least 60% reduction in contouring time. In areas where raters performed poorly contouring from scratch, editing of the automatic segmentations reduced the prevalence of total anatomical miss from approximately 16% to 8% of the total slices contained within the ground truth estimations. These findings suggest that contour editing could be useful for consensus building such as in developing delineation standards, and that both automated methods and even perhaps less sophisticated atlases could improve efficiency, inter-rater variance, and accuracy. (paper)
SU-E-J-132: Automated Segmentation with Post-Registration Atlas Selection Based On Mutual Information

International Nuclear Information System (INIS)

Ren, X; Gao, H; Sharp, G

2015-01-01

Purpose: The delineation of targets and organs-at-risk is a critical step during image-guided radiation therapy, for which manual contouring is the gold standard. However, it is often time-consuming and may suffer from intra- and inter-rater variability. The purpose of this work is to investigate the automated segmentation. Methods: The automatic segmentation here is based on mutual information (MI), with the atlas from Public Domain Database for Computational Anatomy (PDDCA) with manually drawn contours.Using dice coefficient (DC) as the quantitative measure of segmentation accuracy, we perform leave-one-out cross-validations for all PDDCA images sequentially, during which other images are registered to each chosen image and DC is computed between registered contour and ground truth. Meanwhile, six strategies, including MI, are selected to measure the image similarity, with MI to be the best. Then given a target image to be segmented and an atlas, automatic segmentation consists of: (a) the affine registration step for image positioning; (b) the active demons registration method to register the atlas to the target image; (c) the computation of MI values between the deformed atlas and the target image; (d) the weighted image fusion of three deformed atlas images with highest MI values to form the segmented contour. Results: MI was found to be the best among six studied strategies in the sense that it had the highest positive correlation between similarity measure (e.g., MI values) and DC. For automated segmentation, the weighted image fusion of three deformed atlas images with highest MI values provided the highest DC among four proposed strategies. Conclusion: MI has the highest correlation with DC, and therefore is an appropriate choice for post-registration atlas selection in atlas-based segmentation. Xuhua Ren and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)
SU-E-J-132: Automated Segmentation with Post-Registration Atlas Selection Based On Mutual Information

Energy Technology Data Exchange (ETDEWEB)

Ren, X; Gao, H [Shanghai Jiao Tong University, Shanghai, Shanghai (China); Sharp, G [Massachusetts General Hospital, Boston, MA (United States)

2015-06-15

Purpose: The delineation of targets and organs-at-risk is a critical step during image-guided radiation therapy, for which manual contouring is the gold standard. However, it is often time-consuming and may suffer from intra- and inter-rater variability. The purpose of this work is to investigate the automated segmentation. Methods: The automatic segmentation here is based on mutual information (MI), with the atlas from Public Domain Database for Computational Anatomy (PDDCA) with manually drawn contours.Using dice coefficient (DC) as the quantitative measure of segmentation accuracy, we perform leave-one-out cross-validations for all PDDCA images sequentially, during which other images are registered to each chosen image and DC is computed between registered contour and ground truth. Meanwhile, six strategies, including MI, are selected to measure the image similarity, with MI to be the best. Then given a target image to be segmented and an atlas, automatic segmentation consists of: (a) the affine registration step for image positioning; (b) the active demons registration method to register the atlas to the target image; (c) the computation of MI values between the deformed atlas and the target image; (d) the weighted image fusion of three deformed atlas images with highest MI values to form the segmented contour. Results: MI was found to be the best among six studied strategies in the sense that it had the highest positive correlation between similarity measure (e.g., MI values) and DC. For automated segmentation, the weighted image fusion of three deformed atlas images with highest MI values provided the highest DC among four proposed strategies. Conclusion: MI has the highest correlation with DC, and therefore is an appropriate choice for post-registration atlas selection in atlas-based segmentation. Xuhua Ren and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)
Review: Thomas Brüsemeister (2000). Qualitative Forschung. Ein Überblick [Qualitative Research: An Overview

OpenAIRE

Martin Spetsmann-Kunkel

2002-01-01

Thomas BRÜSEMEISTER's book Qualitative Forschung. Ein Überblick [Qualitative Research: An Overview] presents five different methods of social research: case study, narrative interview, grounded theory, ethnomethododical conversation analysis, and objective hermeneutics. These methods are so described as to make them clear and understandable for university entrants and lay people in the area of qualitative social research. URN: urn:nbn:de:0114-fqs020252
ADVANCED CLUSTER BASED IMAGE SEGMENTATION

Directory of Open Access Journals (Sweden)

D. Kesavaraja

2011-11-01

Full Text Available This paper presents efficient and portable implementations of a useful image segmentation technique which makes use of the faster and a variant of the conventional connected components algorithm which we call parallel Components. In the Modern world majority of the doctors are need image segmentation as the service for various purposes and also they expect this system is run faster and secure. Usually Image segmentation Algorithms are not working faster. In spite of several ongoing researches in Conventional Segmentation and its Algorithms might not be able to run faster. So we propose a cluster computing environment for parallel image Segmentation to provide faster result. This paper is the real time implementation of Distributed Image Segmentation in Clustering of Nodes. We demonstrate the effectiveness and feasibility of our method on a set of Medical CT Scan Images. Our general framework is a single address space, distributed memory programming model. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. The image segmentation algorithm makes use of an efficient cluster process which uses a novel approach for parallel merging. Our experimental results are consistent with the theoretical analysis and practical results. It provides the faster execution time for segmentation, when compared with Conventional method. Our test data is different CT scan images from the Medical database. More efficient implementations of Image Segmentation will likely result in even faster execution times.
Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods

Energy Technology Data Exchange (ETDEWEB)

Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich [Departments of Electrical and Computer Engineering and Internal Medicine, Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16, A-8010 Graz (Austria); Department of Electrical and Computer Engineering, Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Department of Radiology, Medical University Graz, Auenbruggerplatz 34, A-8010 Graz (Austria)

2012-03-15

Purpose: Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. Methods: A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and/or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Results: Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of
Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods

International Nuclear Information System (INIS)

Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich

2012-01-01

Purpose: Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. Methods: A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and/or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Results: Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of
Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods.

Science.gov (United States)

Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich

2012-03-01

Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and∕or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of user interaction
Cluster Ensemble-Based Image Segmentation

Directory of Open Access Journals (Sweden)

Xiaoru Wang

2013-07-01

Full Text Available Image segmentation is the foundation of computer vision applications. In this paper, we propose a new cluster ensemble-based image segmentation algorithm, which overcomes several problems of traditional methods. We make two main contributions in this paper. First, we introduce the cluster ensemble concept to fuse the segmentation results from different types of visual features effectively, which can deliver a better final result and achieve a much more stable performance for broad categories of images. Second, we exploit the PageRank idea from Internet applications and apply it to the image segmentation task. This can improve the final segmentation results by combining the spatial information of the image and the semantic similarity of regions. Our experiments on four public image databases validate the superiority of our algorithm over conventional single type of feature or multiple types of features-based algorithms, since our algorithm can fuse multiple types of features effectively for better segmentation results. Moreover, our method is also proved to be very competitive in comparison with other state-of-the-art segmentation algorithms.
Albedo estimation for scene segmentation

Energy Technology Data Exchange (ETDEWEB)

Lee, C H; Rosenfeld, A

1983-03-01

Standard methods of image segmentation do not take into account the three-dimensional nature of the underlying scene. For example, histogram-based segmentation tacitly assumes that the image intensity is piecewise constant, and this is not true when the scene contains curved surfaces. This paper introduces a method of taking 3d information into account in the segmentation process. The image intensities are adjusted to compensate for the effects of estimated surface orientation; the adjusted intensities can be regarded as reflectivity estimates. When histogram-based segmentation is applied to these new values, the image is segmented into parts corresponding to surfaces of constant reflectivity in the scene. 7 references.
Segmenting the Adult Education Market.

Science.gov (United States)

Aurand, Tim

1994-01-01

Describes market segmentation and how the principles of segmentation can be applied to the adult education market. Indicates that applying segmentation techniques to adult education programs results in programs that are educationally and financially satisfying and serve an appropriate population. (JOW)
Gamifying Video Object Segmentation.

Science.gov (United States)

Spampinato, Concetto; Palazzo, Simone; Giordano, Daniela

2017-10-01

Video object segmentation can be considered as one of the most challenging computer vision problems. Indeed, so far, no existing solution is able to effectively deal with the peculiarities of real-world videos, especially in cases of articulated motion and object occlusions; limitations that appear more evident when we compare the performance of automated methods with the human one. However, manually segmenting objects in videos is largely impractical as it requires a lot of time and concentration. To address this problem, in this paper we propose an interactive video object segmentation method, which exploits, on one hand, the capability of humans to identify correctly objects in visual scenes, and on the other hand, the collective human brainpower to solve challenging and large-scale tasks. In particular, our method relies on a game with a purpose to collect human inputs on object locations, followed by an accurate segmentation phase achieved by optimizing an energy function encoding spatial and temporal constraints between object regions as well as human-provided location priors. Performance analysis carried out on complex video benchmarks, and exploiting data provided by over 60 users, demonstrated that our method shows a better trade-off between annotation times and segmentation accuracy than interactive video annotation and automated video object segmentation approaches.

The pinwheel pupil discovery: exoplanet science & improved processing with segmented telescopes

Science.gov (United States)

Breckinridge, James Bernard

2018-01-01

In this paper, we show that by using a “pinwheel” architecture for the segmented primary mirror and curved supports for the secondary mirror, we can achieve a near uniform diffraction background in ground and space large telescope systems needed for high SNR exoplanet science. Also, the point spread function will be nearly rotationally symmetric, enabling improved digital image reconstruction. Large (>4-m) aperture space telescopes are needed to characterize terrestrial exoplanets by direct imaging coronagraphy. Launch vehicle volume constrains these apertures are segmented and deployed in space to form a large mirror aperture that is masked by the gaps between the hexagonal segments and the shadows of the secondary support system. These gaps and shadows over the pupil result in an image plane point spread function that has bright spikes, which may mask or obscure exoplanets.These telescope artifact mask faint exoplanets, making it necessary for the spacecraft to make a roll about the boresight and integrate again to make sure no planets are missed. This increases integration time, and requires expensive space-craft resources to do bore-sight roll.Currently the LUVOIR and HabEx studies have several significant efforts to develop special purpose A/O technology and to place complex absorbing apodizers over their Hex pupils to shape the unwanted diffracted light. These strong apodizers absorb light, decreasing system transmittance and reducing SNR. Implementing curved pupil obscurations will eliminate the need for the highly absorbing apodizers and thus result in higher SNR.Quantitative analysis of diffraction patterns that use the pinwheel architecture are compared to straight hex-segment edges with a straight-line secondary shadow mask to show a gain of over a factor of 100 by reducing the background. For the first-time astronomers are able to control and minimize image plane diffraction background “noise”. This technology will enable 10-m segmented
Effect of CT scanning parameters on volumetric measurements of pulmonary nodules by 3D active contour segmentation: a phantom study

International Nuclear Information System (INIS)

Way, Ted W; Chan, H-P; Goodsitt, Mitchell M; Sahiner, Berkman; Hadjiiski, Lubomir M; Zhou Chuan; Chughtai, Aamer

2008-01-01

The purpose of this study is to investigate the effects of CT scanning and reconstruction parameters on automated segmentation and volumetric measurements of nodules in CT images. Phantom nodules of known sizes were used so that segmentation accuracy could be quantified in comparison to ground-truth volumes. Spherical nodules having 4.8, 9.5 and 16 mm diameters and 50 and 100 mg cc -1 calcium contents were embedded in lung-tissue-simulating foam which was inserted in the thoracic cavity of a chest section phantom. CT scans of the phantom were acquired with a 16-slice scanner at various tube currents, pitches, fields-of-view and slice thicknesses. Scans were also taken using identical techniques either within the same day or five months apart for study of reproducibility. The phantom nodules were segmented with a three-dimensional active contour (3DAC) model that we previously developed for use on patient nodules. The percentage volume errors relative to the ground-truth volumes were estimated under the various imaging conditions. There was no statistically significant difference in volume error for repeated CT scans or scans taken with techniques where only pitch, field of view, or tube current (mA) were changed. However, the slice thickness significantly (p < 0.05) affected the volume error. Therefore, to evaluate nodule growth, consistent imaging conditions and high resolution should be used for acquisition of the serial CT scans, especially for smaller nodules. Understanding the effects of scanning and reconstruction parameters on volume measurements by 3DAC allows better interpretation of data and assessment of growth. Tracking nodule growth with computerized segmentation methods would reduce inter- and intraobserver variabilities
An overview of the NASA rotary engine research program

Science.gov (United States)

Meng, P. R.; Hady, W. F.

1984-01-01

A brief overview and technical highlights of the research efforts and studies on rotary engines over the last several years at the NASA Lewis Research Center are presented. The test results obtained from turbocharged rotary engines and preliminary results from a high performance single rotor engine were discussed. Combustion modeling studies of the rotary engine and the use of a Laser Doppler Velocimeter to confirm the studies were examined. An in-house program in which a turbocharged rotary engine was installed in a Cessna Skymaster for ground test studies was reviewed. Details are presented on single rotor stratified charge rotary engine research efforts, both in-house and on contract.
Dosimetric impact of dual-energy CT tissue segmentation for low-energy prostate brachytherapy: a Monte Carlo study

Science.gov (United States)

Remy, Charlotte; Lalonde, Arthur; Béliveau-Nadeau, Dominic; Carrier, Jean-François; Bouchard, Hugo

2018-01-01

The purpose of this study is to evaluate the impact of a novel tissue characterization method using dual-energy over single-energy computed tomography (DECT and SECT) on Monte Carlo (MC) dose calculations for low-dose rate (LDR) prostate brachytherapy performed in a patient like geometry. A virtual patient geometry is created using contours from a real patient pelvis CT scan, where known elemental compositions and varying densities are overwritten in each voxel. A second phantom is made with additional calcifications. Both phantoms are the ground truth with which all results are compared. Simulated CT images are generated from them using attenuation coefficients taken from the XCOM database with a 100 kVp spectrum for SECT and 80 and 140Sn kVp for DECT. Tissue segmentation for Monte Carlo dose calculation is made using a stoichiometric calibration method for the simulated SECT images. For the DECT images, Bayesian eigentissue decomposition is used. A LDR prostate brachytherapy plan is defined with 125I sources and then calculated using the EGSnrc user-code Brachydose for each case. Dose distributions and dose-volume histograms (DVH) are compared to ground truth to assess the accuracy of tissue segmentation. For noiseless images, DECT-based tissue segmentation outperforms the SECT procedure with a root mean square error (RMS) on relative errors on dose distributions respectively of 2.39% versus 7.77%, and provides DVHs closest to the reference DVHs for all tissues. For a medium level of CT noise, Bayesian eigentissue decomposition still performs better on the overall dose calculation as the RMS error is found to be of 7.83% compared to 9.15% for SECT. Both methods give a similar DVH for the prostate while the DECT segmentation remains more accurate for organs at risk and in presence of calcifications, with less than 5% of RMS errors within the calcifications versus up to 154% for SECT. In a patient-like geometry, DECT-based tissue segmentation provides dose
U.S. Army Custom Segmentation System

Science.gov (United States)

2007-06-01

segmentation is individual or intergroup differences in response to marketing - mix variables. Presumptions about segments: •different demands in a...product or service category, •respond differently to changes in the marketing mix Criteria for segments: •The segments must exist in the environment
Fully automatic detection and segmentation of abdominal aortic thrombus in post-operative CTA images using Deep Convolutional Neural Networks.

Science.gov (United States)

López-Linares, Karen; Aranjuelo, Nerea; Kabongo, Luis; Maclair, Gregory; Lete, Nerea; Ceresa, Mario; García-Familiar, Ainhoa; Macía, Iván; González Ballester, Miguel A

2018-05-01

Computerized Tomography Angiography (CTA) based follow-up of Abdominal Aortic Aneurysms (AAA) treated with Endovascular Aneurysm Repair (EVAR) is essential to evaluate the progress of the patient and detect complications. In this context, accurate quantification of post-operative thrombus volume is required. However, a proper evaluation is hindered by the lack of automatic, robust and reproducible thrombus segmentation algorithms. We propose a new fully automatic approach based on Deep Convolutional Neural Networks (DCNN) for robust and reproducible thrombus region of interest detection and subsequent fine thrombus segmentation. The DetecNet detection network is adapted to perform region of interest extraction from a complete CTA and a new segmentation network architecture, based on Fully Convolutional Networks and a Holistically-Nested Edge Detection Network, is presented. These networks are trained, validated and tested in 13 post-operative CTA volumes of different patients using a 4-fold cross-validation approach to provide more robustness to the results. Our pipeline achieves a Dice score of more than 82% for post-operative thrombus segmentation and provides a mean relative volume difference between ground truth and automatic segmentation that lays within the experienced human observer variance without the need of human intervention in most common cases. Copyright © 2018 Elsevier B.V. All rights reserved.
Sideband cooling and coherent dynamics in a microchip multi-segmented ion trap

Energy Technology Data Exchange (ETDEWEB)

Schulz, Stephan A; Poschinger, Ulrich; Ziesel, Frank; Schmidt-Kaler, Ferdinand [Universitaet Ulm, Institut fuer Quanteninformationsverarbeitung, Albert-Einstein-Allee 11, D-89069 Ulm (Germany)], E-mail: stephan.schulz@uni-ulm.de

2008-04-15

Miniaturized ion trap arrays with many trap segments present a promising architecture for scalable quantum information processing. The miniaturization of segmented linear Paul traps allows partitioning the microtrap into different storage and processing zones. The individual position control of many ions-each of them carrying qubit information in its long-lived electronic levels-by the external trap control voltages is important for the implementation of next generation large-scale quantum algorithms. We present a novel scalable microchip multi-segmented ion trap with two different adjacent zones, one for the storage and another dedicated to the processing of quantum information using single ions and linear ion crystals. A pair of radio-frequency-driven electrodes and 62 independently controlled dc electrodes allows shuttling of single ions or linear ion crystals with numerically designed axial potentials at axial and radial trap frequencies of a few megahertz. We characterize and optimize the microtrap using sideband spectroscopy on the narrow S{sub 1/2}{r_reversible}D{sub 5/2} qubit transition of the {sup 40}Ca{sup +} ion, and demonstrate coherent single-qubit Rabi rotations and optical cooling methods. We determine the heating rate using sideband cooling measurements to the vibrational ground state, which is necessary for subsequent two-qubit quantum logic operations. The applicability for scalable quantum information processing is proved.
Comparison of vessel enhancement algorithms applied to time-of-flight MRA images for cerebrovascular segmentation.

