WorldWideScience

Sample records for bi-weekly space segment

  1. AGOR 28: SIO Shipyard Representative Bi-Weekly Progress Report

    Science.gov (United States)

    2015-07-02

    for Sally Ride. ii. Working on NS5 Hierarchy 4. Operator Concerns: • Acoustic Tiles – No additional tiles have been removed this reporting...period. The yard has covered the tiles in the HVAC and MSD spaces with insulation and Quad=zero. The yard has covered the tiles on the upper level of...the Main Machinery Space on the port side with insulation and Quad-zero. The port and starboard sides of the lower level of the Main Machinery space

  2. AGOR 28 SIO Shipyard Representative Bi-Weekly Progress Report

    Science.gov (United States)

    2014-11-20

    Accommodation Spaces – Work continues primarily on the Foc’sle Deck with most of the stateroom walls up and doors installed. Potable water piping to sinks ...and showers is being finished up on both the foc’sle and 01 decks. HVAC work continues on both decks as well. 01 Deck

  3. AGOR 28: SIO Shipyard Representative Bi-Weekly Progress Report

    Science.gov (United States)

    2014-10-09

    is completed on Armstrong. Cables recently secured into MSD Rm cable trays . • Hi-Fog Piping – With Armstrong’s system installed, DCI has...accommodations and 8 in the machinery spaces working on the large power cables . It’s a start and hopefully it will continue to ramp up as more work

  4. Precision segmented reflectors for space applications

    Science.gov (United States)

    Lehman, David H.; Pawlik, Eugene V.; Meinel, Aden B.; Fichter, W. B.

    1990-08-01

    A project to develop precision segmented reflectors (PSRs) which operate at submillimeter wavelengths is described. The development of a light efficient means for the construction of large-aperture segmented reflecting space-based telescopes is the primary aim of the project. The 20-m Large Deployable Reflector (LDR) telescope is being developed for a survey mission, and it will make use of the reflector panels and materials, structures, and figure control being elaborated for the PSR. The surface accuracy of a 0.9-m PSR panel is shown to be 1.74-micron RMS, the goal of 100-micron RMS positioning accuracy has been achieved for a 4-m erectable structure. A voice-coil actuator for the figure control system architecture demonstrated 1-micron panel control accuracy in a 3-axis evaluation. The PSR technology is demonstrated to be of value for several NASA projects involving optical communications and interferometers as well as missions which make use of large-diameter segmented reflectors.

  5. Frictionless segmented mechanics for controlled space closure.

    Science.gov (United States)

    Andrade, Ildeu

    2017-02-01

    Extraction spaces may be needed to achieve specific orthodontic goals of positioning the dentition in harmony with the craniofacial complex. However, the fundamental reality that determines the occlusion final position is the control exerted by the orthodontist while closing the extraction spaces. A specific treatment objective may require the posterior teeth to remain in a constant position anteroposteriorly as well as vertically, while the anterior teeth occupy the entire extraction site. Another treatment objective may require the opposite, or any number of intentional alternatives of extraction site closure. The present case report describes a simple controlled segmented mechanic system that permitted definable and predictable force systems to be applied and allowed to predict the treatment outcome with confidence. This case was presented to the Brazilian Board of Orthodontics and Dentofacial Orthopedics (BBO) in partial fulfillment of the requirements for Diplomate certification.

  6. Frictionless segmented mechanics for controlled space closure

    Directory of Open Access Journals (Sweden)

    Ildeu Andrade Jr

    Full Text Available ABSTRACT Extraction spaces may be needed to achieve specific orthodontic goals of positioning the dentition in harmony with the craniofacial complex. However, the fundamental reality that determines the occlusion final position is the control exerted by the orthodontist while closing the extraction spaces. A specific treatment objective may require the posterior teeth to remain in a constant position anteroposteriorly as well as vertically, while the anterior teeth occupy the entire extraction site. Another treatment objective may require the opposite, or any number of intentional alternatives of extraction site closure. The present case report describes a simple controlled segmented mechanic system that permitted definable and predictable force systems to be applied and allowed to predict the treatment outcome with confidence. This case was presented to the Brazilian Board of Orthodontics and Dentofacial Orthopedics (BBO in partial fulfillment of the requirements for Diplomate certification.

  7. Phase I trial of concurrent chemoradiotherapy for laryngeal and hypopharyngeal cancers with bi-weekly docetaxel

    International Nuclear Information System (INIS)

    Yoshida, Tomoyuki; Nakamura, Kazuhiro; Simizu, Shigetaka

    2005-01-01

    Docetaxel (DOC) has radiation-sensitizing effects because it synchronizes with the most radiation-sensitive G2/M phase of the cell cycle. From the results of concurrent radiotherapy with weekly DOC administrations in a phase I trial, dose-limiting toxicity (DLT) was mucositis and the recommended dose was 10 mg/m 2 , but the administration schedule was a problem. We planned concurrent radiation therapy in a bi-weekly DOC phase I trial to improve the larynx preservation rate and to determine which schedule and dosage of DOC would yield its inherent cytotoxic effects. We decided the maximum tolerated dose (MTD) and DLT to serve as an index of the appearance of adverse events. Patients with stage II or stage III T2N1 hypopharyngeal cancer or stage II or III laryngeal cancer were included in this study. DOC was administered on the days of initiation of bi-weekly radiation (day 1, day 15, day 29). Radiation was given (2 Gy/day: 5 days per week) for a total of 30 Fr, with a total of 60 Gy. The starting dose of DOC was 30 mg/m 2 (level 1) and the dosage was raised by 5 mg/m 2 at each level. DLT was observed due to mucositis and neutropenia at 40 mg/m 2 (level 3), the MTD was 40 mg/m 2 and the recommended dose (RD) was 35 mg/m 2 . Especially in hypopharyngeal cancer of Grade 3 or more, mucositis appeared, with swallowing difficulty in cases with a wide range of irradiation. At dosages of 35 mg/m 2 , the effectiveness was favorable and this was the suitable dosage recommended for the subsequent phase II trial. This clinical study was performed with permission of our IRB (Institutional Review Board). (author)