Science.gov (United States)

Phellan, Renzo; Forkert, Nils D

2017-11-01

Vessel enhancement algorithms are often used as a preprocessing step for vessel segmentation in medical images to improve the overall segmentation accuracy. Each algorithm uses different characteristics to enhance vessels, such that the most suitable algorithm may vary for different applications. This paper presents a comparative analysis of the accuracy gains in vessel segmentation generated by the use of nine vessel enhancement algorithms: Multiscale vesselness using the formulas described by Erdt (MSE), Frangi (MSF), and Sato (MSS), optimally oriented flux (OOF), ranking orientations responses path operator (RORPO), the regularized Perona-Malik approach (RPM), vessel enhanced diffusion (VED), hybrid diffusion with continuous switch (HDCS), and the white top hat algorithm (WTH). The filters were evaluated and compared based on time-of-flight MRA datasets and corresponding manual segmentations from 5 healthy subjects and 10 patients with an arteriovenous malformation. Additionally, five synthetic angiographic datasets with corresponding ground truth segmentation were generated with three different noise levels (low, medium, and high) and also used for comparison. The parameters for each algorithm and subsequent segmentation were optimized using leave-one-out cross evaluation. The Dice coefficient, Matthews correlation coefficient, area under the ROC curve, number of connected components, and true positives were used for comparison. The results of this study suggest that vessel enhancement algorithms do not always lead to more accurate segmentation results compared to segmenting nonenhanced images directly. Multiscale vesselness algorithms, such as MSE, MSF, and MSS proved to be robust to noise, while diffusion-based filters, such as RPM, VED, and HDCS ranked in the top of the list in scenarios with medium or no noise. Filters that assume tubular-shapes, such as MSE, MSF, MSS, OOF, RORPO, and VED show a decrease in accuracy when considering patients with an AVM
Poly(ether amide) segmented block copolymers with adipicacid based tetra amide segments

NARCIS (Netherlands)

Biemond, G.J.E.; Feijen, Jan; Gaymans, R.J.

2007-01-01

Poly(tetramethylene oxide)-based poly(ether ester amide)s with monodisperse tetraamide segments were synthesized. The tetraamide segment was based on adipic acid, terephthalic acid, and hexamethylenediamine. The synthesis method of the copolymers and the influence of the tetraamide concentration,
The deficit of decent work as a global problem of social and labor segment

Directory of Open Access Journals (Sweden)

Anatoliy Kolot

2016-12-01

Full Text Available The overview of the current trends in social and labor segment globally and in the Ukrainian economy is provided. The crises in functioning of the social and labor segment as the forms of expression of the deficit of decent work were isolated. The reasons destabilizing the social and labor segment and limiting the development of the decent work institute are presented. The findings on the situation of self-employment and vulnerable employment worldwide are given. The modern transformations in employment through the lens of decent work are disclosed, with a focus on vulnerable employment. A correlation between inequality in income and a deficit of decent work is shown. The relationship and interaction between decent work and human values in terms of the new economy and postindustrial society development as a philosophical platform of the modern concept of decent work is proven. The aggravation of the crisis of values of the labor g life in the light of deficit of the decent work is explained. The conceptual foundations of the decent work are revealed. The author's vision of the decent work institute as an integrated political, economic, and social platform of sustainable development is reasoned. The criteria and components of the decent work are presented. The importance of inclusive labor markets to expand the scale of decent work is disclosed. The strategic landmarks of overcoming the deficit of decent work are delineated.
Metric Learning for Hyperspectral Image Segmentation

Science.gov (United States)

Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca

2011-01-01

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.
Treatment of carcinoma of the upper thoracic segment of the esophagus

International Nuclear Information System (INIS)

Stolyarov, V.I.; Berezkin, D.P.; Trishkin, V.A.; Ekimov, V.I.; Filatov, V.N.; Shulepov, A.V.; Feliz, P.

1987-01-01

Out of 350 hospitalized cases of esophageal carcinoma in the upper thoracic segment, stage 3-4 tumors were identified in 82.8%. A retarded seeking of medical advice was chiefly responsidle for the advancement of tumors. Radical surgery was performed in 32 (9.1%) patients only. The percentage of radically-treated cases could have been greater, if there had been fewer refusals to operate and to be operated on both on the part of patiens and doctors who would object to surgery on the grounds of concomitant pathology or the patient's age. Radiotherapy, used in 197 (72.7%) patients as a sole method of treatment, was followed by remission in 68%
Market Segmentation for Information Services.

Science.gov (United States)

Halperin, Michael

1981-01-01

Discusses the advantages and limitations of market segmentation as strategy for the marketing of information services made available by nonprofit organizations, particularly libraries. Market segmentation is defined, a market grid for libraries is described, and the segmentation of information services is outlined. A 16-item reference list is…
Probabilistic Segmentation of Folk Music Recordings

Directory of Open Access Journals (Sweden)

Ciril Bohak

2016-01-01

Full Text Available The paper presents a novel method for automatic segmentation of folk music field recordings. The method is based on a distance measure that uses dynamic time warping to cope with tempo variations and a dynamic programming approach to handle pitch drifting for finding similarities and estimating the length of repeating segment. A probabilistic framework based on HMM is used to find segment boundaries, searching for optimal match between the expected segment length, between-segment similarities, and likely locations of segment beginnings. Evaluation of several current state-of-the-art approaches for segmentation of commercial music is presented and their weaknesses when dealing with folk music are exposed, such as intolerance to pitch drift and variable tempo. The proposed method is evaluated and its performance analyzed on a collection of 206 folk songs of different ensemble types: solo, two- and three-voiced, choir, instrumental, and instrumental with singing. It outperforms current commercial music segmentation methods for noninstrumental music and is on a par with the best for instrumental recordings. The method is also comparable to a more specialized method for segmentation of solo singing folk music recordings.
Automated medical image segmentation techniques

Directory of Open Access Journals (Sweden)

Sharma Neeraj

2010-01-01

Full Text Available Accurate segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT and Magnetic resonance (MR imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment planning. This review provides details of automated segmentation methods, specifically discussed in the context of CT and MR images. The motive is to discuss the problems encountered in segmentation of CT and MR images, and the relative merits and limitations of methods currently available for segmentation of medical images.
Prognostic validation of a 17-segment score derived from a 20-segment score for myocardial perfusion SPECT interpretation.

Science.gov (United States)

Berman, Daniel S; Abidov, Aiden; Kang, Xingping; Hayes, Sean W; Friedman, John D; Sciammarella, Maria G; Cohen, Ishac; Gerlach, James; Waechter, Parker B; Germano, Guido; Hachamovitch, Rory

2004-01-01

Recently, a 17-segment model of the left ventricle has been recommended as an optimally weighted approach for interpreting myocardial perfusion single photon emission computed tomography (SPECT). Methods to convert databases from previous 20- to new 17-segment data and criteria for abnormality for the 17-segment scores are needed. Initially, for derivation of the conversion algorithm, 65 patients were studied (algorithm population) (pilot group, n = 28; validation group, n = 37). Three conversion algorithms were derived: algorithm 1, which used mid, distal, and apical scores; algorithm 2, which used distal and apical scores alone; and algorithm 3, which used maximal scores of the distal septal, lateral, and apical segments in the 20-segment model for 3 corresponding segments of the 17-segment model. The prognosis population comprised 16,020 consecutive patients (mean age, 65 +/- 12 years; 41% women) who had exercise or vasodilator stress technetium 99m sestamibi myocardial perfusion SPECT and were followed up for 2.1 +/- 0.8 years. In this population, 17-segment scores were derived from 20-segment scores by use of algorithm 2, which demonstrated the best agreement with expert 17-segment reading in the algorithm population. The prognostic value of the 20- and 17-segment scores was compared by converting the respective summed scores into percent myocardium abnormal. Conversion algorithm 2 was found to be highly concordant with expert visual analysis by the 17-segment model (r = 0.982; kappa = 0.866) in the algorithm population. In the prognosis population, 456 cardiac deaths occurred during follow-up. When the conversion algorithm was applied, extent and severity of perfusion defects were nearly identical by 20- and derived 17-segment scores. The receiver operating characteristic curve areas by 20- and 17-segment perfusion scores were identical for predicting cardiac death (both 0.77 +/- 0.02, P = not significant). The optimal prognostic cutoff value for either 20
NUCLEAR SEGMENTATION IN MICROSCOPE CELL IMAGES: A HAND-SEGMENTED DATASET AND COMPARISON OF ALGORITHMS

OpenAIRE

Coelho, Luís Pedro; Shariff, Aabid; Murphy, Robert F.

2009-01-01

Image segmentation is an essential step in many image analysis pipelines and many algorithms have been proposed to solve this problem. However, they are often evaluated subjectively or based on a small number of examples. To fill this gap, we hand-segmented a set of 97 fluorescence microscopy images (a total of 4009 cells) and objectively evaluated some previously proposed segmentation algorithms.
Generalized pixel profiling and comparative segmentation with application to arteriovenous malformation segmentation.

Science.gov (United States)

Babin, D; Pižurica, A; Bellens, R; De Bock, J; Shang, Y; Goossens, B; Vansteenkiste, E; Philips, W

2012-07-01

Extraction of structural and geometric information from 3-D images of blood vessels is a well known and widely addressed segmentation problem. The segmentation of cerebral blood vessels is of great importance in diagnostic and clinical applications, with a special application in diagnostics and surgery on arteriovenous malformations (AVM). However, the techniques addressing the problem of the AVM inner structure segmentation are rare. In this work we present a novel method of pixel profiling with the application to segmentation of the 3-D angiography AVM images. Our algorithm stands out in situations with low resolution images and high variability of pixel intensity. Another advantage of our method is that the parameters are set automatically, which yields little manual user intervention. The results on phantoms and real data demonstrate its effectiveness and potentials for fine delineation of AVM structure. Copyright © 2012 Elsevier B.V. All rights reserved.
Robust shape regression for supervised vessel segmentation and its application to coronary segmentation in CTA

DEFF Research Database (Denmark)

Schaap, Michiel; van Walsum, Theo; Neefjes, Lisan

2011-01-01

This paper presents a vessel segmentation method which learns the geometry and appearance of vessels in medical images from annotated data and uses this knowledge to segment vessels in unseen images. Vessels are segmented in a coarse-to-fine fashion. First, the vessel boundaries are estimated...
TU-F-BRF-06: 3D Pancreas MRI Segmentation Using Dictionary Learning and Manifold Clustering

International Nuclear Information System (INIS)

Gou, S; Rapacchi, S; Hu, P; Sheng, K

2014-01-01

Purpose: The recent advent of MRI guided radiotherapy machines has lent an exciting platform for soft tissue target localization during treatment. However, tools to efficiently utilize MRI images for such purpose have not been developed. Specifically, to efficiently quantify the organ motion, we develop an automated segmentation method using dictionary learning and manifold clustering (DLMC). Methods: Fast 3D HASTE and VIBE MR images of 2 healthy volunteers and 3 patients were acquired. A bounding box was defined to include pancreas and surrounding normal organs including the liver, duodenum and stomach. The first slice of the MRI was used for dictionary learning based on mean-shift clustering and K-SVD sparse representation. Subsequent images were iteratively reconstructed until the error is less than a preset threshold. The preliminarily segmentation was subject to the constraints of manifold clustering. The segmentation results were compared with the mean shift merging (MSM), level set (LS) and manual segmentation methods. Results: DLMC resulted in consistently higher accuracy and robustness than comparing methods. Using manual contours as the ground truth, the mean Dices indices for all subjects are 0.54, 0.56 and 0.67 for MSM, LS and DLMC, respectively based on the HASTE image. The mean Dices indices are 0.70, 0.77 and 0.79 for the three methods based on VIBE images. DLMC is clearly more robust on the patients with the diseased pancreas while LS and MSM tend to over-segment the pancreas. DLMC also achieved higher sensitivity (0.80) and specificity (0.99) combining both imaging techniques. LS achieved equivalent sensitivity on VIBE images but was more computationally inefficient. Conclusion: We showed that pancreas and surrounding normal organs can be reliably segmented based on fast MRI using DLMC. This method will facilitate both planning volume definition and imaging guidance during treatment

TU-F-BRF-06: 3D Pancreas MRI Segmentation Using Dictionary Learning and Manifold Clustering

Energy Technology Data Exchange (ETDEWEB)

Gou, S; Rapacchi, S; Hu, P; Sheng, K [UCLA School of Medicine, Los Angeles, CA (United States)

2014-06-15

Purpose: The recent advent of MRI guided radiotherapy machines has lent an exciting platform for soft tissue target localization during treatment. However, tools to efficiently utilize MRI images for such purpose have not been developed. Specifically, to efficiently quantify the organ motion, we develop an automated segmentation method using dictionary learning and manifold clustering (DLMC). Methods: Fast 3D HASTE and VIBE MR images of 2 healthy volunteers and 3 patients were acquired. A bounding box was defined to include pancreas and surrounding normal organs including the liver, duodenum and stomach. The first slice of the MRI was used for dictionary learning based on mean-shift clustering and K-SVD sparse representation. Subsequent images were iteratively reconstructed until the error is less than a preset threshold. The preliminarily segmentation was subject to the constraints of manifold clustering. The segmentation results were compared with the mean shift merging (MSM), level set (LS) and manual segmentation methods. Results: DLMC resulted in consistently higher accuracy and robustness than comparing methods. Using manual contours as the ground truth, the mean Dices indices for all subjects are 0.54, 0.56 and 0.67 for MSM, LS and DLMC, respectively based on the HASTE image. The mean Dices indices are 0.70, 0.77 and 0.79 for the three methods based on VIBE images. DLMC is clearly more robust on the patients with the diseased pancreas while LS and MSM tend to over-segment the pancreas. DLMC also achieved higher sensitivity (0.80) and specificity (0.99) combining both imaging techniques. LS achieved equivalent sensitivity on VIBE images but was more computationally inefficient. Conclusion: We showed that pancreas and surrounding normal organs can be reliably segmented based on fast MRI using DLMC. This method will facilitate both planning volume definition and imaging guidance during treatment.
TU-H-CAMPUS-IeP3-01: Simultaneous PET Restoration and PET/CT Co-Segmentation Using a Variational Method

International Nuclear Information System (INIS)

Li, L; Tan, S; Lu, W

2016-01-01

Purpose: PET images are usually blurred due to the finite spatial resolution, while CT images suffer from low contrast. Segment a tumor from either a single PET or CT image is thus challenging. To make full use of the complementary information between PET and CT, we propose a novel variational method for simultaneous PET image restoration and PET/CT images co-segmentation. Methods: The proposed model was constructed based on the Γ-convergence approximation of Mumford-Shah (MS) segmentation model for PET/CT co-segmentation. Moreover, a PET de-blur process was integrated into the MS model to improve the segmentation accuracy. An interaction edge constraint term over the two modalities were specially designed to share the complementary information. The energy functional was iteratively optimized using an alternate minimization (AM) algorithm. The performance of the proposed method was validated on ten lung cancer cases and five esophageal cancer cases. The ground truth were manually delineated by an experienced radiation oncologist using the complementary visual features of PET and CT. The segmentation accuracy was evaluated by Dice similarity index (DSI) and volume error (VE). Results: The proposed method achieved an expected restoration result for PET image and satisfactory segmentation results for both PET and CT images. For lung cancer dataset, the average DSI (0.72) increased by 0.17 and 0.40 than single PET and CT segmentation. For esophageal cancer dataset, the average DSI (0.85) increased by 0.07 and 0.43 than single PET and CT segmentation. Conclusion: The proposed method took full advantage of the complementary information from PET and CT images. This work was supported in part by the National Cancer Institute Grants R01CA172638. Shan Tan and Laquan Li were supported in part by the National Natural Science Foundation of China, under Grant Nos. 60971112 and 61375018.
Structure-properties relationships of novel poly(carbonate-co-amide) segmented copolymers with polyamide-6 as hard segments and polycarbonate as soft segments

Science.gov (United States)

Yang, Yunyun; Kong, Weibo; Yuan, Ye; Zhou, Changlin; Cai, Xufu

2018-04-01

Novel poly(carbonate-co-amide) (PCA) block copolymers are prepared with polycarbonate diol (PCD) as soft segments, polyamide-6 (PA6) as hard segments and 4,4'-diphenylmethane diisocyanate (MDI) as coupling agent through reactive processing. The reactive processing strategy is eco-friendly and resolve the incompatibility between polyamide segments and PCD segments in preparation processing. The chemical structure, crystalline properties, thermal properties, mechanical properties and water resistance were extensively studied by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Differential scanning calorimetry (DSC), Thermal gravity analysis (TGA), Dynamic mechanical analysis (DMA), tensile testing, water contact angle and water absorption, respectively. The as-prepared PCAs exhibit obvious microphase separation between the crystalline hard PA6 phase and amorphous PCD soft segments. Meanwhile, PCAs showed outstanding mechanical with the maximum tensile strength of 46.3 MPa and elongation at break of 909%. The contact angle and water absorption results indicate that PCAs demonstrate outstanding water resistance even though possess the hydrophilic surfaces. The TGA measurements prove that the thermal stability of PCA can satisfy the requirement of multiple-processing without decomposition.
Segmentation and informality in Vietnam : a survey of the literature: country case study on labour market segmentation

OpenAIRE

Cling, Jean-Pierre; Razafindrakoto, Mireille; Roubaud, François

2014-01-01

Labour market segmentation is usually defined as the division of the labour markets into separate sub-markets or segments, distinguished by different characteristics and behavioural rules (incomes, contracts, etc.). The economic debate on the segmentation issue has been focusing in developed countries, and especially in Europe, on contractual segmentation and dualism.
Segmentation by Large Scale Hypothesis Testing - Segmentation as Outlier Detection

DEFF Research Database (Denmark)

Darkner, Sune; Dahl, Anders Lindbjerg; Larsen, Rasmus

2010-01-01

a microscope and we show how the method can handle transparent particles with significant glare point. The method generalizes to other problems. THis is illustrated by applying the method to camera calibration images and MRI of the midsagittal plane for gray and white matter separation and segmentation......We propose a novel and efficient way of performing local image segmentation. For many applications a threshold of pixel intensities is sufficient but determine the appropriate threshold value can be difficult. In cases with large global intensity variation the threshold value has to be adapted...... locally. We propose a method based on large scale hypothesis testing with a consistent method for selecting an appropriate threshold for the given data. By estimating the background distribution we characterize the segment of interest as a set of outliers with a certain probability based on the estimated...
(DCT-FY08) Target Detection Using Multiple Modality Airborne and Ground Based Sensors

Science.gov (United States)

2013-03-01

resolution SIFT grids in metric-topological SLAM ,” in Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2009. [4] M. Bosse and R...single camera SLAM ,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 6, pp. 1052–1067, 2007. [7] D. Nister, O. Naroditsky, and J. Bergen...segmentation with ground-based and airborne LIDAR range data,” in Proceedings of the Fourth International Symposium on 3D Data Processing
PLEIADES-HR SYSTEM PRODUCTS PERFORMANCE AFTER IN-ORBIT COMMISSIONING PHASE

Directory of Open Access Journals (Sweden)

C. Panem

2012-07-01

Full Text Available Launched on 2011, December 16th by the second Soyuz operated in French Guiana, PLEIADES-HR acquired its first high resolution images 3 days after. The PLEIADES program is a space Earth Observation system led by the French Space Agency (CNES, it provides the first european high resolution satellite which will simultaneously acquire in Panchromatic and Multi- Spectral modes 20 km wide images with a 70 cm nadir resolution. Imaging capabilities have been highly optimized in order to acquire, in the same pass, along-track mosaics, stereo pairs and triplets, and multi-targets. Ground segment processes automatically data to ensure operational requirements and quick access to images for the users. Since ground processing capabilities have been taken into account very early in the mission development, it has been possible to relax some costly on-board components requirements, in order to achieve a cost effective on-board/ground compromise. Starting from the PLEIADES system and on board characteristics, this paper first presents an overview of ground segment functional breakdown. Then it focuses more precisely on the different levels of products and associated processing performances. Finally the paper shows how appropriate ground processing systems allowed CNES Image Quality team to assess radiometric and geometric performances during the 6 first months of PLEIADES 1A.
Pavement management segment consolidation

Science.gov (United States)

1998-01-01

Dividing roads into "homogeneous" segments has been a major problem for all areas of highway engineering. SDDOT uses Deighton Associates Limited software, dTIMS, to analyze life-cycle costs for various rehabilitation strategies on each segment of roa...
Hybrid Broadband Ground-Motion Simulation Using Scenario Earthquakes for the Istanbul Area

KAUST Repository

Reshi, Owais A.