  8. Successful and well-tolerated bi-weekly immunoadsorption regimen in pemphigus vulgaris.

    Science.gov (United States)

    Dietze, Jenny; Hohenstein, Bernd; Tselmin, Sergey; Julius, Ulrich; Bornstein, Stefan R; Beissert, Stefan; Günther, Claudia

    2017-11-01

    Pemphigus vulgaris is a chronic autoimmune disease characterized by blisters and erosions forming in the mucous membranes and the skin. Many patients are severely impaired by pain, weight loss and increased risk of infections. The disease is mediated by specific autoantibodies directed against desmogleins that contribute to connect keratinocytes in the epidermis. Autoantibody deposition in the skin causes inflammation and intraepidermal akantholysis. The concentration of autoantibodies in serum correlates with disease activity. Therefore, the removal of autoantibodies by immunoadsorption is a targeted therapeutic intervention for patients with pemphigus vulgaris. A total of 9 patients with pemphigus vulgaris resistant to the standard treatment regimen were treated by immunoadsorption using the TheraSorb™-Ig adsorber system and analyzed retrospectively. Patients received immunoadsorption on two or four consecutive days. Cycles were repeated every two or four weeks, respectively. Treatment was performed for a mean period of 17.5 months (range 6-26). Outcome was measured as improvement in clinical disease analyzed by the investigators global assessment and the reduction of autoantibodies in serum measured by indirect immunofluorescence and ELISA. Tolerability of treatment by patients was evaluated using a visual analog scale. Retrospective analysis of 9 patients consecutively treated by immunoadsorption revealed an 80% reduction of the autoantibody concentration in serum after 6 months of treatment, led to a clinical improvement of disease in combination with classical immunosuppression. Steroid consumption could be reduced by 50% after 30 and 75% after 90 days. Therapy resulted in a total response rate of 89%, with 56% of patients reaching partial and 33% complete remission. The bi-weekly treatment regimen resulted in effective improvement of disease and was in favor to the 4-weekly regimen by the subjective judgment of tolerability by the patients

  9. Frictionless segmented mechanics for controlled space closure

    OpenAIRE

    Andrade Jr, Ildeu

    2017-01-01

    ABSTRACT Extraction spaces may be needed to achieve specific orthodontic goals of positioning the dentition in harmony with the craniofacial complex. However, the fundamental reality that determines the occlusion final position is the control exerted by the orthodontist while closing the extraction spaces. A specific treatment objective may require the posterior teeth to remain in a constant position anteroposteriorly as well as vertically, while the anterior teeth occupy the entire extractio...

  10. Image Segmentation and Processing for Efficient Parking Space Analysis

    OpenAIRE

    Tutika, Chetan Sai; Vallapaneni, Charan; R, Karthik; KP, Bharath; Muthu, N Ruban Rajesh Kumar

    2018-01-01

    In this paper, we develop a method to detect vacant parking spaces in an environment with unclear segments and contours with the help of MATLAB image processing capabilities. Due to the anomalies present in the parking spaces, such as uneven illumination, distorted slot lines and overlapping of cars. The present-day conventional algorithms have difficulties processing the image for accurate results. The algorithm proposed uses a combination of image pre-processing and false contour detection ...

  11. Color image segmentation using perceptual spaces through applets ...

    African Journals Online (AJOL)

    HP-630

    2013-02-13

    Feb 13, 2013 ... automatic methods to detect plant diseases. An area that offers this possibility is the digital processing of color images. Currently, the digital image processing .... opening (or lock) reconstruction. 3. Applies color segmentation method with each perceptual space. This method is applied for each channel (hue ...

  12. Color image segmentation using perceptual spaces through applets ...

    African Journals Online (AJOL)

    Color image segmentation using perceptual spaces through applets for determining and preventing diseases in chili peppers. JL González-Pérez, MC Espino-Gudiño, J Gudiño-Bazaldúa, JL Rojas-Rentería, V Rodríguez-Hernández, VM Castaño ...

  13. Hierarchical Segmentation Using Tree-Based Shape Spaces.

    Science.gov (United States)

    Xu, Yongchao; Carlinet, Edwin; Geraud, Thierry; Najman, Laurent

    2017-03-01

    Current trends in image segmentation are to compute a hierarchy of image segmentations from fine to coarse. A classical approach to obtain a single meaningful image partition from a given hierarchy is to cut it in an optimal way, following the seminal approach of the scale-set theory. While interesting in many cases, the resulting segmentation, being a non-horizontal cut, is limited by the structure of the hierarchy. In this paper, we propose a novel approach that acts by transforming an input hierarchy into a new saliency map. It relies on the notion of shape space: a graph representation of a set of regions extracted from the image. Each region is characterized with an attribute describing it. We weigh the boundaries of a subset of meaningful regions (local minima) in the shape space by extinction values based on the attribute. This extinction-based saliency map represents a new hierarchy of segmentations highlighting regions having some specific characteristics. Each threshold of this map represents a segmentation which is generally different from any cut of the original hierarchy. This new approach thus enlarges the set of possible partition results that can be extracted from a given hierarchy. Qualitative and quantitative illustrations demonstrate the usefulness of the proposed method.