2016-04-13

Seismic design, analysis and retrofitting of structures demand an intensive assessment of potential ground motions in seismically active regions. Peak ground motions and frequency content of seismic excitations effectively influence the behavior of structures. In regions of sparse ground motion records, ground-motion simulations provide the synthetic seismic records, which not only provide insight into the mechanisms of earthquakes but also help in improving some aspects of earthquake engineering. Broadband ground-motion simulation methods typically utilize physics-based modeling of source and path effects at low frequencies coupled with high frequency semi-stochastic methods. I apply the hybrid simulation method by Mai et al. (2010) to model several scenario earthquakes in the Marmara Sea, an area of high seismic hazard. Simulated ground motions were generated at 75 stations using systematically calibrated model parameters. The region-specific source, path and site model parameters were calibrated by simulating a w4.1 Marmara Sea earthquake that occurred on November 16, 2015 on the fault segment in the vicinity of Istanbul. The calibrated parameters were then used to simulate the scenario earthquakes with magnitudes w6.0, w6.25, w6.5 and w6.75 over the Marmara Sea fault. Effects of fault geometry, hypocenter location, slip distribution and rupture propagation were thoroughly studied to understand variability in ground motions. A rigorous analysis of waveforms reveal that these parameters are critical for determining the behavior of ground motions especially in the near-field. Comparison of simulated ground motion intensities with ground-motion prediction quations indicates the need of development of the region-specific ground-motion prediction equation for Istanbul area. Peak ground motion maps are presented to illustrate the shaking in the Istanbul area due to the scenario earthquakes. The southern part of Istanbul including Princes Islands show high amplitudes
Automatic segmentation of vertebrae from radiographs

DEFF Research Database (Denmark)

Mysling, Peter; Petersen, Peter Kersten; Nielsen, Mads

2011-01-01

Segmentation of vertebral contours is an essential task in the design of automatic tools for vertebral fracture assessment. In this paper, we propose a novel segmentation technique which does not require operator interaction. The proposed technique solves the segmentation problem in a hierarchical...... is constrained by a conditional shape model, based on the variability of the coarse spine location estimates. The technique is evaluated on a data set of manually annotated lumbar radiographs. The results compare favorably to the previous work in automatic vertebra segmentation, in terms of both segmentation...
Fault geometry, rupture dynamics and ground motion from potential earthquakes on the North Anatolian Fault under the Sea of Marmara

KAUST Repository

Oglesby, David D.

2012-03-01

Using the 3-D finite-element method, we develop dynamic spontaneous rupture models of earthquakes on the North Anatolian Fault system in the Sea of Marmara, Turkey, considering the geometrical complexity of the fault system in this region. We find that the earthquake size, rupture propagation pattern and ground motion all strongly depend on the interplay between the initial (static) regional pre-stress field and the dynamic stress field radiated by the propagating rupture. By testing several nucleation locations, we observe that those far from an oblique normal fault stepover segment (near Istanbul) lead to large through-going rupture on the entire fault system, whereas nucleation locations closer to the stepover segment tend to produce ruptures that die out in the stepover. However, this pattern can change drastically with only a 10° rotation of the regional stress field. Our simulations also reveal that while dynamic unclamping near fault bends can produce a new mode of supershear rupture propagation, this unclamping has a much smaller effect on the speed of the peak in slip velocity along the fault. Finally, we find that the complex fault geometry leads to a very complex and asymmetric pattern of near-fault ground motion, including greatly amplified ground motion on the insides of fault bends. The ground-motion pattern can change significantly with different hypocentres, even beyond the typical effects of directivity. The results of this study may have implications for seismic hazard in this region, for the dynamics and ground motion of geometrically complex faults, and for the interpretation of kinematic inverse rupture models.
Fault geometry, rupture dynamics and ground motion from potential earthquakes on the North Anatolian Fault under the Sea of Marmara

KAUST Repository

Oglesby, David D.; Mai, Paul Martin

2012-01-01

Using the 3-D finite-element method, we develop dynamic spontaneous rupture models of earthquakes on the North Anatolian Fault system in the Sea of Marmara, Turkey, considering the geometrical complexity of the fault system in this region. We find that the earthquake size, rupture propagation pattern and ground motion all strongly depend on the interplay between the initial (static) regional pre-stress field and the dynamic stress field radiated by the propagating rupture. By testing several nucleation locations, we observe that those far from an oblique normal fault stepover segment (near Istanbul) lead to large through-going rupture on the entire fault system, whereas nucleation locations closer to the stepover segment tend to produce ruptures that die out in the stepover. However, this pattern can change drastically with only a 10° rotation of the regional stress field. Our simulations also reveal that while dynamic unclamping near fault bends can produce a new mode of supershear rupture propagation, this unclamping has a much smaller effect on the speed of the peak in slip velocity along the fault. Finally, we find that the complex fault geometry leads to a very complex and asymmetric pattern of near-fault ground motion, including greatly amplified ground motion on the insides of fault bends. The ground-motion pattern can change significantly with different hypocentres, even beyond the typical effects of directivity. The results of this study may have implications for seismic hazard in this region, for the dynamics and ground motion of geometrically complex faults, and for the interpretation of kinematic inverse rupture models.
A combined segmenting and non-segmenting approach to signal quality estimation for ambulatory photoplethysmography

International Nuclear Information System (INIS)

Wander, J D; Morris, D

2014-01-01

Continuous cardiac monitoring of healthy and unhealthy patients can help us understand the progression of heart disease and enable early treatment. Optical pulse sensing is an excellent candidate for continuous mobile monitoring of cardiovascular health indicators, but optical pulse signals are susceptible to corruption from a number of noise sources, including motion artifact. Therefore, before higher-level health indicators can be reliably computed, corrupted data must be separated from valid data. This is an especially difficult task in the presence of artifact caused by ambulation (e.g. walking or jogging), which shares significant spectral energy with the true pulsatile signal. In this manuscript, we present a machine-learning-based system for automated estimation of signal quality of optical pulse signals that performs well in the presence of periodic artifact. We hypothesized that signal processing methods that identified individual heart beats (segmenting approaches) would be more error-prone than methods that did not (non-segmenting approaches) when applied to data contaminated by periodic artifact. We further hypothesized that a fusion of segmenting and non-segmenting approaches would outperform either approach alone. Therefore, we developed a novel non-segmenting approach to signal quality estimation that we then utilized in combination with a traditional segmenting approach. Using this system we were able to robustly detect differences in signal quality as labeled by expert human raters (Pearson’s r = 0.9263). We then validated our original hypotheses by demonstrating that our non-segmenting approach outperformed the segmenting approach in the presence of contaminated signal, and that the combined system outperformed either individually. Lastly, as an example, we demonstrated the utility of our signal quality estimation system in evaluating the trustworthiness of heart rate measurements derived from optical pulse signals. (paper)
Rhythm-based segmentation of Popular Chinese Music

DEFF Research Database (Denmark)

Jensen, Karl Kristoffer

2005-01-01

We present a new method to segment popular music based on rhythm. By computing a shortest path based on the self-similarity matrix calculated from a model of rhythm, segmenting boundaries are found along the di- agonal of the matrix. The cost of a new segment is opti- mized by matching manual...... and automatic segment boundaries. We compile a small song database of 21 randomly selected popular Chinese songs which come from Chinese Mainland, Taiwan and Hong Kong. The segmenting results on the small corpus show that 78% manual segmentation points are detected and 74% auto- matic segmentation points...
Unsupervised Performance Evaluation of Image Segmentation

Directory of Open Access Journals (Sweden)

Chabrier Sebastien

2006-01-01

Full Text Available We present in this paper a study of unsupervised evaluation criteria that enable the quantification of the quality of an image segmentation result. These evaluation criteria compute some statistics for each region or class in a segmentation result. Such an evaluation criterion can be useful for different applications: the comparison of segmentation results, the automatic choice of the best fitted parameters of a segmentation method for a given image, or the definition of new segmentation methods by optimization. We first present the state of art of unsupervised evaluation, and then, we compare six unsupervised evaluation criteria. For this comparative study, we use a database composed of 8400 synthetic gray-level images segmented in four different ways. Vinet's measure (correct classification rate is used as an objective criterion to compare the behavior of the different criteria. Finally, we present the experimental results on the segmentation evaluation of a few gray-level natural images.
Methods of evaluating segmentation characteristics and segmentation of major faults

Energy Technology Data Exchange (ETDEWEB)

Lee, Kie Hwa; Chang, Tae Woo; Kyung, Jai Bok [Seoul National Univ., Seoul (Korea, Republic of)] (and others)

2000-03-15

Seismological, geological, and geophysical studies were made for reasonable segmentation of the Ulsan fault and the results are as follows. One- and two- dimensional electrical surveys revealed clearly the fault fracture zone enlarges systematically northward and southward from the vicinity of Mohwa-ri, indicating Mohwa-ri is at the seismic segment boundary. Field Geological survey and microscope observation of fault gouge indicates that the Quaternary faults in the area are reactivated products of the preexisting faults. Trench survey of the Chonbuk fault Galgok-ri revealed thrust faults and cumulative vertical displacement due to faulting during the late Quaternary with about 1.1-1.9 m displacement per event; the latest event occurred from 14000 to 25000 yrs. BP. The seismic survey showed the basement surface os cut by numerous reverse faults and indicated the possibility that the boundary between Kyeongsangbukdo and Kyeongsannamdo may be segment boundary.
Methods of evaluating segmentation characteristics and segmentation of major faults

International Nuclear Information System (INIS)

Lee, Kie Hwa; Chang, Tae Woo; Kyung, Jai Bok

2000-03-01

Seismological, geological, and geophysical studies were made for reasonable segmentation of the Ulsan fault and the results are as follows. One- and two- dimensional electrical surveys revealed clearly the fault fracture zone enlarges systematically northward and southward from the vicinity of Mohwa-ri, indicating Mohwa-ri is at the seismic segment boundary. Field Geological survey and microscope observation of fault gouge indicates that the Quaternary faults in the area are reactivated products of the preexisting faults. Trench survey of the Chonbuk fault Galgok-ri revealed thrust faults and cumulative vertical displacement due to faulting during the late Quaternary with about 1.1-1.9 m displacement per event; the latest event occurred from 14000 to 25000 yrs. BP. The seismic survey showed the basement surface os cut by numerous reverse faults and indicated the possibility that the boundary between Kyeongsangbukdo and Kyeongsannamdo may be segment boundary
A new framework for interactive images segmentation

International Nuclear Information System (INIS)

Ashraf, M.; Sarim, M.; Shaikh, A.B.

2017-01-01

Image segmentation has become a widely studied research problem in image processing. There exist different graph based solutions for interactive image segmentation but the domain of image segmentation still needs persistent improvements. The segmentation quality of existing techniques generally depends on the manual input provided in beginning, therefore, these algorithms may not produce quality segmentation with initial seed labels provided by a novice user. In this work we investigated the use of cellular automata in image segmentation and proposed a new algorithm that follows a cellular automaton in label propagation. It incorporates both the pixel's local and global information in the segmentation process. We introduced the novel global constraints in automata evolution rules; hence proposed scheme of automata evolution is more effective than the automata based earlier evolution schemes. Global constraints are also effective in deceasing the sensitivity towards small changes made in manual input; therefore proposed approach is less dependent on label seed marks. It can produce the quality segmentation with modest user efforts. Segmentation results indicate that the proposed algorithm performs better than the earlier segmentation techniques. (author)
Westinghouse experience in using mechanical cutting for reactor vessel internals segmentation

International Nuclear Information System (INIS)

Boucau, Joseph; Fallstroem, Stefan; Segerud, Per; Kreitman, Paul J.

2010-01-01

plants dismantled to date in the US have repackaged the less activated waste back into the reactor vessel and shipped the entire assembly to the disposal site. Decisions like these can be driven by many factors such as disposal costs, transportation logistics, licensing fees, etc., but will have a significant impact on the segmentation and packaging plan so must be considered early in the planning phase. All segmentation tools are remotely controlled since the mechanical segmentation projects that Westinghouse has executed, so far, have been performed under water due to the high radiation levels. ALARA and personal safety is the number one priority during the site work. The complexity of the work requires well designed and reliable tools. Westinghouse has optimized the technologies from its experiences accumulated over the years. Its main focus has always been to improve tool handling and cutting speed, water cleanliness, fail-safe and safety aspects. Different band saws, disc saws, tube cutters and shearing tools have been developed to cut the reactor internals. All of those equipments are hydraulically driven which is very suitable for submerged applications. The purpose of this paper will be to provide an overview of the Westinghouse mechanical segmentation process, based on actual experience from the work that has been completed to date. (authors)
Automated Segmentation of High-Resolution Photospheric Images of Active Regions

Science.gov (United States)

Yang, Meng; Tian, Yu; Rao, Changhui

2018-02-01

Due to the development of ground-based, large-aperture solar telescopes with adaptive optics (AO) resulting in increasing resolving ability, more accurate sunspot identifications and characterizations are required. In this article, we have developed a set of automated segmentation methods for high-resolution solar photospheric images. Firstly, a local-intensity-clustering level-set method is applied to roughly separate solar granulation and sunspots. Then reinitialization-free level-set evolution is adopted to adjust the boundaries of the photospheric patch; an adaptive intensity threshold is used to discriminate between umbra and penumbra; light bridges are selected according to their regional properties from candidates produced by morphological operations. The proposed method is applied to the solar high-resolution TiO 705.7-nm images taken by the 151-element AO system and Ground-Layer Adaptive Optics prototype system at the 1-m New Vacuum Solar Telescope of the Yunnan Observatory. Experimental results show that the method achieves satisfactory robustness and efficiency with low computational cost on high-resolution images. The method could also be applied to full-disk images, and the calculated sunspot areas correlate well with the data given by the National Oceanic and Atmospheric Administration (NOAA).

International EUREKA: Initialization Segment

International Nuclear Information System (INIS)

1982-02-01

The Initialization Segment creates the starting description of the uranium market. The starting description includes the international boundaries of trade, the geologic provinces, resources, reserves, production, uranium demand forecasts, and existing market transactions. The Initialization Segment is designed to accept information of various degrees of detail, depending on what is known about each region. It must transform this information into a specific data structure required by the Market Segment of the model, filling in gaps in the information through a predetermined sequence of defaults and built in assumptions. A principal function of the Initialization Segment is to create diagnostic messages indicating any inconsistencies in data and explaining which assumptions were used to organize the data base. This permits the user to manipulate the data base until such time the user is satisfied that all the assumptions used are reasonable and that any inconsistencies are resolved in a satisfactory manner
Image Segmentation Using Minimum Spanning Tree

Science.gov (United States)

Dewi, M. P.; Armiati, A.; Alvini, S.

2018-04-01

This research aim to segmented the digital image. The process of segmentation is to separate the object from the background. So the main object can be processed for the other purposes. Along with the development of technology in digital image processing application, the segmentation process becomes increasingly necessary. The segmented image which is the result of the segmentation process should accurate due to the next process need the interpretation of the information on the image. This article discussed the application of minimum spanning tree on graph in segmentation process of digital image. This method is able to separate an object from the background and the image will change to be the binary images. In this case, the object that being the focus is set in white, while the background is black or otherwise.
Preserved local but disrupted contextual figure-ground influences in an individual with abnormal function of intermediate visual areas

Science.gov (United States)

Brooks, Joseph L.; Gilaie-Dotan, Sharon; Rees, Geraint; Bentin, Shlomo; Driver, Jon

2012-01-01

Visual perception depends not only on local stimulus features but also on their relationship to the surrounding stimulus context, as evident in both local and contextual influences on figure-ground segmentation. Intermediate visual areas may play a role in such contextual influences, as we tested here by examining LG, a rare case of developmental visual agnosia. LG has no evident abnormality of brain structure and functional neuroimaging showed relatively normal V1 function, but his intermediate visual areas (V2/V3) function abnormally. We found that contextual influences on figure-ground organization were selectively disrupted in LG, while local sources of figure-ground influences were preserved. Effects of object knowledge and familiarity on figure-ground organization were also significantly diminished. Our results suggest that the mechanisms mediating contextual and familiarity influences on figure-ground organization are dissociable from those mediating local influences on figure-ground assignment. The disruption of contextual processing in intermediate visual areas may play a role in the substantial object recognition difficulties experienced by LG. PMID:22947116
TFTR grounding scheme and ground-monitor system

International Nuclear Information System (INIS)

Viola, M.

1983-01-01

The Tokamak Fusion Test Reactor (TFTR) grounding system utilizes a single-point ground. It is located directly under the machine, at the basement floor level, and is tied to the building perimeter ground. Wired to this single-point ground, via individual 500 MCM insulated cables, are: the vacuum vessel; four toroidal field coil cases/inner support structure quadrants; umbrella structure halves; the substructure ring girder; radial beams and columns; and the diagnostic systems. Prior to the first machine operation, a ground-loop removal program was initiated. It required insulation of all hangers and supports (within a 35-foot radius of the center of the machine) of the various piping, conduits, cable trays, and ventilation systems. A special ground-monitor system was designed and installed. It actively monitors each of the individual machine grounds to insure that there are no inadvertent ground loops within the machine structure or its ground and that the machine grounds are intact prior to each pulse. The TFTR grounding system has proven to be a very manageable system and one that is easy to maintain
An overview of the joint FAA/NASA aircraft/ground runway friction program

Science.gov (United States)

Yager, Thomas J.

1989-01-01

There is a need for information on runways which may become slippery due to various forms and types of contaminants. Experience has shown that since the beginning of all weather aircraft operations, there have been landing and aborted takeoff incidents and/or accidents each year where aircraft have either run off the end or veered off the shoulder of low friction runways. NASA Langley's Landing and Impact Dynamics Branch is involved in several research programs directed towards obtaining a better understanding of how different tire properties interact with varying pavement surface characteristics to produce acceptable performance for aircraft ground handling requirements. One such effort, which was jointly supported by not only NASA and the FAA but by several aviation industry groups including the Flight Safety Foundation, is described.
Mild toxic anterior segment syndrome mimicking delayed onset toxic anterior segment syndrome after cataract surgery

Directory of Open Access Journals (Sweden)

Su-Na Lee

2014-01-01

Full Text Available Toxic anterior segment syndrome (TASS is an acute sterile postoperative anterior segment inflammation that may occur after anterior segment surgery. I report herein a case that developed mild TASS in one eye after bilateral uneventful cataract surgery, which was masked during early postoperative period under steroid eye drop and mimicking delayed onset TASS after switching to weaker steroid eye drop.
TU-AB-303-07: Evaluation of Automatic Segmentation of Critical Structures for Head-And-Neck and Thoracic Radiotherapy Planning

International Nuclear Information System (INIS)

Yang, J; Balter, P; Court, L

2015-01-01

Purpose: To evaluate the performance of commercially available automatic segmentation tools built into treatment planning systems (TPS) in terms of their segmentation accuracy and flexibility in customization. Methods: Twelve head-and-neck cancer patients and twelve thoracic cancer patients were retrospectively selected to benchmark the model-based segmentation (MBS) and atlas-based segmentation (ABS) in RayStation TPS and the Smart Probabilistic Image Contouring Engine (SPICE) in Pinnacle TPS. Multi-atlas contouring service (MACS) that was developed in-house as a plug-in of Pinnacle TPS was evaluated as well. Manual contours used in clinic were reviewed and modified for consistency and served as ground truth for the evaluation. Head-and-neck evaluation included six regions of interest (ROIs): left and right parotid glands, brainstem, spinal cord, mandible, and submandibular glands. Thoracic evaluation includes seven ROIs: left and right lungs, spinal cord, heart, esophagus, and left and right brachial plexus. Auto-segmented contours were compared with the manual contours using the Dice similarity coefficient (DSC) and the mean surface distance (MSD). Results: In head- and-neck evaluation, only mandible has a high accuracy in all segmentations (DSC>85%); SPICE achieved DSC>70% for parotid glands; MACS achieved this for both parotid glands and submandibular glands; and RayStation ABS achieved this for spinal cord. In thoracic evaluation, SPICE achieved the best in lung and heart segmentation, while MACS achieved the best for all other structures. The less distinguishable structures on CT images, such as brainstem, spinal cord, parotid glands, submandibular glands, esophagus, and brachial plexus, showed great variability in different segmentation tools (mostly DSC<70% and MSD>3mm). The template for RayStation ABS can be easily customized by users, while RayStation MBS and SPICE rely on the vendors to provide the templates/models. Conclusion: Great variability was
TU-AB-303-07: Evaluation of Automatic Segmentation of Critical Structures for Head-And-Neck and Thoracic Radiotherapy Planning

Energy Technology Data Exchange (ETDEWEB)

Yang, J; Balter, P; Court, L [MD Anderson Cancer Center, Houston, TX (United States)

2015-06-15

Purpose: To evaluate the performance of commercially available automatic segmentation tools built into treatment planning systems (TPS) in terms of their segmentation accuracy and flexibility in customization. Methods: Twelve head-and-neck cancer patients and twelve thoracic cancer patients were retrospectively selected to benchmark the model-based segmentation (MBS) and atlas-based segmentation (ABS) in RayStation TPS and the Smart Probabilistic Image Contouring Engine (SPICE) in Pinnacle TPS. Multi-atlas contouring service (MACS) that was developed in-house as a plug-in of Pinnacle TPS was evaluated as well. Manual contours used in clinic were reviewed and modified for consistency and served as ground truth for the evaluation. Head-and-neck evaluation included six regions of interest (ROIs): left and right parotid glands, brainstem, spinal cord, mandible, and submandibular glands. Thoracic evaluation includes seven ROIs: left and right lungs, spinal cord, heart, esophagus, and left and right brachial plexus. Auto-segmented contours were compared with the manual contours using the Dice similarity coefficient (DSC) and the mean surface distance (MSD). Results: In head- and-neck evaluation, only mandible has a high accuracy in all segmentations (DSC>85%); SPICE achieved DSC>70% for parotid glands; MACS achieved this for both parotid glands and submandibular glands; and RayStation ABS achieved this for spinal cord. In thoracic evaluation, SPICE achieved the best in lung and heart segmentation, while MACS achieved the best for all other structures. The less distinguishable structures on CT images, such as brainstem, spinal cord, parotid glands, submandibular glands, esophagus, and brachial plexus, showed great variability in different segmentation tools (mostly DSC<70% and MSD>3mm). The template for RayStation ABS can be easily customized by users, while RayStation MBS and SPICE rely on the vendors to provide the templates/models. Conclusion: Great variability was
Sustainable ground transportation – review of technologies, challenges and opportunities

Energy Technology Data Exchange (ETDEWEB)

Agarwal, Ramesh K. [Department of Mechanical Engineering and Materials Science, Washington University, St. Louis, MO 63130 (United States)

2013-07-01

Currently there are nearly 750 million ground vehicles in service worldwide. They are responsible for 50% of petroleum (oil) consumption and 60% of all greenhouse gas (GHG) emissions worldwide. The number of vehicles is forecasted to double by 2050. Therefore the environmental issues such as noise, emissions and fuel burn have become important for energy and environmental sustainability. This paper provides an overview of specific energy and environmental issues related to ground transportation. The technologies related to reduction in energy requirements such as reducing the vehicle mass by using the high strength low weight materials and reducing the viscous drag by active flow control and smoothing the operational profile, and reducing the contact friction by special tire materials are discussed along with the portable energy sources for reducing the GHG emissions such as low carbon fuels (biofuels), Lithium-ion batteries with high energy density and stability, and fuel cells. The technological challenges and opportunities for innovations are discussed.
Scorpion image segmentation system

Science.gov (United States)

Joseph, E.; Aibinu, A. M.; Sadiq, B. A.; Bello Salau, H.; Salami, M. J. E.

2013-12-01

Death as a result of scorpion sting has been a major public health problem in developing countries. Despite the high rate of death as a result of scorpion sting, little report exists in literature of intelligent device and system for automatic detection of scorpion. This paper proposed a digital image processing approach based on the floresencing characteristics of Scorpion under Ultra-violet (UV) light for automatic detection and identification of scorpion. The acquired UV-based images undergo pre-processing to equalize uneven illumination and colour space channel separation. The extracted channels are then segmented into two non-overlapping classes. It has been observed that simple thresholding of the green channel of the acquired RGB UV-based image is sufficient for segmenting Scorpion from other background components in the acquired image. Two approaches to image segmentation have also been proposed in this work, namely, the simple average segmentation technique and K-means image segmentation. The proposed algorithm has been tested on over 40 UV scorpion images obtained from different part of the world and results obtained show an average accuracy of 97.7% in correctly classifying the pixel into two non-overlapping clusters. The proposed 1system will eliminate the problem associated with some of the existing manual approaches presently in use for scorpion detection.
Evaluation and comparison of current fetal ultrasound image segmentation methods for biometric measurements: a grand challenge.

Science.gov (United States)

Rueda, Sylvia; Fathima, Sana; Knight, Caroline L; Yaqub, Mohammad; Papageorghiou, Aris T; Rahmatullah, Bahbibi; Foi, Alessandro; Maggioni, Matteo; Pepe, Antonietta; Tohka, Jussi; Stebbing, Richard V; McManigle, John E; Ciurte, Anca; Bresson, Xavier; Cuadra, Meritxell Bach; Sun, Changming; Ponomarev, Gennady V; Gelfand, Mikhail S; Kazanov, Marat D; Wang, Ching-Wei; Chen, Hsiang-Chou; Peng, Chun-Wei; Hung, Chu-Mei; Noble, J Alison

2014-04-01

This paper presents the evaluation results of the methods submitted to Challenge US: Biometric Measurements from Fetal Ultrasound Images, a segmentation challenge held at the IEEE International Symposium on Biomedical Imaging 2012. The challenge was set to compare and evaluate current fetal ultrasound image segmentation methods. It consisted of automatically segmenting fetal anatomical structures to measure standard obstetric biometric parameters, from 2D fetal ultrasound images taken on fetuses at different gestational ages (21 weeks, 28 weeks, and 33 weeks) and with varying image quality to reflect data encountered in real clinical environments. Four independent sub-challenges were proposed, according to the objects of interest measured in clinical practice: abdomen, head, femur, and whole fetus. Five teams participated in the head sub-challenge and two teams in the femur sub-challenge, including one team who tackled both. Nobody attempted the abdomen and whole fetus sub-challenges. The challenge goals were two-fold and the participants were asked to submit the segmentation results as well as the measurements derived from the segmented objects. Extensive quantitative (region-based, distance-based, and Bland-Altman measurements) and qualitative evaluation was performed to compare the results from a representative selection of current methods submitted to the challenge. Several experts (three for the head sub-challenge and two for the femur sub-challenge), with different degrees of expertise, manually delineated the objects of interest to define the ground truth used within the evaluation framework. For the head sub-challenge, several groups produced results that could be potentially used in clinical settings, with comparable performance to manual delineations. The femur sub-challenge had inferior performance to the head sub-challenge due to the fact that it is a harder segmentation problem and that the techniques presented relied more on the femur's appearance.
Brain Tumor Image Segmentation in MRI Image

Science.gov (United States)

Peni Agustin Tjahyaningtijas, Hapsari

2018-04-01

Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient’s life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.
Colour application on mammography image segmentation

Science.gov (United States)

Embong, R.; Aziz, N. M. Nik Ab.; Karim, A. H. Abd; Ibrahim, M. R.

2017-09-01

The segmentation process is one of the most important steps in image processing and computer vision since it is vital in the initial stage of image analysis. Segmentation of medical images involves complex structures and it requires precise segmentation result which is necessary for clinical diagnosis such as the detection of tumour, oedema, and necrotic tissues. Since mammography images are grayscale, researchers are looking at the effect of colour in the segmentation process of medical images. Colour is known to play a significant role in the perception of object boundaries in non-medical colour images. Processing colour images require handling more data, hence providing a richer description of objects in the scene. Colour images contain ten percent (10%) additional edge information as compared to their grayscale counterparts. Nevertheless, edge detection in colour image is more challenging than grayscale image as colour space is considered as a vector space. In this study, we implemented red, green, yellow, and blue colour maps to grayscale mammography images with the purpose of testing the effect of colours on the segmentation of abnormality regions in the mammography images. We applied the segmentation process using the Fuzzy C-means algorithm and evaluated the percentage of average relative error of area for each colour type. The results showed that all segmentation with the colour map can be done successfully even for blurred and noisy images. Also the size of the area of the abnormality region is reduced when compare to the segmentation area without the colour map. The green colour map segmentation produced the smallest percentage of average relative error (10.009%) while yellow colour map segmentation gave the largest percentage of relative error (11.367%).
What are Segments in Google Analytics

Science.gov (United States)

Segments find all sessions that meet a specific condition. You can then apply this segment to any report in Google Analytics (GA). Segments are a way of identifying sessions and users while filters identify specific events, like pageviews.
Ground Motion Analysis of Co-Located DAS and Seismometer Sensors

Science.gov (United States)

Wang, H. F.; Fratta, D.; Lord, N. E.; Lancelle, C.; Thurber, C. H.; Zeng, X.; Parker, L.; Chalari, A.; Miller, D.; Feigl, K. L.; Team, P.

2016-12-01

The PoroTomo research team deployed 8700-meters of Distributed Acoustic Sensing (DAS) cable in a shallow trench and 400-meters in a borehole at Brady Hot Springs, Nevada in March 2016 together with an array of 246, three-component geophones. The seismic sensors occupied a natural laboratory 1500 x 500 x 400 meters overlying the Brady geothermal field. The DAS cable was laid out in three parallel zig-zag lines with line segments approximately 100-meters in length and geophones were spaced at approximately 50-m intervals. In several line segments, geophones were co-located within one meter of the DAS cable. Both DAS and the conventional geophones recorded continuously over 15 days. A large Vibroseis truck (T-Rex) provided the seismic source at approximately 250 locations outside and within the array. The Vibroseis protocol called for excitation in one vertical and two orthogonal horizontal directions at each location. For each mode, three, 5-to-80-Hz upsweeps were made over 20 seconds. In addition, a moderate-sized earthquake with a local magnitude of 4.3 was recorded on March 21, 2016. Its epicenter was approximately 150-km away. Several DAS line segments with co-located geophone stations were used to test relationships between the strain rate recorded by DAS and ground velocity recorded by the geophones.
Segmentation-less Digital Rock Physics

Science.gov (United States)

Tisato, N.; Ikeda, K.; Goldfarb, E. J.; Spikes, K. T.

2017-12-01

In the last decade, Digital Rock Physics (DRP) has become an avenue to investigate physical and mechanical properties of geomaterials. DRP offers the advantage of simulating laboratory experiments on numerical samples that are obtained from analytical methods. Potentially, DRP could allow sparing part of the time and resources that are allocated to perform complicated laboratory tests. Like classic laboratory tests, the goal of DRP is to estimate accurately physical properties of rocks like hydraulic permeability or elastic moduli. Nevertheless, the physical properties of samples imaged using micro-computed tomography (μCT) are estimated through segmentation of the μCT dataset. Segmentation proves to be a challenging and arbitrary procedure that typically leads to inaccurate estimates of physical properties. Here we present a novel technique to extract physical properties from a μCT dataset without the use of segmentation. We show examples in which we use segmentation-less method to simulate elastic wave propagation and pressure wave diffusion to estimate elastic properties and permeability, respectively. The proposed method takes advantage of effective medium theories and uses the density and the porosity that are measured in the laboratory to constrain the results. We discuss the results and highlight that segmentation-less DRP is more accurate than segmentation based DRP approaches and theoretical modeling for the studied rock. In conclusion, the segmentation-less approach here presented seems to be a promising method to improve accuracy and to ease the overall workflow of DRP.
Automatic training and reliability estimation for 3D ASM applied to cardiac MRI segmentation.

Science.gov (United States)

Tobon-Gomez, Catalina; Sukno, Federico M; Butakoff, Constantine; Huguet, Marina; Frangi, Alejandro F

2012-07-07

Training active shape models requires collecting manual ground-truth meshes in a large image database. While shape information can be reused across multiple imaging modalities, intensity information needs to be imaging modality and protocol specific. In this context, this study has two main purposes: (1) to test the potential of using intensity models learned from MRI simulated datasets and (2) to test the potential of including a measure of reliability during the matching process to increase robustness. We used a population of 400 virtual subjects (XCAT phantom), and two clinical populations of 40 and 45 subjects. Virtual subjects were used to generate simulated datasets (MRISIM simulator). Intensity models were trained both on simulated and real datasets. The trained models were used to segment the left ventricle (LV) and right ventricle (RV) from real datasets. Segmentations were also obtained with and without reliability information. Performance was evaluated with point-to-surface and volume errors. Simulated intensity models obtained average accuracy comparable to inter-observer variability for LV segmentation. The inclusion of reliability information reduced volume errors in hypertrophic patients (EF errors from 17 ± 57% to 10 ± 18%; LV MASS errors from -27 ± 22 g to -14 ± 25 g), and in heart failure patients (EF errors from -8 ± 42% to -5 ± 14%). The RV model of the simulated images needs further improvement to better resemble image intensities around the myocardial edges. Both for real and simulated models, reliability information increased segmentation robustness without penalizing accuracy.
Segmentation, advertising and prices

NARCIS (Netherlands)

Galeotti, Andrea; Moraga González, José

This paper explores the implications of market segmentation on firm competitiveness. In contrast to earlier work, here market segmentation is minimal in the sense that it is based on consumer attributes that are completely unrelated to tastes. We show that when the market is comprised by two
Chromosome condensation and segmentation

International Nuclear Information System (INIS)

Viegas-Pequignot, E.M.