  14. Space Network Ground Segment Sustainment (SGSS) Project: Developing a COTS-Intensive Ground System

    Science.gov (United States)

    Saylor, Richard; Esker, Linda; Herman, Frank; Jacobsohn, Jeremy; Saylor, Rick; Hoffman, Constance

    2013-01-01

    Purpose of the Space Network Ground Segment Sustainment (SGSS) is to implement a new modern ground segment that will enable the NASA Space Network (SN) to deliver high quality services to the SN community for the future The key SGSS Goals: (1) Re-engineer the SN ground segment (2) Enable cost efficiencies in the operability and maintainability of the broader SN.

  15. Apodized Pupil Lyot Coronagraphs designs for future segmented space telescopes

    Science.gov (United States)

    St. Laurent, Kathryn; Fogarty, Kevin; Zimmerman, Neil; N’Diaye, Mamadou; Stark, Chris; Sivaramakrishnan, Anand; Pueyo, Laurent; Vanderbei, Robert; Soummer, Remi

    2018-01-01

    A coronagraphic starlight suppression system situated on a future flagship space observatory offers a promising avenue to image Earth-like exoplanets and search for biomarkers in their atmospheric spectra. One NASA mission concept that could serve as the platform to realize this scientific breakthrough is the Large UV/Optical/IR Surveyor (LUVOIR). Such a mission would also address a broad range of topics in astrophysics with a multi-wavelength suite of instruments.In support of the community’s assessment of the scientific capability of a LUVOIR mission, the Exoplanet Exploration Program (ExEP) has launched a multi-team technical study: Segmented Coronagraph Design and Analysis (SCDA). The goal of this study is to develop viable coronagraph instrument concepts for a LUVOIR-type mission. Results of the SCDA effort will directly inform the mission concept evaluation being carried out by the LUVOIR Science and Technology Definition Team. The apodized pupil Lyot coronagraph (APLC) is one of several coronagraph design families that the SCDA study is assessing. The APLC is a Lyot-style coronagraph that suppresses starlight through a series of amplitude operations on the on-axis field. Given a suite of seven plausible segmented telescope apertures, we have developed an object-oriented software toolkit to automate the exploration of thousands of APLC design parameter combinations. In the course of exploring this parameter space we have established relationships between APLC throughput and telescope aperture geometry, Lyot stop, inner working angle, bandwidth, and contrast level. In parallel with the parameter space exploration, we have investigated several strategies to improve the robustness of APLC designs to fabrication and alignment errors and integrated a Design Reference Mission framework to evaluate designs with scientific yield metrics.

  16. Status and progress in the Space Surveillance and Tracking Segment of ESA's Space Situational Awareness Programme

    Science.gov (United States)

    Fletcher, E.

    2010-09-01

    In November 2008, the European Space Agency (ESA) Council at Ministerial level approved the start of ESA’s Space Situational Awareness programme. Between 2009 and 2012 a preparatory phase will run that will develop the architectural design of the system, the governance and data policy and the provision of precursor services in the areas of: Space Surveillance and Tracking, Space Weather and Near Earth Objects. This paper will concentrate on the first of these segments: Space Surveillance and Tracking. It will develop the following main topics: Customer requirements and their integration, the initiation of an integrated catalogue, extension of correlated data to service provision and international cooperation and data fusion The development of the services resulting from these points will be a key driver in the final architecture. This architecture will be proposed at the next Ministerial Council to further develop a full SSA system from 2012 onwards.

  17. White blood cell segmentation by color-space-based k-means clustering.

    Science.gov (United States)

    Zhang, Congcong; Xiao, Xiaoyan; Li, Xiaomei; Chen, Ying-Jie; Zhen, Wu; Chang, Jun; Zheng, Chengyun; Liu, Zhi

    2014-09-01

    White blood cell (WBC) segmentation, which is important for cytometry, is a challenging issue because of the morphological diversity of WBCs and the complex and uncertain background of blood smear images. This paper proposes a novel method for the nucleus and cytoplasm segmentation of WBCs for cytometry. A color adjustment step was also introduced before segmentation. Color space decomposition and k-means clustering were combined for segmentation. A database including 300 microscopic blood smear images were used to evaluate the performance of our method. The proposed segmentation method achieves 95.7% and 91.3% overall accuracy for nucleus segmentation and cytoplasm segmentation, respectively. Experimental results demonstrate that the proposed method can segment WBCs effectively with high accuracy.

  18. Color Image Segmentation Based on Different Color Space Models Using Automatic GrabCut

    OpenAIRE

    Khattab, Dina; Ebied, Hala Mousher; Hussein, Ashraf Saad; Tolba, Mohamed Fahmy

    2014-01-01

    This paper presents a comparative study using different color spaces to evaluate the performance of color image segmentation using the automatic GrabCut technique. GrabCut is considered as one of the semiautomatic image segmentation techniques, since it requires user interaction for the initialization of the segmentation process. The automation of the GrabCut technique is proposed as a modification of the original semiautomatic one in order to eliminate the user interaction. The automatic Gra...

  19. Feature-space transformation improves supervised segmentation across scanners

    DEFF Research Database (Denmark)

    van Opbroek, Annegreet; Achterberg, Hakim C.; de Bruijne, Marleen

    2015-01-01

    Image-segmentation techniques based on supervised classification generally perform well on the condition that training and test samples have the same feature distribution. However, if training and test images are acquired with different scanners or scanning parameters, their feature distributions...