1981-01-01

Some aspects of chromosome condensation in mammalians -humans especially- were studied by means of cytogenetic techniques of chromosome banding. Two further approaches were adopted: a study of normal condensation as early as prophase, and an analysis of chromosome segmentation induced by physical (temperature and γ-rays) or chemical agents (base analogues, antibiotics, ...) in order to show out the factors liable to affect condensation. Here 'segmentation' means an abnormal chromosome condensation appearing systematically and being reproducible. The study of normal condensation was made possible by the development of a technique based on cell synchronization by thymidine and giving prophasic and prometaphasic cells. Besides, the possibility of inducing R-banding segmentations on these cells by BrdU (5-bromodeoxyuridine) allowed a much finer analysis of karyotypes. Another technique was developed using 5-ACR (5-azacytidine), it allowed to induce a segmentation similar to the one obtained using BrdU and identify heterochromatic areas rich in G-C bases pairs [fr
Experimental evaluation of ALS point cloud ground extraction over different land cover in the Malopolska Province

Science.gov (United States)

Korzeniowska, Karolina; Mandlburger, Gottfried; Klimczyk, Agata

2013-04-01

The paper presents an evaluation of different terrain point extraction algorithms for Airborne Laser Scanning (ALS) point clouds. The research area covers eight test sites in the Małopolska Province (Poland) with varying point density between 3-15points/m² and surface as well as land cover characteristics. In this paper the existing implementations of algorithms were considered. Approaches based on mathematical morphology, progressive densification, robust surface interpolation and segmentation were compared. From the group of morphological filters, the Progressive Morphological Filter (PMF) proposed by Zhang K. et al. (2003) in LIS software was evaluated. From the progressive densification filter methods developed by Axelsson P. (2000) the Martin Isenburg's implementation in LAStools software (LAStools, 2012) was chosen. The third group of methods are surface-based filters. In this study, we used the hierarchic robust interpolation approach by Kraus K., Pfeifer N. (1998) as implemented in SCOP++ (Trimble, 2012). The fourth group of methods works on segmentation. From this filtering concept the segmentation algorithm available in LIS was tested (Wichmann V., 2012). The main aim in executing the automatic classification for ground extraction was operating in default mode or with default parameters which were selected by the developers of the algorithms. It was assumed that the default settings were equivalent to the parameters on which the best results can be achieved. In case it was not possible to apply an algorithm in default mode, a combination of the available and most crucial parameters for ground extraction were selected. As a result of these analyses, several output LAS files with different ground classification were achieved. The results were described on the basis of qualitative and quantitative analyses, both being in a formal description. The classification differences were verified on point cloud data. Qualitative verification of ground extraction was

FLAIR lesion segmentation: Application in patients with brain tumors and acute ischemic stroke

International Nuclear Information System (INIS)

Artzi, Moran; Aizenstein, Orna; Jonas-Kimchi, Tali; Myers, Vicki; Hallevi, Hen; Ben Bashat, Dafna

2013-01-01

Background: Lesion size in fluid attenuation inversion recovery (FLAIR) images is an important clinical parameter for patient assessment and follow-up. Although manual delineation of lesion areas considered as ground truth, it is time-consuming, highly user-dependent and difficult to perform in areas of indistinct borders. In this study, an automatic methodology for FLAIR lesion segmentation is proposed, and its application in patients with brain tumors undergoing therapy; and in patients following stroke is demonstrated. Materials and methods: FLAIR lesion segmentation was performed in 57 magnetic resonance imaging (MRI) data sets obtained from 44 patients: 28 patients with primary brain tumors; 5 patients with recurrent-progressive glioblastoma (rGB) who were scanned longitudinally during anti-angiogenic therapy (18 MRI scans); and 11 patients following ischemic stroke. Results: FLAIR lesion segmentation was obtained in all patients. When compared to manual delineation, a high visual similarity was observed, with an absolute relative volume difference of 16.80% and 20.96% and a volumetric overlap error of 24.87% and 27.50% obtained for two raters: accepted values for automatic methods. Quantitative measurements of the segmented lesion volumes were in line with qualitative radiological assessment in four patients who received anti-anogiogenic drugs. In stroke patients the proposed methodology enabled identification of the ischemic lesion and differentiation from other FLAIR hyperintense areas, such as pre-existing disease. Conclusion: This study proposed a replicable methodology for FLAIR lesion detection and quantification and for discrimination between lesion of interest and pre-existing disease. Results from this study show the wide clinical applications of this methodology in research and clinical practice
FLAIR lesion segmentation: Application in patients with brain tumors and acute ischemic stroke

Energy Technology Data Exchange (ETDEWEB)

Artzi, Moran, E-mail: artzimy@gmail.com [The Functional Brain Center, The Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv (Israel); Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv (Israel); Aizenstein, Orna, E-mail: ornaaize@gmail.com [The Functional Brain Center, The Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv (Israel); Jonas-Kimchi, Tali, E-mail: talijk@tlvmc.gov.il [Radiology Department, Tel Aviv Sourasky Medical Center, Tel Aviv (Israel); Myers, Vicki, E-mail: vicki_myers@hotmail.com [The Functional Brain Center, The Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv (Israel); Hallevi, Hen, E-mail: hen.hallevi@gmail.com [Neurology Department, Tel Aviv Sourasky Medical Center, Tel Aviv (Israel); Ben Bashat, Dafna, E-mail: dafnab@tlvmc.gov.il [The Functional Brain Center, The Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv (Israel); Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv (Israel)

2013-09-15

Background: Lesion size in fluid attenuation inversion recovery (FLAIR) images is an important clinical parameter for patient assessment and follow-up. Although manual delineation of lesion areas considered as ground truth, it is time-consuming, highly user-dependent and difficult to perform in areas of indistinct borders. In this study, an automatic methodology for FLAIR lesion segmentation is proposed, and its application in patients with brain tumors undergoing therapy; and in patients following stroke is demonstrated. Materials and methods: FLAIR lesion segmentation was performed in 57 magnetic resonance imaging (MRI) data sets obtained from 44 patients: 28 patients with primary brain tumors; 5 patients with recurrent-progressive glioblastoma (rGB) who were scanned longitudinally during anti-angiogenic therapy (18 MRI scans); and 11 patients following ischemic stroke. Results: FLAIR lesion segmentation was obtained in all patients. When compared to manual delineation, a high visual similarity was observed, with an absolute relative volume difference of 16.80% and 20.96% and a volumetric overlap error of 24.87% and 27.50% obtained for two raters: accepted values for automatic methods. Quantitative measurements of the segmented lesion volumes were in line with qualitative radiological assessment in four patients who received anti-anogiogenic drugs. In stroke patients the proposed methodology enabled identification of the ischemic lesion and differentiation from other FLAIR hyperintense areas, such as pre-existing disease. Conclusion: This study proposed a replicable methodology for FLAIR lesion detection and quantification and for discrimination between lesion of interest and pre-existing disease. Results from this study show the wide clinical applications of this methodology in research and clinical practice.
Fully automated chest wall line segmentation in breast MRI by using context information

Science.gov (United States)

Wu, Shandong; Weinstein, Susan P.; Conant, Emily F.; Localio, A. Russell; Schnall, Mitchell D.; Kontos, Despina

2012-03-01

Breast MRI has emerged as an effective modality for the clinical management of breast cancer. Evidence suggests that computer-aided applications can further improve the diagnostic accuracy of breast MRI. A critical and challenging first step for automated breast MRI analysis, is to separate the breast as an organ from the chest wall. Manual segmentation or user-assisted interactive tools are inefficient, tedious, and error-prone, which is prohibitively impractical for processing large amounts of data from clinical trials. To address this challenge, we developed a fully automated and robust computerized segmentation method that intensively utilizes context information of breast MR imaging and the breast tissue's morphological characteristics to accurately delineate the breast and chest wall boundary. A critical component is the joint application of anisotropic diffusion and bilateral image filtering to enhance the edge that corresponds to the chest wall line (CWL) and to reduce the effect of adjacent non-CWL tissues. A CWL voting algorithm is proposed based on CWL candidates yielded from multiple sequential MRI slices, in which a CWL representative is generated and used through a dynamic time warping (DTW) algorithm to filter out inferior candidates, leaving the optimal one. Our method is validated by a representative dataset of 20 3D unilateral breast MRI scans that span the full range of the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) fibroglandular density categorization. A promising performance (average overlay percentage of 89.33%) is observed when the automated segmentation is compared to manually segmented ground truth obtained by an experienced breast imaging radiologist. The automated method runs time-efficiently at ~3 minutes for each breast MR image set (28 slices).
Track segment synthesis method for NTA film

International Nuclear Information System (INIS)

Kumazawa, Shigeru

1980-03-01

A method is presented for synthesizing track segments extracted from a gray-level digital picture of NTA film in automatic counting system. In order to detect each track in an arbitrary direction, even if it has some gaps, as a set of the track segments, the method links extracted segments along the track, in succession, to the linked track segments, according to whether each extracted segment bears a similarity of direction to the track or not and whether it is connected with the linked track segments or not. In the case of a large digital picture, the method is applied to each subpicture, which is a strip of the picture, and then concatenates subsets of track segments linked at each subpicture as a set of track segments belonging to a track. The method was applied to detecting tracks in various directions over the eight 364 x 40-pixel subpictures with the gray scale of 127/pixel (picture element) of the microphotograph of NTA film. It was proved to be able to synthesize track segments correctly for every track in the picture. (author)
Video Object Segmentation through Spatially Accurate and Temporally Dense Extraction of Primary Object Regions (Open Access)

Science.gov (United States)

2013-10-03

fol- low the setup in the literature ([13, 14]), and use 5 (birdfall, cheetah , girl, monkeydog and parachute) of the videos for evaluation (since the...segmentation labeling results of the method, GT is the ground-truth labeling of the video, and F is the (a) Birdfall (b) Cheetah (c) Girl (d) Monkeydog...Video Ours [14] [13] [20] [6] birdfall 155 189 288 252 454 cheetah 633 806 905 1142 1217 girl 1488 1698 1785 1304 1755 monkeydog 365 472 521 563 683
Groundwater Storage Changes in China from Satellite Gravity: An Overview

Directory of Open Access Journals (Sweden)

Wei Feng

2018-04-01

Full Text Available Groundwater plays a critical role in the global water cycle and is the drinking source for almost half of the world’s population. However, exact quantification of its storage change remains elusive due primarily to limited ground observations in space and time. The Gravity Recovery and Climate Experiment (GRACE twin-satellite data have provided global observations of water storage variations at monthly sampling for over a decade and a half, and is enable to estimate changes in groundwater storage (GWS after removing other water storage components using auxiliary datasets and models. In this paper, we present an overview of GWS changes in three main aquifers within China using GRACE data, and conduct a comprehensive accuracy assessment using in situ ground well observations and hydrological models. GRACE detects a significant GWS depletion rate of 7.2 ± 1.1 km3/yr in the North China Plain (NCP during 2002–2014, consistent with ground well observations and model predictions. The Liaohe River Basin (LRB experienced a pronounced GWS decline during 2005–2009, at a depletion rate of 5.0 ± 1.2 km3/yr. Since 2010, GRACE-based GWS reveal a slow recovery in the LRB, with excellent agreement with ground well observations. For the whole study period 2002–2014, no significant long-term GWS depletion is found in the LRB nor in the Tarim Basin. A case study in the Inner Tibetan Plateau highlights there still exist large uncertainties in GRACE-based GWS change estimates.
LIFE-STYLE SEGMENTATION WITH TAILORED INTERVIEWING

NARCIS (Netherlands)

KAMAKURA, WA; WEDEL, M

The authors present a tailored interviewing procedure for life-style segmentation. The procedure assumes that a life-style measurement instrument has been designed. A classification of a sample of consumers into life-style segments is obtained using a latent-class model. With these segments, the
Segmented rail linear induction motor

Science.gov (United States)

Cowan, Jr., Maynard; Marder, Barry M.

1996-01-01

A segmented rail linear induction motor has a segmented rail consisting of a plurality of nonferrous electrically conductive segments aligned along a guideway. The motor further includes a carriage including at least one pair of opposed coils fastened to the carriage for moving the carriage. A power source applies an electric current to the coils to induce currents in the conductive surfaces to repel the coils from adjacent edges of the conductive surfaces.
Thigh muscle segmentation of chemical shift encoding-based water-fat magnetic resonance images: The reference database MyoSegmenTUM.

Directory of Open Access Journals (Sweden)

Sarah Schlaeger

Full Text Available Magnetic resonance imaging (MRI can non-invasively assess muscle anatomy, exercise effects and pathologies with different underlying causes such as neuromuscular diseases (NMD. Quantitative MRI including fat fraction mapping using chemical shift encoding-based water-fat MRI has emerged for reliable determination of muscle volume and fat composition. The data analysis of water-fat images requires segmentation of the different muscles which has been mainly performed manually in the past and is a very time consuming process, currently limiting the clinical applicability. An automatization of the segmentation process would lead to a more time-efficient analysis. In the present work, the manually segmented thigh magnetic resonance imaging database MyoSegmenTUM is presented. It hosts water-fat MR images of both thighs of 15 healthy subjects and 4 patients with NMD with a voxel size of 3.2x2x4 mm3 with the corresponding segmentation masks for four functional muscle groups: quadriceps femoris, sartorius, gracilis, hamstrings. The database is freely accessible online at https://osf.io/svwa7/?view_only=c2c980c17b3a40fca35d088a3cdd83e2. The database is mainly meant as ground truth which can be used as training and test dataset for automatic muscle segmentation algorithms. The segmentation allows extraction of muscle cross sectional area (CSA and volume. Proton density fat fraction (PDFF of the defined muscle groups from the corresponding images and quadriceps muscle strength measurements/neurological muscle strength rating can be used for benchmarking purposes.
A Novel Approach for Bi-Level Segmentation of Tuberculosis Bacilli Based on Meta-Heuristic Algorithms

Directory of Open Access Journals (Sweden)

AYAS, S.

2018-02-01

Full Text Available Image thresholding is the most crucial step in microscopic image analysis to distinguish bacilli objects causing of tuberculosis disease. Therefore, several bi-level thresholding algorithms are widely used to increase the bacilli segmentation accuracy. However, bi-level microscopic image thresholding problem has not been solved using optimization algorithms. This paper introduces a novel approach for the segmentation problem using heuristic algorithms and presents visual and quantitative comparisons of heuristic and state-of-art thresholding algorithms. In this study, well-known heuristic algorithms such as Firefly Algorithm, Particle Swarm Optimization, Cuckoo Search, Flower Pollination are used to solve bi-level microscopic image thresholding problem, and the results are compared with the state-of-art thresholding algorithms such as K-Means, Fuzzy C-Means, Fast Marching. Kapur's entropy is chosen as the entropy measure to be maximized. Experiments are performed to make comparisons in terms of evaluation metrics and execution time. The quantitative results are calculated based on ground truth segmentation. According to the visual results, heuristic algorithms have better performance and the quantitative results are in accord with the visual results. Furthermore, experimental time comparisons show the superiority and effectiveness of the heuristic algorithms over traditional thresholding algorithms.
Deformable segmentation via sparse shape representation.

Science.gov (United States)

Zhang, Shaoting; Zhan, Yiqiang; Dewan, Maneesh; Huang, Junzhou; Metaxas, Dimitris N; Zhou, Xiang Sean

2011-01-01

Appearance and shape are two key elements exploited in medical image segmentation. However, in some medical image analysis tasks, appearance cues are weak/misleading due to disease/artifacts and often lead to erroneous segmentation. In this paper, a novel deformable model is proposed for robust segmentation in the presence of weak/misleading appearance cues. Owing to the less trustable appearance information, this method focuses on the effective shape modeling with two contributions. First, a shape composition method is designed to incorporate shape prior on-the-fly. Based on two sparsity observations, this method is robust to false appearance information and adaptive to statistically insignificant shape modes. Second, shape priors are modeled and used in a hierarchical fashion. More specifically, by using affinity propagation method, our deformable surface is divided into multiple partitions, on which local shape models are built independently. This scheme facilitates a more compact shape prior modeling and hence a more robust and efficient segmentation. Our deformable model is applied on two very diverse segmentation problems, liver segmentation in PET-CT images and rodent brain segmentation in MR images. Compared to state-of-art methods, our method achieves better performance in both studies.
Segmenting hospitals for improved management strategy.

Science.gov (United States)

Malhotra, N K

1989-09-01

The author presents a conceptual framework for the a priori and clustering-based approaches to segmentation and evaluates them in the context of segmenting institutional health care markets. An empirical study is reported in which the hospital market is segmented on three state-of-being variables. The segmentation approach also takes into account important organizational decision-making variables. The sophisticated Thurstone Case V procedure is employed. Several marketing implications for hospitals, other health care organizations, hospital suppliers, and donor publics are identified.
Segmentation and Classification of Nepal Earthquake Induced Landslides Using SENTINEL-1 Product

Science.gov (United States)

Kunwar, Saket

2016-06-01

On April 26, 2015, an earthquake of magnitude 7.8 on the Richter scale occurred, with epicentre at Barpak (28°12'20''N,84°44'19''E), Nepal. Landslides induced due to the earthquake and its aftershock added to the natural disaster claiming more than 9000 lives. Landslides represented as lines that extend from the head scarp to the toe of the deposit were mapped by the staff of the British Geological Survey and is available freely under Open Data Commons Open Database License(ODC-ODbL) license at the Humanitarian Data Exchange Program. This collection of 5578 landslides is used as preliminary ground truth in this study with the aim of producing polygonal delineation of the landslides from the polylines via object oriented segmentation. Texture measures from Sentinel-1a Ground Range Detected (GRD) Amplitude data and eigenvalue-decomposed Single Look Complex (SLC) polarimetry product are stacked for this purpose. This has also enabled the investigation of landslide properties in the H-Alpha plane, while developing a classification mechanism for identifying the occurrence of landslides.
Polyether based segmented copolymers with uniform aramid units

NARCIS (Netherlands)

Niesten, M.C.E.J.

2000-01-01

Segmented copolymers with short, glassy or crystalline hard segments and long, amorphous soft segments (multi-block copolymers) are thermoplastic elastomers (TPE’s). The hard segments form physical crosslinks for the amorphous (rubbery) soft segments. As a result, this type of materials combines
Market Segmentation from a Behavioral Perspective

Science.gov (United States)

Wells, Victoria K.; Chang, Shing Wan; Oliveira-Castro, Jorge; Pallister, John

2010-01-01

A segmentation approach is presented using both traditional demographic segmentation bases (age, social class/occupation, and working status) and a segmentation by benefits sought. The benefits sought in this case are utilitarian and informational reinforcement, variables developed from the Behavioral Perspective Model (BPM). Using data from 1,847…
Skip segment Hirschsprung disease and Waardenburg syndrome

OpenAIRE

Gross, Erica R.; Geddes, Gabrielle C.; McCarrier, Julie A.; Jarzembowski, Jason A.; Arca, Marjorie J.

2015-01-01

Skip segment Hirschsprung disease describes a segment of ganglionated bowel between two segments of aganglionated bowel. It is a rare phenomenon that is difficult to diagnose. We describe a recent case of skip segment Hirschsprung disease in a neonate with a family history of Waardenburg syndrome and the genetic profile that was identified.
Rock characterization while drilling and application of roof bolter drilling data for evaluation of ground conditions

Directory of Open Access Journals (Sweden)

Jamal Rostami

2015-06-01

Full Text Available Despite recent advances in mine health and safety, roof collapse and instabilities are still the leading causes of injury and fatality in underground mining operations. Improving safety and optimum design of ground support requires good and reliable ground characterization. While many geophysical methods have been developed for ground characterizations, their accuracy is insufficient for customized ground support design of underground workings. The actual measurements on the samples of the roof and wall strata from the exploration boring are reliable but the related holes are far apart, thus unsuitable for design purposes. The best source of information could be the geological back mapping of the roof and walls, but this is disruptive to mining operations, and provided information is only from rock surface. Interpretation of the data obtained from roof bolt drilling can offer a good and reliable source of information that can be used for ground characterization and ground support design and evaluations. This paper offers a brief review of the mine roof characterization methods, followed by introduction and discussion of the roof characterization methods by instrumented roof bolters. A brief overview of the results of the preliminary study and initial testing on an instrumented drill and summary of the suggested improvements are also discussed.
Correlates between kinematics and baropodometric measurements for an integrated in-vivo assessment of the segmental foot function in gait.

Science.gov (United States)

Giacomozzi, Claudia; Leardini, Alberto; Caravaggi, Paolo

2014-08-22

Baropodometry and multi-segmental foot kinematics are frequently employed to obtain insight into the mechanics of the foot-ground interaction in both basic research and clinical settings. However, nothing hitherto has been reported on the full integration of kinematics with baropodometric parameters, and only a few studies have addressed the association between intersegmental kinematics and plantar loading within specific foot regions. The aim of this study was to understanding the relationships between foot joint mobility and plantar loading by focusing on the correlation between these two measures. An integrated pressure-force-kinematics system was used to measure plantar pressure and rotations between foot segments during the stance phase of walking in 10 healthy subjects. An anatomically-based mask was applied to each footprint to obtain six regions according to the position of the markers; hence each kinematic segment was paired with a corresponding area of the plantar surface. Relationships between segmental motion and relevant baropodometric data were explored by means of correlation analysis. Negative, weak-to-moderate correlations (R(2)plantar pressure in almost all regions. The study helps improve our understanding of the relationship between joint mobility and plantar loading in the healthy foot and represents a critical preliminary analysis before addressing possible clinical applications. Copyright © 2014 Elsevier Ltd. All rights reserved.
Spinal cord grey matter segmentation challenge.