  20. Multilevel space-time aggregation for bright field cell microscopy segmentation and tracking.

    Science.gov (United States)

    Inglis, Tiffany; De Sterck, Hans; Sanders, Geoffrey; Djambazian, Haig; Sladek, Robert; Sundararajan, Saravanan; Hudson, Thomas J

    2010-01-01

    A multilevel aggregation method is applied to the problem of segmenting live cell bright field microscope images. The method employed is a variant of the so-called "Segmentation by Weighted Aggregation" technique, which itself is based on Algebraic Multigrid methods. The variant of the method used is described in detail, and it is explained how it is tailored to the application at hand. In particular, a new scale-invariant "saliency measure" is proposed for deciding when aggregates of pixels constitute salient segments that should not be grouped further. It is shown how segmentation based on multilevel intensity similarity alone does not lead to satisfactory results for bright field cells. However, the addition of multilevel intensity variance (as a measure of texture) to the feature vector of each aggregate leads to correct cell segmentation. Preliminary results are presented for applying the multilevel aggregation algorithm in space time to temporal sequences of microscope images, with the goal of obtaining space-time segments ("object tunnels") that track individual cells. The advantages and drawbacks of the space-time aggregation approach for segmentation and tracking of live cells in sequences of bright field microscope images are presented, along with a discussion on how this approach may be used in the future work as a building block in a complete and robust segmentation and tracking system.

  1. Strength of tensed and compressed concrete segments in crack spacing under short-term dynamic load

    Directory of Open Access Journals (Sweden)

    Galyautdinov Zaur

    2018-01-01

    Full Text Available Formation of model describing dynamic straining of reinforced concrete requires taking into account the basic aspects influencing the stress-strain state of structures. Strength of concrete segments in crack spacing is one of the crucial aspects that affect general strain behavior of reinforced concrete. Experimental results demonstrate significant change in strength of tensed and compressed concrete segments in crack spacing both under static and under dynamic loading. In this case, strength depends on tensile strain level and the slope angle of rebars towards the cracks direction. Existing theoretical and experimental studies estimate strength of concrete segments in crack spacing under static loading. The present work presents results of experimental and theoretical studies of dynamic strength of plates between cracks subjected to compression-tension. Experimental data was analyzed statistically; the dependences were suggested to describe dynamic strength of concrete segments depending on tensile strain level and slope angle of rebars to cracks direction.

  2. Multi-atlas and unsupervised learning approach to perirectal space segmentation in CT images.

    Science.gov (United States)

    Ghose, Soumya; Denham, James W; Ebert, Martin A; Kennedy, Angel; Mitra, Jhimli; Dowling, Jason A

    2016-12-01

    Perirectal space segmentation in computed tomography images aids in quantifying radiation dose received by healthy tissues and toxicity during the course of radiation therapy treatment of the prostate. Radiation dose normalised by tissue volume facilitates predicting outcomes or possible harmful side effects of radiation therapy treatment. Manual segmentation of the perirectal space is time consuming and challenging in the presence of inter-patient anatomical variability and may suffer from inter- and intra-observer variabilities. However automatic or semi-automatic segmentation of the perirectal space in CT images is a challenging task due to inter patient anatomical variability, contrast variability and imaging artifacts. In the model presented here, a volume of interest is obtained in a multi-atlas based segmentation approach. Un-supervised learning in the volume of interest with a Gaussian-mixture-modeling based clustering approach is adopted to achieve a soft segmentation of the perirectal space. Probabilities from soft clustering are further refined by rigid registration of the multi-atlas mask in a probabilistic domain. A maximum a posteriori approach is adopted to achieve a binary segmentation from the refined probabilities. A mean volume similarity value of 97% and a mean surface difference of 3.06 ± 0.51 mm is achieved in a leave-one-patient-out validation framework with a subset of a clinical trial dataset. Qualitative results show a good approximation of the perirectal space volume compared to the ground truth.

  3. End-to-end simulation and verification of GNC and robotic systems considering both space segment and ground segment

    Science.gov (United States)

    Benninghoff, Heike; Rems, Florian; Risse, Eicke; Brunner, Bernhard; Stelzer, Martin; Krenn, Rainer; Reiner, Matthias; Stangl, Christian; Gnat, Marcin

    2018-01-01

    In the framework of a project called on-orbit servicing end-to-end simulation, the final approach and capture of a tumbling client satellite in an on-orbit servicing mission are simulated. The necessary components are developed and the entire end-to-end chain is tested and verified. This involves both on-board and on-ground systems. The space segment comprises a passive client satellite, and an active service satellite with its rendezvous and berthing payload. The space segment is simulated using a software satellite simulator and two robotic, hardware-in-the-loop test beds, the European Proximity Operations Simulator (EPOS) 2.0 and the OOS-Sim. The ground segment is established as for a real servicing mission, such that realistic operations can be performed from the different consoles in the control room. During the simulation of the telerobotic operation, it is important to provide a realistic communication environment with different parameters like they occur in the real world (realistic delay and jitter, for example).

  4. Scale-space for empty catheter segmentation in PCI fluoroscopic images.

    Science.gov (United States)

    Bacchuwar, Ketan; Cousty, Jean; Vaillant, Régis; Najman, Laurent

    2017-07-01

    In this article, we present a method for empty guiding catheter segmentation in fluoroscopic X-ray images. The guiding catheter, being a commonly visible landmark, its segmentation is an important and a difficult brick for Percutaneous Coronary Intervention (PCI) procedure modeling. In number of clinical situations, the catheter is empty and appears as a low contrasted structure with two parallel and partially disconnected edges. To segment it, we work on the level-set scale-space of image, the min tree, to extract curve blobs. We then propose a novel structural scale-space, a hierarchy built on these curve blobs. The deep connected component, i.e. the cluster of curve blobs on this hierarchy, that maximizes the likelihood to be an empty catheter is retained as final segmentation. We evaluate the performance of the algorithm on a database of 1250 fluoroscopic images from 6 patients. As a result, we obtain very good qualitative and quantitative segmentation performance, with mean precision and recall of 80.48 and 63.04% respectively. We develop a novel structural scale-space to segment a structured object, the empty catheter, in challenging situations where the information content is very sparse in the images. Fully-automatic empty catheter segmentation in X-ray fluoroscopic images is an important and preliminary step in PCI procedure modeling, as it aids in tagging the arrival and removal location of other interventional tools.