Science.gov (United States)

Prados, Ferran; Ashburner, John; Blaiotta, Claudia; Brosch, Tom; Carballido-Gamio, Julio; Cardoso, Manuel Jorge; Conrad, Benjamin N; Datta, Esha; Dávid, Gergely; Leener, Benjamin De; Dupont, Sara M; Freund, Patrick; Wheeler-Kingshott, Claudia A M Gandini; Grussu, Francesco; Henry, Roland; Landman, Bennett A; Ljungberg, Emil; Lyttle, Bailey; Ourselin, Sebastien; Papinutto, Nico; Saporito, Salvatore; Schlaeger, Regina; Smith, Seth A; Summers, Paul; Tam, Roger; Yiannakas, Marios C; Zhu, Alyssa; Cohen-Adad, Julien

2017-05-15

An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey and white matter for tissue specific analysis. There are several semi- or fully-automated segmentation methods for cervical cord cross-sectional area measurement with an excellent performance close or equal to the manual segmentation. However, grey matter segmentation is still challenging due to small cross-sectional size and shape, and active research is being conducted by several groups around the world in this field. Therefore a grey matter spinal cord segmentation challenge was organised to test different capabilities of various methods using the same multi-centre and multi-vendor dataset acquired with distinct 3D gradient-echo sequences. This challenge aimed to characterize the state-of-the-art in the field as well as identifying new opportunities for future improvements. Six different spinal cord grey matter segmentation methods developed independently by various research groups across the world and their performance were compared to manual segmentation outcomes, the present gold-standard. All algorithms provided good overall results for detecting the grey matter butterfly, albeit with variable performance in certain quality-of-segmentation metrics. The data have been made publicly available and the challenge web site remains open to new submissions. No modifications were introduced to any of the presented methods as a result of this challenge for the purposes of this publication. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
A new background distribution-based active contour model for three-dimensional lesion segmentation in breast DCE-MRI

Energy Technology Data Exchange (ETDEWEB)

Liu, Hui; Liu, Yiping; Qiu, Tianshuang [Department of Biomedical Engineering, Dalian University of Technology, Dalian 116024 (China); Zhao, Zuowei, E-mail: liuhui@dlut.edu.cn [Second Affiliated Hospital, Dalian Medical University, Dalian 116027 (China); Zhang, Lina [Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian 116027 (China)

2014-08-15

Purpose: To develop and evaluate a computerized semiautomatic segmentation method for accurate extraction of three-dimensional lesions from dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) of the breast. Methods: The authors propose a new background distribution-based active contour model using level set (BDACMLS) to segment lesions in breast DCE-MRIs. The method starts with manual selection of a region of interest (ROI) that contains the entire lesion in a single slice where the lesion is enhanced. Then the lesion volume from the volume data of interest, which is captured automatically, is separated. The core idea of BDACMLS is a new signed pressure function which is based solely on the intensity distribution combined with pathophysiological basis. To compare the algorithm results, two experienced radiologists delineated all lesions jointly to obtain the ground truth. In addition, results generated by other different methods based on level set (LS) are also compared with the authors’ method. Finally, the performance of the proposed method is evaluated by several region-based metrics such as the overlap ratio. Results: Forty-two studies with 46 lesions that contain 29 benign and 17 malignant lesions are evaluated. The dataset includes various typical pathologies of the breast such as invasive ductal carcinoma, ductal carcinomain situ, scar carcinoma, phyllodes tumor, breast cysts, fibroadenoma, etc. The overlap ratio for BDACMLS with respect to manual segmentation is 79.55% ± 12.60% (mean ± s.d.). Conclusions: A new active contour model method has been developed and shown to successfully segment breast DCE-MRI three-dimensional lesions. The results from this model correspond more closely to manual segmentation, solve the weak-edge-passed problem, and improve the robustness in segmenting different lesions.

Automatic segmentation of the left ventricle in a cardiac MR short axis image using blind morphological operation

Science.gov (United States)

Irshad, Mehreen; Muhammad, Nazeer; Sharif, Muhammad; Yasmeen, Mussarat

2018-04-01

Conventionally, cardiac MR image analysis is done manually. Automatic examination for analyzing images can replace the monotonous tasks of massive amounts of data to analyze the global and regional functions of the cardiac left ventricle (LV). This task is performed using MR images to calculate the analytic cardiac parameter like end-systolic volume, end-diastolic volume, ejection fraction, and myocardial mass, respectively. These analytic parameters depend upon genuine delineation of epicardial, endocardial, papillary muscle, and trabeculations contours. In this paper, we propose an automatic segmentation method using the sum of absolute differences technique to localize the left ventricle. Blind morphological operations are proposed to segment and detect the LV contours of the epicardium and endocardium, automatically. We test the benchmark Sunny Brook dataset for evaluation of the proposed work. Contours of epicardium and endocardium are compared quantitatively to determine contour's accuracy and observe high matching values. Similarity or overlapping of an automatic examination to the given ground truth analysis by an expert are observed with high accuracy as with an index value of 91.30% . The proposed method for automatic segmentation gives better performance relative to existing techniques in terms of accuracy.
Exploring the use of grounded theory as a methodological approach to examine the 'black box' of network leadership in the national quality forum.

Science.gov (United States)

Hoflund, A Bryce

2013-01-01

This paper describes how grounded theory was used to investigate the "black box" of network leadership in the creation of the National Quality Forum. Scholars are beginning to recognize the importance of network organizations and are in the embryonic stages of collecting and analyzing data about network leadership processes. Grounded theory, with its focus on deriving theory from empirical data, offers researchers a distinctive way of studying little-known phenomena and is therefore well suited to exploring network leadership processes. Specifically, this paper provides an overview of grounded theory, a discussion of the appropriateness of grounded theory to investigating network phenomena, a description of how the research was conducted, and a discussion of the limitations and lessons learned from using this approach.
Analysis of a kinetic multi-segment foot model part II: kinetics and clinical implications.

Science.gov (United States)

Bruening, Dustin A; Cooney, Kevin M; Buczek, Frank L

2012-04-01

Kinematic multi-segment foot models have seen increased use in clinical and research settings, but the addition of kinetics has been limited and hampered by measurement limitations and modeling assumptions. In this second of two companion papers, we complete the presentation and analysis of a three segment kinetic foot model by incorporating kinetic parameters and calculating joint moments and powers. The model was tested on 17 pediatric subjects (ages 7-18 years) during normal gait. Ground reaction forces were measured using two adjacent force platforms, requiring targeted walking and the creation of two sub-models to analyze ankle, midtarsal, and 1st metatarsophalangeal joints. Targeted walking resulted in only minimal kinematic and kinetic differences compared with walking at self selected speeds. Joint moments and powers were calculated and ensemble averages are presented as a normative database for comparison purposes. Ankle joint powers are shown to be overestimated when using a traditional single-segment foot model, as substantial angular velocities are attributed to the mid-tarsal joint. Power transfer is apparent between the 1st metatarsophalangeal and mid-tarsal joints in terminal stance/pre-swing. While the measurement approach presented here is limited to clinical populations with only minimal impairments, some elements of the model can also be incorporated into routine clinical gait analysis. Copyright © 2011 Elsevier B.V. All rights reserved.
Multi-scale Modelling of Segmentation

DEFF Research Database (Denmark)

Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri

2016-01-01

pieces. In a second experiment on non-real-time segmentation, musicians indicated boundaries and their strength for six examples. Kernel density estimation was used to develop multi-scale segmentation models. Contrary to previous research, no relationship was found between boundary strength and boundary......While listening to music, people often unwittingly break down musical pieces into constituent chunks such as verses and choruses. Music segmentation studies have suggested that some consensus regarding boundary perception exists, despite individual differences. However, neither the effects...
Naval EarthMap Observer: overview and data processing

Science.gov (United States)

Bowles, Jeffrey H.; Davis, Curtiss O.; Carney, Megan; Clamons, Dean; Gao, Bo-Cai; Gillis, David; Kappus, Mary E.; Lamela, G.; Montes, Marcos J.; Palmadesso, Peter J.; Rhea, J.; Snyder, William A.

1999-12-01

We present an overview of the Naval EarthMap Observer (NEMO) spacecraft and then focus on the processing of NEMO data both on-board the spacecraft and on the ground. The NEMO spacecraft provides for Joint Naval needs and demonstrates the use of hyperspectral imagery for the characterization of the littoral environment and for littoral ocean model development. NEMO is being funded jointly by the U.S. government and commercial partners. The Coastal Ocean Imaging Spectrometer (COIS) is the primary instrument on the NEMO and covers the spectral range from 400 to 2500 nm at 10-nm resolution with either 30 or 60 m work GSD. The hyperspectral data is processed on-board the NEMO using NRL's Optical Real-time Automated Spectral Identification System (ORASIS) algorithm that provides for real time analysis, feature extraction and greater than 10:1 data compression. The high compression factor allows for ground coverage of greater than 106 km2/day. Calibration of the sensor is done with a combination of moon imaging, using an onboard light source and vicarious calibration using a number of earth sites being monitored for that purpose. The data will be atmospherically corrected using ATREM. Algorithms will also be available to determine water clarity, bathymetry and bottom type.
Skip segment Hirschsprung disease and Waardenburg syndrome

Directory of Open Access Journals (Sweden)

Erica R. Gross

2015-04-01

Full Text Available Skip segment Hirschsprung disease describes a segment of ganglionated bowel between two segments of aganglionated bowel. It is a rare phenomenon that is difficult to diagnose. We describe a recent case of skip segment Hirschsprung disease in a neonate with a family history of Waardenburg syndrome and the genetic profile that was identified.
NPOESS Interface Data Processing Segment Product Generation

Science.gov (United States)

Grant, K. D.

2009-12-01

The National Oceanic and Atmospheric Administration (NOAA), Department of Defense (DoD), and National Aeronautics and Space Administration (NASA) are jointly acquiring the next-generation weather and environmental satellite system; the National Polar-orbiting Operational Environmental Satellite System (NPOESS). NPOESS replaces the current Polar-orbiting Operational Environmental Satellites (POES) managed by NOAA and the Defense Meteorological Satellite Program (DMSP) managed by the DoD. The NPOESS satellites carry a suite of sensors that collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The NPOESS design allows centralized mission management and delivers high quality environmental products to military, civil and scientific users. The ground data processing segment for NPOESS is the Interface Data Processing Segment (IDPS), developed by Raytheon Intelligence and Information Systems. The IDPS processes NPOESS satellite data to provide environmental data products to NOAA and DoD processing centers operated by the United States government. The IDPS will process environmental data products beginning with the NPOESS Preparatory Project (NPP) and continuing through the lifetime of the NPOESS system. Within the overall NPOESS processing environment, the IDPS must process a data volume nearly 1000 times the size of current systems -- in one-quarter of the time. Further, it must support the calibration, validation, and data quality improvement initiatives of the NPOESS program to ensure the production of atmospheric and environmental products that meet strict requirements for accuracy and precision. This paper will describe the architecture approach that is necessary to meet these challenging, and seemingly exclusive, NPOESS IDPS design requirements, with a focus on the processing relationships required to generate the NPP products.
NPOESS Interface Data Processing Segment (IDPS) Hardware

Science.gov (United States)

Sullivan, W. J.; Grant, K. D.; Bergeron, C.

2008-12-01

The National Oceanic and Atmospheric Administration (NOAA), Department of Defense (DoD), and National Aeronautics and Space Administration (NASA) are jointly acquiring the next-generation weather and environmental satellite system; the National Polar-orbiting Operational Environmental Satellite System (NPOESS). NPOESS replaces the current Polar-orbiting Operational Environmental Satellites (POES) managed by NOAA and the Defense Meteorological Satellite Program (DMSP) managed by the DoD. The NPOESS satellites carry a suite of sensors that collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The NPOESS design allows centralized mission management and delivers high quality environmental products to military, civil and scientific users. The ground data processing segment for NPOESS is the Interface Data Processing Segment (IDPS), developed by Raytheon Intelligence and Information Systems. IDPS processes NPOESS satellite data to provide environmental data products to NOAA and DoD processing centers operated by the United States government. IDPS will process environmental data products beginning with the NPOESS Preparatory Project (NPP) and continuing through the lifetime of the NPOESS system. Within the overall NPOESS processing environment, the IDPS must process a data volume several orders of magnitude the size of current systems -- in one-quarter of the time. Further, it must support the calibration, validation, and data quality improvement initiatives of the NPOESS program to ensure the production of atmospheric and environmental products that meet strict requirements for accuracy and precision. This poster will illustrate and describe the IDPS HW architecture that is necessary to meet these challenging design requirements. In addition, it will illustrate the expandability features of the architecture in support of future data processing and data distribution needs.
Study on the Feasibility of RGB Substitute CIR for Automatic Removal Vegetation Occlusion Based on Ground Close-Range Building Images

Science.gov (United States)

Li, C.; Li, F.; Liu, Y.; Li, X.; Liu, P.; Xiao, B.

2012-07-01

Building 3D reconstruction based on ground remote sensing data (image, video and lidar) inevitably faces the problem that buildings are always occluded by vegetation, so how to automatically remove and repair vegetation occlusion is a very important preprocessing work for image understanding, compute vision and digital photogrammetry. In the traditional multispectral remote sensing which is achieved by aeronautics and space platforms, the Red and Near-infrared (NIR) bands, such as NDVI (Normalized Difference Vegetation Index), are useful to distinguish vegetation and clouds, amongst other targets. However, especially in the ground platform, CIR (Color Infra Red) is little utilized by compute vision and digital photogrammetry which usually only take true color RBG into account. Therefore whether CIR is necessary for vegetation segmentation or not has significance in that most of close-range cameras don't contain such NIR band. Moreover, the CIE L*a*b color space, which transform from RGB, seems not of much interest by photogrammetrists despite its powerfulness in image classification and analysis. So, CIE (L, a, b) feature and support vector machine (SVM) is suggested for vegetation segmentation to substitute for CIR. Finally, experimental results of visual effect and automation are given. The conclusion is that it's feasible to remove and segment vegetation occlusion without NIR band. This work should pave the way for texture reconstruction and repair for future 3D reconstruction.
Segmentation-Based And Segmentation-Free Methods for Spotting Handwritten Arabic Words

OpenAIRE

Ball , Gregory R.; Srihari , Sargur N.; Srinivasan , Harish

2006-01-01

http://www.suvisoft.com; Given a set of handwritten documents, a common goal is to search for a relevant subset. Attempting to find a query word or image in such a set of documents is called word spotting. Spotting handwritten words in documents written in the Latin alphabet, and more recently in Arabic, has received considerable attention. One issue is generating candidate word regions on a page. Attempting to definitely segment the document into such regions (automatic segmentation) can mee...
Monitoring fish distributions along electrofishing segments

Science.gov (United States)

Miranda, Leandro E.

2014-01-01

Electrofishing is widely used to monitor fish species composition and relative abundance in streams and lakes. According to standard protocols, multiple segments are selected in a body of water to monitor population relative abundance as the ratio of total catch to total sampling effort. The standard protocol provides an assessment of fish distribution at a macrohabitat scale among segments, but not within segments. An ancillary protocol was developed for assessing fish distribution at a finer scale within electrofishing segments. The ancillary protocol was used to estimate spacing, dispersion, and association of two species along shore segments in two local reservoirs. The added information provided by the ancillary protocol may be useful for assessing fish distribution relative to fish of the same species, to fish of different species, and to environmental or habitat characteristics.
Space Telecommunications Radio System (STRS) Architecture. Part 1; Tutorial - Overview

Science.gov (United States)

Handler, Louis M.; Briones, Janette C.; Mortensen, Dale J.; Reinhart, Richard C.

2012-01-01

Space Telecommunications Radio System (STRS) Architecture Standard provides a NASA standard for software-defined radio. STRS is being demonstrated in the Space Communications and Navigation (SCaN) Testbed formerly known as Communications, Navigation and Networking Configurable Testbed (CoNNeCT). Ground station radios communicating the SCaN testbed are also being written to comply with the STRS architecture. The STRS Architecture Tutorial Overview presents a general introduction to the STRS architecture standard developed at the NASA Glenn Research Center (GRC), addresses frequently asked questions, and clarifies methods of implementing the standard. The STRS architecture should be used as a base for many of NASA s future telecommunications technologies. The presentation will provide a basic understanding of STRS.
AUTOMATIC RETINA EXUDATES SEGMENTATION WITHOUT A MANUALLY LABELLED TRAINING SET

Energy Technology Data Exchange (ETDEWEB)

Giancardo, Luca [ORNL; Meriaudeau, Fabrice [ORNL; Karnowski, Thomas Paul [ORNL; Li, Yaquin [University of Tennessee, Knoxville (UTK); Tobin Jr, Kenneth William [ORNL; Chaum, Edward [University of Tennessee, Knoxville (UTK)

2011-01-01

Diabetic macular edema (DME) is a common vision threatening complication of diabetic retinopathy which can be assessed by detecting exudates (a type of bright lesion) in fundus images. In this work, two new methods for the detection of exudates are presented which do not use a supervised learning step and therefore do not require ground-truthed lesion training sets which are time consuming to create, difficult to obtain, and prone to human error. We introduce a new dataset of fundus images from various ethnic groups and levels of DME which we have made publicly available. We evaluate our algorithm with this dataset and compare our results with two recent exudate segmentation algorithms. In all of our tests, our algorithms perform better or comparable with an order of magnitude reduction in computational time.
Color image Segmentation using automatic thresholding techniques

International Nuclear Information System (INIS)

Harrabi, R.; Ben Braiek, E.

2011-01-01

In this paper, entropy and between-class variance based thresholding methods for color images segmentation are studied. The maximization of the between-class variance (MVI) and the entropy (ME) have been used as a criterion functions to determine an optimal threshold to segment images into nearly homogenous regions. Segmentation results from the two methods are validated and the segmentation sensitivity for the test data available is evaluated, and a comparative study between these methods in different color spaces is presented. The experimental results demonstrate the superiority of the MVI method for color image segmentation.
An Overview of data science uses in bioimage informatics.

Science.gov (United States)

Chessel, Anatole

2017-02-15

This review aims at providing a practical overview of the use of statistical features and associated data science methods in bioimage informatics. To achieve a quantitative link between images and biological concepts, one typically replaces an object coming from an image (a segmented cell or intracellular object, a pattern of expression or localisation, even a whole image) by a vector of numbers. They range from carefully crafted biologically relevant measurements to features learnt through deep neural networks. This replacement allows for the use of practical algorithms for visualisation, comparison and inference, such as the ones from machine learning or multivariate statistics. While originating mainly, for biology, in high content screening, those methods are integral to the use of data science for the quantitative analysis of microscopy images to gain biological insight, and they are sure to gather more interest as the need to make sense of the increasing amount of acquired imaging data grows more pressing. Copyright © 2017 Elsevier Inc. All rights reserved.
Algorithms for Cytoplasm Segmentation of Fluorescence Labelled Cells

Directory of Open Access Journals (Sweden)

Carolina Wählby

2002-01-01

Full Text Available Automatic cell segmentation has various applications in cytometry, and while the nucleus is often very distinct and easy to identify, the cytoplasm provides a lot more challenge. A new combination of image analysis algorithms for segmentation of cells imaged by fluorescence microscopy is presented. The algorithm consists of an image pre‐processing step, a general segmentation and merging step followed by a segmentation quality measurement. The quality measurement consists of a statistical analysis of a number of shape descriptive features. Objects that have features that differ to that of correctly segmented single cells can be further processed by a splitting step. By statistical analysis we therefore get a feedback system for separation of clustered cells. After the segmentation is completed, the quality of the final segmentation is evaluated. By training the algorithm on a representative set of training images, the algorithm is made fully automatic for subsequent images created under similar conditions. Automatic cytoplasm segmentation was tested on CHO‐cells stained with calcein. The fully automatic method showed between 89% and 97% correct segmentation as compared to manual segmentation.
Benchmarking of Remote Sensing Segmentation Methods

Czech Academy of Sciences Publication Activity Database

Mikeš, Stanislav; Haindl, Michal; Scarpa, G.; Gaetano, R.

2015-01-01

Roč. 8, č. 5 (2015), s. 2240-2248 ISSN 1939-1404 R&D Projects: GA ČR(CZ) GA14-10911S Institutional support: RVO:67985556 Keywords : benchmark * remote sensing segmentation * unsupervised segmentation * supervised segmentation Subject RIV: BD - Theory of Information Impact factor: 2.145, year: 2015 http://library.utia.cas.cz/separaty/2015/RO/haindl-0445995.pdf
Tests of the gravitational redshift effect in space-born and ground-based experiments

Science.gov (United States)

Vavilova, I. B.

2018-02-01

This paper provides a brief overview of experiments as concerns with the tests of the gravitational redshift (GRS) effect in ground-based and space-born experiments. In particular, we consider the GRS effects in the gravitational field of the Earth, the major planets of the Solar system, compact stars (white dwarfs and neutron stars) where this effect is confirmed with a higher accuracy. We discuss availabilities to confirm the GRS effect for galaxies and galaxy clusters in visible and X-ray ranges of the electromagnetic spectrum.
Unsupervised Retinal Vessel Segmentation Using Combined Filters.

Directory of Open Access Journals (Sweden)

Wendeson S Oliveira

Full Text Available Image segmentation of retinal blood vessels is a process that can help to predict and diagnose cardiovascular related diseases, such as hypertension and diabetes, which are known to affect the retinal blood vessels' appearance. This work proposes an unsupervised method for the segmentation of retinal vessels images using a combined matched filter, Frangi's filter and Gabor Wavelet filter to enhance the images. The combination of these three filters in order to improve the segmentation is the main motivation of this work. We investigate two approaches to perform the filter combination: weighted mean and median ranking. Segmentation methods are tested after the vessel enhancement. Enhanced images with median ranking are segmented using a simple threshold criterion. Two segmentation procedures are applied when considering enhanced retinal images using the weighted mean approach. The first method is based on deformable models and the second uses fuzzy C-means for the image segmentation. The procedure is evaluated using two public image databases, Drive and Stare. The experimental results demonstrate that the proposed methods perform well for vessel segmentation in comparison with state-of-the-art methods.
Automatic segmentation of psoriasis lesions

Science.gov (United States)

Ning, Yang; Shi, Chenbo; Wang, Li; Shu, Chang

2014-10-01

The automatic segmentation of psoriatic lesions is widely researched these years. It is an important step in Computer-aid methods of calculating PASI for estimation of lesions. Currently those algorithms can only handle single erythema or only deal with scaling segmentation. In practice, scaling and erythema are often mixed together. In order to get the segmentation of lesions area - this paper proposes an algorithm based on Random forests with color and texture features. The algorithm has three steps. The first step, the polarized light is applied based on the skin's Tyndall-effect in the imaging to eliminate the reflection and Lab color space are used for fitting the human perception. The second step, sliding window and its sub windows are used to get textural feature and color feature. In this step, a feature of image roughness has been defined, so that scaling can be easily separated from normal skin. In the end, Random forests will be used to ensure the generalization ability of the algorithm. This algorithm can give reliable segmentation results even the image has different lighting conditions, skin types. In the data set offered by Union Hospital, more than 90% images can be segmented accurately.

Inelastic response evaluation of steel frame structure subjected to near-fault ground motions

Energy Technology Data Exchange (ETDEWEB)

Choi, In Kil; Kim, Hyung Kyu; Choun, Young Sun; Seo, Jeong Moon

2004-04-01

A survey on some of the Quaternary fault segments near the Korean nuclear power plants is ongoing. It is likely that these faults would be identified as active ones. If the faults are confirmed as active ones, it will be necessary to reevaluate the seismic safety of nuclear power plants located near the fault. This study was performed to acquire overall knowledge of near-fault ground motions and evaluate inealstic response characteristics of near-fault ground motions. Although Korean peninsular is not located in the strong earthquake region, it is necessary to evaluate seismic safety of NPP for the earthquakes occurred in near-fault area with characteristics different from that of general far-fault earthquakes in order to improve seismic safety of existing NPP structures and equipment. As a result, for the seismic safety evaluation of NPP structures and equipment considering near-fault effects, this report will give many valuable information. In order to improve seismic safety of NPP structures and equipment against near-fault ground motions, it is necessary to consider inelastic response characteristics of near-fault ground motions in current design code. Also in Korea where these studies are immature yet, in the future more works of near-fault earthquakes must be accomplished.
Overview of Ground Air Quality Measurements and Their Links to Airborne, Remote Sensing and Model Studies during the KORUS-AQ Campaign

Science.gov (United States)

Lee, G.; Ahn, J. Y.; Chang, L. S.; Kim, J.; Park, R.

2017-12-01

During the KORUS-AQ, extensive sets of chemical measurements for reactive gases and aerosol species were made at 3 major sites on upwind island (Baengyeong Island), urban (Olympic Park in Seoul) and downwind rural forest location (Taewha Forest). Also, intensive aerosol size and composition observations from 5 NIER super sites, 3 NIMR monitoring sites, and 5 other university sites were currently facilitated in the KORUS-AQ data set. In addition, air quality criteria species data from 264 nation-wide ground monitoring sites with 5 minute temporal resolution during the whole campaign period were supplemented to cover mostly in densely populated urban areas, but sparsely in rural areas. The specific objectives of these ground sites were to provide highly comprehensive data set to coordinate the close collaborations among other research platforms including airborne measurements, remote sensing, and model studies. The continuous measurements at ground sites were well compared with repetitive low-level aircraft observations of NASA's DC-8 over Olympic Park and Taewha Forest site. Similarly, many ground measurements enabled the validation of chemical transport models and the remote sensing observations from ground and NASA's King Air. The observed results from inter-comparison studies in many reactive gases and aerosol compositions between different measurement methods and platforms will be presented. Compiling data sets from ground sites, source-wise analysis for ozone and aerosol, their in-situ formations, and transport characteristics by local/regional circulation will be discussed, too.
Simultaneous minimizing monitor units and number of segments without leaf end abutment for segmental intensity modulated radiation therapy delivery

International Nuclear Information System (INIS)

Li Kaile; Dai Jianrong; Ma Lijun

2004-01-01

Leaf end abutment is seldom studied when delivering segmental intensity modulated radiation therapy (IMRT) fields. We developed an efficient leaf sequencing method to eliminate leaf end abutment for segmental IMRT delivery. Our method uses simple matrix and sorting operations to obtain a solution that simultaneously minimizes total monitor units and number of segments without leaf end abutment between segments. We implemented and demonstrated our method for multiple clinical cases. We compared the results of our method with the results from exhaustive search method. We found that our solution without leaf end abutment produced equivalent results to the unconstrained solutions in terms of minimum total monitor units and minimum number of leaf segments. We conclude that the leaf end abutment fields can be avoided without affecting the efficiency of segmental IMRT delivery. The major strength of our method is its simplicity and high computing speed. This potentially provides a useful means for generating segmental IMRT fields that require high spatial resolution or complex intensity distributions
NASA Langley and NLR Research of Distributed Air/Ground Traffic Management

Science.gov (United States)

Ballin, Mark G.; Hoekstra, Jacco M.; Wing, David J.; Lohr, Gary W.

2002-01-01

Distributed Air/Ground Traffic Management (DAG-TM) is a concept of future air traffic operations that proposes to distribute information, decision-making authority, and responsibility among flight crews, the air traffic service provider, and aeronautical operational control organizations. This paper provides an overview and status of DAG-TM research at NASA Langley Research Center and the National Aerospace Laboratory of The Netherlands. Specific objectives of the research are to evaluate the technical and operational feasibility of the autonomous airborne component of DAG-TM, which is founded on the operational paradigm of free flight. The paper includes an overview of research approaches, the airborne technologies under development, and a summary of experimental investigations and findings to date. Although research is not yet complete, these findings indicate that free flight is feasible and will significantly enhance system capacity and safety. While free flight cannot alone resolve the complex issues faced by those modernizing the global airspace, it should be considered an essential part of a comprehensive air traffic management modernization activity.
Hierarchical image segmentation for learning object priors

Energy Technology Data Exchange (ETDEWEB)

Prasad, Lakshman [Los Alamos National Laboratory; Yang, Xingwei [TEMPLE UNIV.; Latecki, Longin J [TEMPLE UNIV.; Li, Nan [TEMPLE UNIV.

2010-11-10

The proposed segmentation approach naturally combines experience based and image based information. The experience based information is obtained by training a classifier for each object class. For a given test image, the result of each classifier is represented as a probability map. The final segmentation is obtained with a hierarchial image segmentation algorithm that considers both the probability maps and the image features such as color and edge strength. We also utilize image region hierarchy to obtain not only local but also semi-global features as input to the classifiers. Moreover, to get robust probability maps, we take into account the region context information by averaging the probability maps over different levels of the hierarchical segmentation algorithm. The obtained segmentation results are superior to the state-of-the-art supervised image segmentation algorithms.
Effect of the average soft-segment length on the morphology and properties of segmented polyurethane nanocomposites

International Nuclear Information System (INIS)

Finnigan, Bradley; Halley, Peter; Jack, Kevin; McDowell, Alasdair; Truss, Rowan; Casey, Phil; Knott, Robert; Martin, Darren

2006-01-01

Two organically modified layered silicates (with small and large diameters) were incorporated into three segmented polyurethanes with various degrees of microphase separation. Microphase separation increased with the molecular weight of the poly(hexamethylene oxide) soft segment. The molecular weight of the soft segment did not influence the amount of polyurethane intercalating the interlayer spacing. Small-angle neutron scattering and differential scanning calorimetry data indicated that the layered silicates did not affect the microphase morphology of any host polymer, regardless of the particle diameter. The stiffness enhancement on filler addition increased as the microphase separation of the polyurethane decreased, presumably because a greater number of urethane linkages were available to interact with the filler. For comparison, the small nanofiller was introduced into a polyurethane with a poly(tetramethylene oxide) soft segment, and a significant increase in the tensile strength and a sharper upturn in the stress-strain curve resulted. No such improvement occurred in the host polymers with poly(hexamethylene oxide) soft segments. It is proposed that the nanocomposite containing the more hydrophilic and mobile poly(tetramethylene oxide) soft segment is capable of greater secondary bonding between the polyurethane chains and the organosilicate surface, resulting in improved stress transfer to the filler and reduced molecular slippage.
Essays in international market segmentation

NARCIS (Netherlands)

Hofstede, ter F.

1999-01-01

The primary objective of this thesis is to develop and validate new methodologies to improve the effectiveness of international segmentation strategies. The current status of international market segmentation research is reviewed in an introductory chapter, which provided a number of
An overview of the laser ranging method of space laser altimeter

Science.gov (United States)

Zhou, Hui; Chen, Yuwei; Hyyppä, Juha; Li, Song

2017-11-01

Space laser altimeter is an active remote sensing instrument to measure topographic map of Earth, Moon and planetary. The space laser altimeter determines the range between the instrument and laser footprint by measuring round trip time of laser pulse. The return pulse reflected from ground surface is gathered by the receiver of space laser altimeter, the pulsewidth and amplitude of which are changeable with the variability of the ground relief. Meantime, several kinds of noise overlapped on the return pulse signal affect its signal-to-noise ratio. To eliminate the influence of these factors that cause range walk and range uncertainty, the reliable laser ranging methods need to be implemented to obtain high-precision range results. Based on typical space laser altimeters in the past few decades, various ranging methods are expounded in detail according to the operational principle of instruments and timing method. By illustrating the concrete procedure of determining time of flight of laser pulse, this overview provides the comparison of the employed technologies in previous and undergoing research programs and prospect innovative technology for space laser altimeters in future.
Roentgenological diagnoss of central segmental lung cancer

International Nuclear Information System (INIS)

Gurevich, L.A.; Fedchenko, G.G.

1984-01-01

Basing on an analysis of the results of clinicoroentgenological examination of 268 patments roentgenological semiotics of segmental lung cancer is presented. Some peculiarities of the X-ray picture of cancer of different segments of the lungs were revealed depending on tumor site and growth type. For the syndrome of segmental darkening the comprehensive X-ray methods where the chief method is tomography of the segmental bronchi are proposed
Method of manufacturing a large-area segmented photovoltaic module

Science.gov (United States)

Lenox, Carl

2013-11-05

One embodiment of the invention relates to a segmented photovoltaic (PV) module which is manufactured from laminate segments. The segmented PV module includes rectangular-shaped laminate segments formed from rectangular-shaped PV laminates and further includes non-rectangular-shaped laminate segments formed from rectangular-shaped and approximately-triangular-shaped PV laminates. The laminate segments are mechanically joined and electrically interconnected to form the segmented module. Another embodiment relates to a method of manufacturing a large-area segmented photovoltaic module from laminate segments of various shapes. Other embodiments relate to processes for providing a photovoltaic array for installation at a site. Other embodiments and features are also disclosed.
Study of the morphology exhibited by linear segmented polyurethanes

International Nuclear Information System (INIS)

Pereira, I.M.; Orefice, R.L.

2009-01-01

Five series of segmented polyurethanes with different hard segment content were prepared by the prepolymer mixing method. The nano-morphology of the obtained polyurethanes and their microphase separation were investigated by infrared spectroscopy, modulated differential scanning calorimetry and small-angle X-ray scattering. Although highly hydrogen bonded hard segments were formed, high hard segment contents promoted phase mixture and decreased the chain mobility, decreasing the hard segment domain precipitation and the soft segments crystallization. The applied techniques were able to show that the hard-segment content and the hard-segment interactions were the two controlling factors for determining the structure of segmented polyurethanes. (author)
Aerothermal Ground Testing of Flexible Thermal Protection Systems for Hypersonic Inflatable Aerodynamic Decelerators

Science.gov (United States)

Bruce, Walter E., III; Mesick, Nathaniel J.; Ferlemann, Paul G.; Siemers, Paul M., III; DelCorso, Joseph A.; Hughes, Stephen J.; Tobin, Steven A.; Kardell, Matthew P.

2012-01-01

Flexible TPS development involves ground testing and analysis necessary to characterize performance of the FTPS candidates prior to flight testing. This paper provides an overview of the analysis and ground testing efforts performed over the last year at the NASA Langley Research Center and in the Boeing Large-Core Arc Tunnel (LCAT). In the LCAT test series, material layups were subjected to aerothermal loads commensurate with peak re-entry conditions enveloping a range of HIAD mission trajectories. The FTPS layups were tested over a heat flux range from 20 to 50 W/cm with associated surface pressures of 3 to 8 kPa. To support the testing effort a significant redesign of the existing shear (wedge) model holder from previous testing efforts was undertaken to develop a new test technique for supporting and evaluating the FTPS in the high-temperature, arc jet flow. Since the FTPS test samples typically experience a geometry change during testing, computational fluid dynamic (CFD) models of the arc jet flow field and test model were developed to support the testing effort. The CFD results were used to help determine the test conditions experienced by the test samples as the surface geometry changes. This paper includes an overview of the Boeing LCAT facility, the general approach for testing FTPS, CFD analysis methodology and results, model holder design and test methodology, and selected thermal results of several FTPS layups.
Prototype implementation of segment assembling software

Directory of Open Access Journals (Sweden)

Pešić Đorđe

2018-01-01

Full Text Available IT education is very important and a lot of effort is put into the development of tools for helping students to acquire programming knowledge and for helping teachers in automating the examination process. This paper describes a prototype of the program segment assembling software used in the context of making tests in the field of algorithmic complexity. The proposed new program segment assembling model uses rules and templates. A template is a simple program segment. A rule defines combining method and data dependencies if they exist. One example of program segment assembling by the proposed system is given. Graphical user interface is also described.
Smart markers for watershed-based cell segmentation.

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Can Fahrettin Koyuncu

Full Text Available Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of "smart markers" for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.
Smart markers for watershed-based cell segmentation.

Science.gov (United States)

Koyuncu, Can Fahrettin; Arslan, Salim; Durmaz, Irem; Cetin-Atalay, Rengul; Gunduz-Demir, Cigdem

2012-01-01

Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of "smart markers" for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.
An overview of coronary quantitation techniques as of 1989. 4

International Nuclear Information System (INIS)

Reiber, J.H.C.

1991-01-01

An extensive overview is presented on the state of the art in quantitative geometric and densitometric computer-aided analysis of coronary obstructions as of early 1989. All the data provided were obtained by requesting a total of 16 investigators known to the author to be actively involved in the development of quantitative coronary arteriography (QCA) techniques to complete a questionnaire including 29 questions on the different aspects of QCA. From this overview a number of conclusions can be drawn, particularly when comparing the results with those from early 1987: 1.There is an increased interest in the development of QCA-techniques for on-line use in the catheterization laboratory; 2.Modern workstations and very powerful personal computers are increasingly being used; 3.Software is mostly written in Pascal and C; 4.In the majority of the cases the edge definition is based on a combination of 1st- and 2nd-derivate functions; 5.Correction for the limited resolution of the X-ray system is still insufficiently used; 6.In the majority of the cases image calibration is based on the measurement of the size of the coronary catheter segment; 7.There has been no signal of new developments in the definition of clinically relevant parameters except for the stenotic flow reserve; 8.Densitometry remains a problematic technique; and 9.The use of more extensive and particularly standardized validation procedures should be encouraged. (author). 103 refs.; 8 figs.; 9 tabs
An unsupervised strategy for biomedical image segmentation

Directory of Open Access Journals (Sweden)

Roberto Rodríguez

2010-09-01

Full Text Available Roberto Rodríguez1, Rubén Hernández21Digital Signal Processing Group, Institute of Cybernetics, Mathematics, and Physics, Havana, Cuba; 2Interdisciplinary Professional Unit of Engineering and Advanced Technology, IPN, MexicoAbstract: Many segmentation techniques have been published, and some of them have been widely used in different application problems. Most of these segmentation techniques have been motivated by specific application purposes. Unsupervised methods, which do not assume any prior scene knowledge can be learned to help the segmentation process, and are obviously more challenging than the supervised ones. In this paper, we present an unsupervised strategy for biomedical image segmentation using an algorithm based on recursively applying mean shift filtering, where entropy is used as a stopping criterion. This strategy is proven with many real images, and a comparison is carried out with manual segmentation. With the proposed strategy, errors less than 20% for false positives and 0% for false negatives are obtained.Keywords: segmentation, mean shift, unsupervised segmentation, entropy
Potential use of ground-based sensor technologies for weed detection.