  5. Detection and segmentation of intersection and branch structures in medical images using orientation space

    International Nuclear Information System (INIS)

    Chen, Jian; Sato, Yoshinobu; Tamura, Shinichi

    1999-01-01

    The purpose of this paper is to present appropriate line segmentation for intersections (X-junctions) and branches (T-junctions). In the local regions of intersections and branches, multiple orientations occur. We propose a novel representation called the ''orientation space'', which is derived by adding the orientation axis to the abscissa and the ordinate of the image. The orientation space representation is constructed by treating the orientation parameter, to which Gabor filters can be tuned, as a continuous variable. The problem of multiple orientation line segmentation is dealt with by thresholding 3D images of the orientation space and then detecting the connected components therein. In this way, X-junctions and T-junctions can be separated effectively. Experimental results obtained using synthesized and real biomedical images are presented. In particular, overlapping vessels in an X-ray coronary angiogram were well segmented by orientation space filtering. (author)

  6. Renal segmentation in physiological feature space with dynamic contrast enhanced MR Urography: preliminary research

    Science.gov (United States)

    Tang, Yang; Jackson, Hollie A.; De Filippo, Roger E.; Lee, Susan; Nelson, Marvin D., Jr.; Moats, Rex A.

    2009-10-01

    The kidney is composed of many structurally and functionally different tissues. These functionally distinct tissues exhibit different magnetic resonance signal characteristics in typical MR Urography. This work exploits the tissue functional differences to construct a physiological feature space for renal segmentation, which has the more distinct meaning for directly functional evaluation, and lower requirements for storage and computation. In this preliminary research, a segmentation method was developed and investigated to demonstrate its feasibility on images obtained using a typical MR Urograpy protocol.

  7. Outer Wall Segmentation of Abdominal Aortic Aneurysm by Variable Neighborhood Search Through Intensity and Gradient Spaces.

    Science.gov (United States)

    Siriapisith, Thanongchai; Kusakunniran, Worapan; Haddawy, Peter

    2018-01-19

    Aortic aneurysm segmentation remains a challenge. Manual segmentation is a time-consuming process which is not practical for routine use. To address this limitation, several automated segmentation techniques for aortic aneurysm have been developed, such as edge detection-based methods, partial differential equation methods, and graph partitioning methods. However, automatic segmentation of aortic aneurysm is difficult due to high pixel similarity to adjacent tissue and a lack of color information in the medical image, preventing previous work from being applicable to difficult cases. This paper uses uses a variable neighborhood search that alternates between intensity-based and gradient-based segmentation techniques. By alternating between intensity and gradient spaces, the search can escape from local optima of each space. The experimental results demonstrate that the proposed method outperforms the other existing segmentation methods in the literature, based on measurements of dice similarity coefficient and jaccard similarity coefficient at the pixel level. In addition, it is shown to perform well for cases that are difficult to segment.

  8. Segmentation of wounds in the combined color-texture feature space

    Science.gov (United States)

    Kolesnik, Marina; Fexa, Alex

    2004-05-01

    In this work we describe an application of the Support Vector Machine (SVM) classifier for the segmentation of wounds in color images. The SVM-based segmentation combines naturally a high dimensional space of image features into a single classification machine. Since particular choice of image features is crucial for the performance of SVM classifier, we investigate the efficiency of color- and texture-based features for the differentiation between skin and wound tissue. We find that color features provide better separation between these two tissues. However, incorporation of even a single textural feature improves an overall quality of the SVM classification. We test the impact of each color feature on the quality of wound segmentation and find optimal combination of these features which produces best segmentation result. We suggest a Histogram Sampling technique, which gives wider separation between wound and skin in the color space. Finally, we find a set of image features, which is typical for most types of wounds. When these features are used as an input to the SVM classifier, a fairly robust segmentation of different wound types is achieved. We evaluate the performance of SVM-based segmentation using ground-truth segmentation carried out by clinicians.

  9. James Webb Space Telescope Optical Simulation Testbed: Segmented Mirror Phase Retrieval Testing

    Science.gov (United States)

    Laginja, Iva; Egron, Sylvain; Brady, Greg; Soummer, Remi; Lajoie, Charles-Philippe; Bonnefois, Aurélie; Long, Joseph; Michau, Vincent; Choquet, Elodie; Ferrari, Marc; Leboulleux, Lucie; Mazoyer, Johan; N’Diaye, Mamadou; Perrin, Marshall; Petrone, Peter; Pueyo, Laurent; Sivaramakrishnan, Anand

    2018-01-01

    The James Webb Space Telescope (JWST) Optical Simulation Testbed (JOST) is a hardware simulator designed to produce JWST-like images. A model of the JWST three mirror anastigmat is realized with three lenses in form of a Cooke Triplet, which provides JWST-like optical quality over a field equivalent to a NIRCam module, and an Iris AO segmented mirror with hexagonal elements is standing in for the JWST segmented primary. This setup successfully produces images extremely similar to NIRCam images from cryotesting in terms of the PSF morphology and sampling relative to the diffraction limit.The testbed is used for staff training of the wavefront sensing and control (WFS&C) team and for independent analysis of WFS&C scenarios of the JWST. Algorithms like geometric phase retrieval (GPR) that may be used in flight and potential upgrades to JWST WFS&C will be explored. We report on the current status of the testbed after alignment, implementation of the segmented mirror, and testing of phase retrieval techniques.This optical bench complements other work at the Makidon laboratory at the Space Telescope Science Institute, including the investigation of coronagraphy for segmented aperture telescopes. Beyond JWST we intend to use JOST for WFS&C studies for future large segmented space telescopes such as LUVOIR.

  10. Coarse-to-Fine Segmentation with Shape-Tailored Continuum Scale Spaces

    KAUST Repository

    Khan, Naeemullah

    2017-11-09

    We formulate an energy for segmentation that is designed to have preference for segmenting the coarse over fine structure of the image, without smoothing across boundaries of regions. The energy is formulated by integrating a continuum of scales from a scale space computed from the heat equation within regions. We show that the energy can be optimized without computing a continuum of scales, but instead from a single scale. This makes the method computationally efficient in comparison to energies using a discrete set of scales. We apply our method to texture and motion segmentation. Experiments on benchmark datasets show that a continuum of scales leads to better segmentation accuracy over discrete scales and other competing methods.

  11. James Webb Space Telescope optical simulation testbed IV: linear control alignment of the primary segmented mirror

    Science.gov (United States)

    Egron, Sylvain; Soummer, Rémi; Lajoie, Charles-Philippe; Bonnefois, Aurélie; Long, Joseph; Michau, Vincent; Choquet, Elodie; Ferrari, Marc; Leboulleux, Lucie; Levecq, Olivier; Mazoyer, Johan; N'Diaye, Mamadou; Perrin, Marshall; Petrone, Peter; Pueyo, Laurent; Sivaramakrishnan, Anand

    2017-09-01

    The James Webb Space Telescope (JWST) Optical Simulation Testbed (JOST) is a tabletop experiment designed to study wavefront sensing and control for a segmented space telescope, such as JWST. With the JWST Science and Operations Center co-located at STScI, JOST was developed to provide both a platform for staff training and to test alternate wavefront sensing and control strategies for independent validation or future improvements beyond the baseline operations. The design of JOST reproduces the physics of JWST's three-mirror anastigmat (TMA) using three custom aspheric lenses. It provides similar quality image as JWST (80% Strehl ratio) over a field equivalent to a NIRCam module, but at 633 nm. An Iris AO segmented mirror stands for the segmented primary mirror of JWST. Actuators allow us to control (1) the 18 segments of the segmented mirror in piston, tip, tilt and (2) the second lens, which stands for the secondary mirror, in tip, tilt and x, y, z positions. We present the most recent experimental results for the segmented mirror alignment. Our implementation of the Wavefront Sensing (WFS) algorithms using phase diversity is tested on simulation and experimentally. The wavefront control (WFC) algorithms, which rely on a linear model for optical aberrations induced by misalignment of the secondary lens and the segmented mirror, are tested and validated both on simulations and experimentally. In this proceeding, we present the performance of the full active optic control loop in presence of perturbations on the segmented mirror, and we detail the quality of the alignment correction.

  12. Edge detection and image segmentation of space scenes using fractal analyses

    Science.gov (United States)

    Cleghorn, Timothy F.; Fuller, J. J.

    1992-01-01

    A method was developed for segmenting images of space scenes into manmade and natural components, using fractal dimensions and lacunarities. Calculations of these parameters are presented. Results are presented for a variety of aerospace images, showing that it is possible to perform edge detections of manmade objects against natural background such as those seen in an aerospace environment.

  13. Exploration of sequence space as the basis of viral RNA genome segmentation.

    Science.gov (United States)

    Moreno, Elena; Ojosnegros, Samuel; García-Arriaza, Juan; Escarmís, Cristina; Domingo, Esteban; Perales, Celia

    2014-05-06

    The mechanisms of viral RNA genome segmentation are unknown. On extensive passage of foot-and-mouth disease virus in baby hamster kidney-21 cells, the virus accumulated multiple point mutations and underwent a transition akin to genome segmentation. The standard single RNA genome molecule was replaced by genomes harboring internal in-frame deletions affecting the L- or capsid-coding region. These genomes were infectious and killed cells by complementation. Here we show that the point mutations in the nonstructural protein-coding region (P2, P3) that accumulated in the standard genome before segmentation increased the relative fitness of the segmented version relative to the standard genome. Fitness increase was documented by intracellular expression of virus-coded proteins and infectious progeny production by RNAs with the internal deletions placed in the sequence context of the parental and evolved genome. The complementation activity involved several viral proteins, one of them being the leader proteinase L. Thus, a history of genetic drift with accumulation of point mutations was needed to allow a major variation in the structure of a viral genome. Thus, exploration of sequence space by a viral genome (in this case an unsegmented RNA) can reach a point of the space in which a totally different genome structure (in this case, a segmented RNA) is favored over the form that performed the exploration.

  14. Angular Spacing Control for Segmented Data Pages in Angle-Multiplexed Holographic Memory

    Science.gov (United States)

    Kinoshita, Nobuhiro; Muroi, Tetsuhiko; Ishii, Norihiko; Kamijo, Koji; Kikuchi, Hiroshi; Shimidzu, Naoki; Ando, Toshio; Masaki, Kazuyoshi; Shimizu, Takehiro

    2011-09-01

    To improve the recording density of angle-multiplexed holographic memory, it is effective to increase the numerical aperture of the lens and to shorten the wavelength of the laser source as well as to increase the multiplexing number. The angular selectivity of a hologram, which determines the multiplexing number, is dependent on the incident angle of not only the reference beam but also the signal beam to the holographic recording medium. The actual signal beam, which is a convergent or divergent beam, is regarded as the sum of plane waves that have different propagation directions, angular selectivities, and optimal angular spacings. In this paper, focusing on the differences in the optimal angular spacing, we proposed a method to control the angular spacing for each segmented data page. We investigated the angular selectivity of a hologram and crosstalk for segmented data pages using numerical simulation. The experimental results showed a practical bit-error rate on the order of 10-3.