Science.gov (United States)

Peteinatos, Gerassimos G; Weis, Martin; Andújar, Dionisio; Rueda Ayala, Victor; Gerhards, Roland

2014-02-01

Site-specific weed management is the part of precision agriculture (PA) that tries to effectively control weed infestations with the least economical and environmental burdens. This can be achieved with the aid of ground-based or near-range sensors in combination with decision rules and precise application technologies. Near-range sensor technologies, developed for mounting on a vehicle, have been emerging for PA applications during the last three decades. These technologies focus on identifying plants and measuring their physiological status with the aid of their spectral and morphological characteristics. Cameras, spectrometers, fluorometers and distance sensors are the most prominent sensors for PA applications. The objective of this article is to describe-ground based sensors that have the potential to be used for weed detection and measurement of weed infestation level. An overview of current sensor systems is presented, describing their concepts, results that have been achieved, already utilized commercial systems and problems that persist. A perspective for the development of these sensors is given. © 2013 Society of Chemical Industry.
MOVING WINDOW SEGMENTATION FRAMEWORK FOR POINT CLOUDS

Directory of Open Access Journals (Sweden)

G. Sithole

2012-07-01

Full Text Available As lidar point clouds become larger streamed processing becomes more attractive. This paper presents a framework for the streamed segmentation of point clouds with the intention of segmenting unstructured point clouds in real-time. The framework is composed of two main components. The first component segments points within a window shifting over the point cloud. The second component stitches the segments within the windows together. In this fashion a point cloud can be streamed through these two components in sequence, thus producing a segmentation. The algorithm has been tested on airborne lidar point cloud and some results of the performance of the framework are presented.
Review of segmentation process in consumer markets

OpenAIRE

Veronika Jadczaková

2013-01-01

Although there has been a considerable debate on market segmentation over five decades, attention was merely devoted to single stages of the segmentation process. In doing so, stages as segmentation base selection or segments profiling have been heavily covered in the extant literature, whereas stages as implementation of the marketing strategy or market definition were of a comparably lower interest. Capitalizing on this shortcoming, this paper strives to close the gap and provide each step...

IFRS 8 – OPERATING SEGMENTS

Directory of Open Access Journals (Sweden)

BOCHIS LEONICA

2009-05-01

Full Text Available Segment reporting in accordance with IFRS 8 will be mandatory for annual financial statements covering periods beginning on or after 1 January 2009. The standards replaces IAS 14, Segment Reporting, from that date. The objective of IFRS 8 is to require
The Hierarchy of Segment Reports

Directory of Open Access Journals (Sweden)

Danilo Dorović

2015-05-01

Full Text Available The article presents an attempt to find the connection between reports created for managers responsible for different business segments. With this purpose, the hierarchy of the business reporting segments is proposed. This can lead to better understanding of the expenses under common responsibility of more than one manager since these expenses should be in more than one report. The structure of cost defined per business segment hierarchy with the aim of new, unusual but relevant cost structure for management can be established. Both could potentially bring new information benefits for management in the context of profit reporting.
Segmental dilatation of the ileum

Directory of Open Access Journals (Sweden)

Tune-Yie Shih

2017-01-01

Full Text Available A 2-year-old boy was sent to the emergency department with the chief problem of abdominal pain for 1 day. He was just discharged from the pediatric ward with the diagnosis of mycoplasmal pneumonia and paralytic ileus. After initial examinations and radiographic investigations, midgut volvulus was impressed. An emergency laparotomy was performed. Segmental dilatation of the ileum with volvulus was found. The operative procedure was resection of the dilated ileal segment with anastomosis. The postoperative recovery was uneventful. The unique abnormality of gastrointestinal tract – segmental dilatation of the ileum, is described in details and the literature is reviewed.
Techniques on semiautomatic segmentation using the Adobe Photoshop

Science.gov (United States)

Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae

2005-04-01

The purpose of this research is to enable anybody to semiautomatically segment the anatomical structures in the MRIs, CTs, and other medical images on the personal computer. The segmented images are used for making three-dimensional images, which are helpful in medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was MR scanned to make 557 MRIs, which were transferred to a personal computer. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL; successively, manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a likewise manner, 11 anatomical structures in the 8,500 anatomcial images were segmented. Also, 12 brain and 10 heart anatomical structures in anatomical images were segmented. Proper segmentation was verified by making and examining the coronal, sagittal, and three-dimensional images from the segmented images. During semiautomatic segmentation on Adobe Photoshop, suitable algorithm could be used, the extent of automatization could be regulated, convenient user interface could be used, and software bugs rarely occurred. The techniques of semiautomatic segmentation using Adobe Photoshop are expected to be widely used for segmentation of the anatomical structures in various medical images.
CT identification of bronchopulmonary segments: 50 normal subjects

International Nuclear Information System (INIS)

Osbourne, D.; Vock, P.; Godwin, J.D.; Silverman, P.M.

1984-01-01

A systematic evaluation of the fissures, segmental bronchi and arteries, bronchopulmonary segments, and peripheral pulmonary parenchyma was made from computed tomographic (CT) scans of 50 patients with normal chest radiographs. Seventy percent of the segmental bronchi and 76% of the segmental arteries were identified. Arteries could be traced to their sixth- and seventh-order branches; their orientation to the plane of the CT section allowed gross identification and localization of bronchopulmonary segments
Segmentation of liver tumors on CT images

International Nuclear Information System (INIS)

Pescia, D.

2011-01-01

This thesis is dedicated to 3D segmentation of liver tumors in CT images. This is a task of great clinical interest since it allows physicians benefiting from reproducible and reliable methods for segmenting such lesions. Accurate segmentation would indeed help them during the evaluation of the lesions, the choice of treatment and treatment planning. Such a complex segmentation task should cope with three main scientific challenges: (i) the highly variable shape of the structures being sought, (ii) their similarity of appearance compared with their surrounding medium and finally (iii) the low signal to noise ratio being observed in these images. This problem is addressed in a clinical context through a two step approach, consisting of the segmentation of the entire liver envelope, before segmenting the tumors which are present within the envelope. We begin by proposing an atlas-based approach for computing pathological liver envelopes. Initially images are pre-processed to compute the envelopes that wrap around binary masks in an attempt to obtain liver envelopes from estimated segmentation of healthy liver parenchyma. A new statistical atlas is then introduced and used to segmentation through its diffeomorphic registration to the new image. This segmentation is achieved through the combination of image matching costs as well as spatial and appearance prior using a multi-scale approach with MRF. The second step of our approach is dedicated to lesions segmentation contained within the envelopes using a combination of machine learning techniques and graph based methods. First, an appropriate feature space is considered that involves texture descriptors being determined through filtering using various scales and orientations. Then, state of the art machine learning techniques are used to determine the most relevant features, as well as the hyper plane that separates the feature space of tumoral voxels to the ones corresponding to healthy tissues. Segmentation is then
Efficient Algorithms for Segmentation of Item-Set Time Series

Science.gov (United States)

Chundi, Parvathi; Rosenkrantz, Daniel J.

We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.
Segmentation of knee injury swelling on infrared images

Science.gov (United States)

Puentes, John; Langet, Hélène; Herry, Christophe; Frize, Monique

2011-03-01

Interpretation of medical infrared images is complex due to thermal noise, absence of texture, and small temperature differences in pathological zones. Acute inflammatory response is a characteristic symptom of some knee injuries like anterior cruciate ligament sprains, muscle or tendons strains, and meniscus tear. Whereas artificial coloring of the original grey level images may allow to visually assess the extent inflammation in the area, their automated segmentation remains a challenging problem. This paper presents a hybrid segmentation algorithm to evaluate the extent of inflammation after knee injury, in terms of temperature variations and surface shape. It is based on the intersection of rapid color segmentation and homogeneous region segmentation, to which a Laplacian of a Gaussian filter is applied. While rapid color segmentation enables to properly detect the observed core of swollen area, homogeneous region segmentation identifies possible inflammation zones, combining homogeneous grey level and hue area segmentation. The hybrid segmentation algorithm compares the potential inflammation regions partially detected by each method to identify overlapping areas. Noise filtering and edge segmentation are then applied to common zones in order to segment the swelling surfaces of the injury. Experimental results on images of a patient with anterior cruciate ligament sprain show the improved performance of the hybrid algorithm with respect to its separated components. The main contribution of this work is a meaningful automatic segmentation of abnormal skin temperature variations on infrared thermography images of knee injury swelling.
Reliability of a Seven-Segment Foot Model with Medial and Lateral Midfoot and Forefoot Segments During Walking Gait.

Science.gov (United States)

Cobb, Stephen C; Joshi, Mukta N; Pomeroy, Robin L

2016-12-01

In-vitro and invasive in-vivo studies have reported relatively independent motion in the medial and lateral forefoot segments during gait. However, most current surface-based models have not defined medial and lateral forefoot or midfoot segments. The purpose of the current study was to determine the reliability of a 7-segment foot model that includes medial and lateral midfoot and forefoot segments during walking gait. Three-dimensional positions of marker clusters located on the leg and 6 foot segments were tracked as 10 participants completed 5 walking trials. To examine the reliability of the foot model, coefficients of multiple correlation (CMC) were calculated across the trials for each participant. Three-dimensional stance time series and range of motion (ROM) during stance were also calculated for each functional articulation. CMCs for all of the functional articulations were ≥ 0.80. Overall, the rearfoot complex (leg-calcaneus segments) was the most reliable articulation and the medial midfoot complex (calcaneus-navicular segments) was the least reliable. With respect to ROM, reliability was greatest for plantarflexion/dorsiflexion and least for abduction/adduction. Further, the stance ROM and time-series patterns results between the current study and previous invasive in-vivo studies that have assessed actual bone motion were generally consistent.
Market Segmentation: An Instructional Module.

Science.gov (United States)

Wright, Peter H.

A concept-based introduction to market segmentation is provided in this instructional module for undergraduate and graduate transportation-related courses. The material can be used in many disciplines including engineering, business, marketing, and technology. The concept of market segmentation is primarily a transportation planning technique by…
Medical image segmentation using genetic algorithms.

Science.gov (United States)

Maulik, Ujjwal

2009-03-01

Genetic algorithms (GAs) have been found to be effective in the domain of medical image segmentation, since the problem can often be mapped to one of search in a complex and multimodal landscape. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. The resulting search space is therefore often noisy with a multitude of local optima. Not only does the genetic algorithmic framework prove to be effective in coming out of local optima, it also brings considerable flexibility into the segmentation procedure. In this paper, an attempt has been made to review the major applications of GAs to the domain of medical image segmentation.
Remote sensing image segmentation based on Hadoop cloud platform

Science.gov (United States)

Li, Jie; Zhu, Lingling; Cao, Fubin

2018-01-01

To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.
Evaluating the effect of multiple sclerosis lesions on automatic brain structure segmentation

Directory of Open Access Journals (Sweden)

Sandra González-Villà

2017-01-01

Full Text Available In recent years, many automatic brain structure segmentation methods have been proposed. However, these methods are commonly tested with non-lesioned brains and the effect of lesions on their performance has not been evaluated. Here, we analyze the effect of multiple sclerosis (MS lesions on three well-known automatic brain structure segmentation methods, namely, FreeSurfer, FIRST and multi-atlas fused by majority voting, which use learning-based, deformable and atlas-based strategies, respectively. To perform a quantitative analysis, 100 synthetic images of MS patients with a total of 2174 lesions are simulated on two public databases with available brain structure ground truth information (IBSR18 and MICCAI’12. The Dice similarity coefficient (DSC differences and the volume differences between the healthy and the simulated images are calculated for the subcortical structures and the brainstem. We observe that the three strategies are affected when lesions are present. However, the effects of the lesions do not follow the same pattern; the lesions either make the segmentation method underperform or surprisingly augment the segmentation accuracy. The obtained results show that FreeSurfer is the method most affected by the presence of lesions, with DSC differences (generated − healthy ranging from −0.11 ± 0.54 to 9.65 ± 9.87, whereas FIRST tends to be the most robust method when lesions are present (−2.40 ± 5.54 to 0.44 ± 0.94. Lesion location is not important for global strategies such as FreeSurfer or majority voting, where structure segmentation is affected wherever the lesions exist. On the other hand, FIRST is more affected when the lesions are overlaid or close to the structure of analysis. The most affected structure by the presence of lesions is the nucleus accumbens (from −1.12 ± 2.53 to 1.32 ± 4.00 for the left hemisphere and from −2.40 ± 5.54 to 9.65 ± 9.87 for the right hemisphere, whereas the
Communication grounding facility

International Nuclear Information System (INIS)

Lee, Gye Seong

1998-06-01

It is about communication grounding facility, which is made up twelve chapters. It includes general grounding with purpose, materials thermal insulating material, construction of grounding, super strength grounding method, grounding facility with grounding way and building of insulating, switched grounding with No. 1A and LCR, grounding facility of transmission line, wireless facility grounding, grounding facility in wireless base station, grounding of power facility, grounding low-tenton interior power wire, communication facility of railroad, install of arrester in apartment and house, install of arrester on introduction and earth conductivity and measurement with introduction and grounding resistance.
The SPQR experiment: detecting damage to orbiting spacecraft with ground-based telescopes

Science.gov (United States)

Paolozzi, Antonio; Porfilio, Manfredi; Currie, Douglas G.; Dantowitz, Ronald F.

2007-09-01

The objective of the Specular Point-like Quick Reference (SPQR) experiment was to evaluate the possibility of improving the resolution of ground-based telescopic imaging of manned spacecraft in orbit. The concept was to reduce image distortions due to atmospheric turbulence by evaluating the Point Spread Function (PSF) of a point-like light reference and processing the spacecraft image accordingly. The target spacecraft was the International Space Station (ISS) and the point-like reference was provided by a laser beam emitted by the ground station and reflected back to the telescope by a Cube Corner Reflector (CCR) mounted on an ISS window. The ultimate objective of the experiment was to demonstrate that it is possible to image spacecraft in Low Earth Orbit (LEO) with a resolution of 20 cm, which would have probably been sufficient to detect the damage which caused the Columbia disaster. The experiment was successfully performed from March to May 2005. The paper provides an overview of the SPQR experiment.
Incorporation of squalene into rod outer segments

International Nuclear Information System (INIS)

Keller, R.K.; Fliesler, S.J.

1990-01-01

We have reported previously that squalene is the major radiolabeled nonsaponifiable lipid product derived from [ 3 H]acetate in short term incubations of frog retinas. In the present study, we demonstrate that newly synthesized squalene is incorporated into rod outer segments under similar in vitro conditions. We show further that squalene is an endogenous constituent of frog rod outer segment membranes; its concentration is approximately 9.5 nmol/mumol of phospholipid or about 9% of the level of cholesterol. Pulse-chase experiments with radiolabeled precursors revealed no metabolism of outer segment squalene to sterols in up to 20 h of chase. Taken together with our previous absolute rate studies, these results suggest that most, if not all, of the squalene synthesized by the frog retina is transported to rod outer segments. Synthesis of protein is not required for squalene transport since puromycin had no effect on squalene incorporation into outer segments. Conversely, inhibition of isoprenoid synthesis with mevinolin had no effect on the incorporation of opsin into the outer segment. These latter results support the conclusion that the de novo synthesis and subsequent intracellular trafficking of opsin and isoprenoid lipids destined for the outer segment occur via independent mechanisms
Interactive segmentation techniques algorithms and performance evaluation

CERN Document Server

He, Jia; Kuo, C-C Jay

2013-01-01

This book focuses on interactive segmentation techniques, which have been extensively studied in recent decades. Interactive segmentation emphasizes clear extraction of objects of interest, whose locations are roughly indicated by human interactions based on high level perception. This book will first introduce classic graph-cut segmentation algorithms and then discuss state-of-the-art techniques, including graph matching methods, region merging and label propagation, clustering methods, and segmentation methods based on edge detection. A comparative analysis of these methods will be provided
Market segmentation using perceived constraints

Science.gov (United States)

Jinhee Jun; Gerard Kyle; Andrew Mowen

2008-01-01

We examined the practical utility of segmenting potential visitors to Cleveland Metroparks using their constraint profiles. Our analysis identified three segments based on their scores on the dimensions of constraints: Other priorities--visitors who scored the highest on 'other priorities' dimension; Highly Constrained--visitors who scored relatively high on...
Reduplication Facilitates Early Word Segmentation

Science.gov (United States)

Ota, Mitsuhiko; Skarabela, Barbora

2018-01-01

This study explores the possibility that early word segmentation is aided by infants' tendency to segment words with repeated syllables ("reduplication"). Twenty-four nine-month-olds were familiarized with passages containing one novel reduplicated word and one novel non-reduplicated word. Their central fixation times in response to…
An Innovative Use of Renewable Ground Heat for Insulation in Low Exergy Building Systems

Directory of Open Access Journals (Sweden)

Hansjürg Leibundgut

2012-08-01

Full Text Available Ground heat is a renewable resource that is readily available for buildings in cool climates, but its relatively low temperature requires the use of a heat pump to extract it for heating. We developed a system that uses low temperature ground heat directly in a building wall to reduce transmission heat losses. The Active Low Exergy Geothermal Insulation Systems (ALEGIS minimizes exergy demand and maximizes the use of renewable geothermal heat from the ground. A fluid is pumped into a small pipe network in an external layer of a wall construction that is linked to a ground heat source. This decouples the building from the outside temperature, therefore eliminating large peak demands and reducing the primary energy demand. Our steady-state analysis shows that at a design temperature of −10 °C the 6 cm thick active insulation system has equivalent performance to 11 cm of passive insulation. Our comparison of heating performance of a building with our active insulation system versus a building with static insulation of the same thickness shows a 15% reduction in annual electricity demand, and thus exergy input. We present an overview of the operation and analysis of our low exergy concept and its modeled performance.

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