  15. Geometric shapes inversion method of space targets by ISAR image segmentation

    Science.gov (United States)

    Huo, Chao-ying; Xing, Xiao-yu; Yin, Hong-cheng; Li, Chen-guang; Zeng, Xiang-yun; Xu, Gao-gui

    2017-11-01

    The geometric shape of target is an effective characteristic in the process of space targets recognition. This paper proposed a method of shape inversion of space target based on components segmentation from ISAR image. The Radon transformation, Hough transformation, K-means clustering, triangulation will be introduced into ISAR image processing. Firstly, we use Radon transformation and edge detection to extract space target's main body spindle and solar panel spindle from ISAR image. Then the targets' main body, solar panel, rectangular and circular antenna are segmented from ISAR image based on image detection theory. Finally, the sizes of every structural component are computed. The effectiveness of this method is verified using typical targets' simulation data.

  16. A segmented appliance for space closure followed by Invisalign and fixed appliances.

    Science.gov (United States)

    Uribe, Flavio; Cutrera, Alice; Nanda, Ravinda

    2011-01-01

    This case report describes the use of a segmented appliance for space closure prior to using Invisalign. The maxillary right canine was retracted into the extracted first premolar space with a sectional wire from the first molar to the canine with no visible brackets in the incisor region. The advantage of this technique is the ability to achieve better root and rotational control during space closure with a fixed appliance that also has limited visibility. A maxillary fixed appliance was used to refine the esthetics in the maxillary arch due to the limitations of the Invisalign appliance in achieving rotational and vertical movements.

  17. Hybrid time-space dynamical systems of growth bacteria with applications in segmentation.

    Science.gov (United States)

    Ibrahim, Rabha W; Nashine, Hemant K; Kamaruddin, Norshaliza

    2017-10-01

    A biological dynamic system carries engineering properties such as control systems and signal processing (or image processing) addicted to molecular biology at the level of bio-molecular communication networks. Dynamical system features and signal reply functions of cellular signaling pathways are some of the main topics in biological dynamic systems (for example the biological segmentation). In the present paper, we introduce new generalized hybrid time-space dynamical systems of growing bacteria. We impose the approximate analytic solution for the system. The generalization adapted the concepts of the Riemann-Liouville fractional operators for time and the Srivastava-Owa fractional operators for space. Moreover, we introduce a numerical perturbation method of two operators to obtain the approximate solutions. We establish the existence and uniqueness results and impose some applications in the sequel. Moreover, we study the Ulam stability and apply these stable solutions to improve the segmentation of a class of growing bacteria. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Wavelet-space correlation imaging for high-speed MRI without motion monitoring or data segmentation.

    Science.gov (United States)

    Li, Yu; Wang, Hui; Tkach, Jean; Roach, David; Woods, Jason; Dumoulin, Charles

    2015-12-01

    This study aims to (i) develop a new high-speed MRI approach by implementing correlation imaging in wavelet-space, and (ii) demonstrate the ability of wavelet-space correlation imaging to image human anatomy with involuntary or physiological motion. Correlation imaging is a high-speed MRI framework in which image reconstruction relies on quantification of data correlation. The presented work integrates correlation imaging with a wavelet transform technique developed originally in the field of signal and image processing. This provides a new high-speed MRI approach to motion-free data collection without motion monitoring or data segmentation. The new approach, called "wavelet-space correlation imaging", is investigated in brain imaging with involuntary motion and chest imaging with free-breathing. Wavelet-space correlation imaging can exceed the speed limit of conventional parallel imaging methods. Using this approach with high acceleration factors (6 for brain MRI, 16 for cardiac MRI, and 8 for lung MRI), motion-free images can be generated in static brain MRI with involuntary motion and nonsegmented dynamic cardiac/lung MRI with free-breathing. Wavelet-space correlation imaging enables high-speed MRI in the presence of involuntary motion or physiological dynamics without motion monitoring or data segmentation. © 2014 Wiley Periodicals, Inc.

  19. Object-Based Change Detection in Urban Areas: The Effects of Segmentation Strategy, Scale, and Feature Space on Unsupervised Methods

    Directory of Open Access Journals (Sweden)

    Lei Ma

    2016-09-01

    Full Text Available Object-based change detection (OBCD has recently been receiving increasing attention as a result of rapid improvements in the resolution of remote sensing data. However, some OBCD issues relating to the segmentation of high-resolution images remain to be explored. For example, segmentation units derived using different segmentation strategies, segmentation scales, feature space, and change detection methods have rarely been assessed. In this study, we have tested four common unsupervised change detection methods using different segmentation strategies and a series of segmentation scale parameters on two WorldView-2 images of urban areas. We have also evaluated the effect of adding extra textural and Normalized Difference Vegetation Index (NDVI information instead of using only spectral information. Our results indicated that change detection methods performed better at a medium scale than at a fine scale where close to the pixel size. Multivariate Alteration Detection (MAD always outperformed the other methods tested, at the same confidence level. The overall accuracy appeared to benefit from using a two-date segmentation strategy rather than single-date segmentation. Adding textural and NDVI information appeared to reduce detection accuracy, but the magnitude of this reduction was not consistent across the different unsupervised methods and segmentation strategies. We conclude that a two-date segmentation strategy is useful for change detection in high-resolution imagery, but that the optimization of thresholds is critical for unsupervised change detection methods. Advanced methods need be explored that can take advantage of additional textural or other parameters.

  20. A scale space approach for automatically segmenting words from historical handwritten documents.

    Science.gov (United States)

    Manmatha, R; Rothfeder, Jamie L

    2005-08-01

    Many libraries, museums, and other organizations contain large collections of handwritten historical documents, for example, the papers of early presidents like George Washington at the Library of Congress. The first step in providing recognition/ retrieval tools is to automatically segment handwritten pages into words. State of the art segmentation techniques like the gap metrics algorithm have been mostly developed and tested on highly constrained documents like bank checks and postal addresses. There has been little work on full handwritten pages and this work has usually involved testing on clean artificial documents created for the purpose of research. Historical manuscript images, on the other hand, contain a great deal of noise and are much more challenging. Here, a novel scale space algorithm for automatically segmenting handwritten (historical) documents into words is described. First, the page is cleaned to remove margins. This is followed by a gray-level projection profile algorithm for finding lines in images. Each line image is then filtered with an anisotropic Laplacian at several scales. This procedure produces blobs which correspond to portions of characters at small scales and to words at larger scales. Crucial to the algorithm is scale selection, that is, finding the optimum scale at which blobs correspond to words. This is done by finding the maximum over scale of the extent or area of the blobs. This scale maximum is estimated using three different approaches. The blobs recovered at the optimum scale are then bounded with a rectangular box to recover the words. A postprocessing filtering step is performed to eliminate boxes of unusual size which are unlikely to correspond to words. The approach is tested on a number of different data sets and it is shown that, on 100 sampled documents from the George Washington corpus of handwritten document images, a total error rate of 17 percent is observed. The technique outperforms a state-of-the-art gap

  1. Design of a quick response SMA actuated segmented nut for space release applications

    Science.gov (United States)

    Zhang, Xiaoyong; Yan, Xiaojun; Yang, Qiaolong

    2010-04-01

    Spacecrafts require a variety of separation and release devices to accommodate separation from the launch vehicle or deployment of heat radiation panels, solar arrays and other appendages. In order to overcome drawbacks of the current release devices, this paper proposes a design scheme of release device with a form of segmented nut and actuated with SMA (Shape Memory Alloy) wire. In order to validate the release device's function and performance, ground tests including single device response time tests, synchronous tests of two devices, fatigue life tests were carried out. Tests results show that the innovative space release device developed in this paper owning the advantages of small size, quick response, long fatigue life, high simultaneity and auto-reset has a potential use in space engineering.

  2. Stereo visualization in the ground segment tasks of the science space missions

    Science.gov (United States)

    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.

  3. Evolution of the SLR ground and space segments and its potential for GGOS

    Science.gov (United States)

    Kehm, Alexander; Bloßfeld, Mathis; Seitz, Florian

    2017-04-01

    SLR is the unique technique that allows determining the geocenter with very high accuracy and contributes to the realization of the scale of a conventional terrestrial reference frame. In addition, due to the high sensitivity of SLR-tracked satellites to the Earth's gravitational field and their mostly simple spherical shape, SLR enables the determination of low-degree spherical harmonic coefficients of the Earth's gravitational field model with high accuracy. In the near future, the SLR network geometry will undergo significant improvements due to the construction of additional SLR stations, such as Brasilia (established in 2014), Argentina (La Plata, operational soon), India (Mount Abu and Ponmudi, planned for 2017), or Spitsbergen (Ny Ålesund, planned for 2019). Furthermore, the SLR space segment will undergo changes due to the launch of additional satellites, e.g. BLITS-II (already planned). Within the present study, the impact of an enhancement of the current SLR ground and space segments on the estimation of consistent orbit parameters, station coordinates, EOP, and low-degree spherical harmonics of the Earth's gravitational field model is investigated. The results are evaluated in terms of the potential of SLR to support the ambitious goals of GGOS. In particular, the study will answer the question to what extent additional stations and/or additional satellites will improve current estimates.

  4. Medial-based deformable models in nonconvex shape-spaces for medical image segmentation.

    Science.gov (United States)

    McIntosh, Chris; Hamarneh, Ghassan

    2012-01-01

    We explore the application of genetic algorithms (GA) to deformable models through the proposition of a novel method for medical image segmentation that combines GA with nonconvex, localized, medial-based shape statistics. We replace the more typical gradient descent optimizer used in deformable models with GA, and the convex, implicit, global shape statistics with nonconvex, explicit, localized ones. Specifically, we propose GA to reduce typical deformable model weaknesses pertaining to model initialization, pose estimation and local minima, through the simultaneous evolution of a large number of models. Furthermore, we constrain the evolution, and thus reduce the size of the search-space, by using statistically-based deformable models whose deformations are intuitive (stretch, bulge, bend) and are driven in terms of localized principal modes of variation, instead of modes of variation across the entire shape that often fail to capture localized shape changes. Although GA are not guaranteed to achieve the global optima, our method compares favorably to the prevalent optimization techniques, convex/nonconvex gradient-based optimizers and to globally optimal graph-theoretic combinatorial optimization techniques, when applied to the task of corpus callosum segmentation in 50 mid-sagittal brain magnetic resonance images.

  5. Approaches to automatic parameter fitting in a microscopy image segmentation pipeline: An exploratory parameter space analysis

    Directory of Open Access Journals (Sweden)

    Christian Held

    2013-01-01

    Full Text Available Introduction: Research and diagnosis in medicine and biology often require the assessment of a large amount of microscopy image data. Although on the one hand, digital pathology and new bioimaging technologies find their way into clinical practice and pharmaceutical research, some general methodological issues in automated image analysis are still open. Methods: In this study, we address the problem of fitting the parameters in a microscopy image segmentation pipeline. We propose to fit the parameters of the pipeline′s modules with optimization algorithms, such as, genetic algorithms or coordinate descents, and show how visual exploration of the parameter space can help to identify sub-optimal parameter settings that need to be avoided. Results: This is of significant help in the design of our automatic parameter fitting framework, which enables us to tune the pipeline for large sets of micrographs. Conclusion: The underlying parameter spaces pose a challenge for manual as well as automated parameter optimization, as the parameter spaces can show several local performance maxima. Hence, optimization strategies that are not able to jump out of local performance maxima, like the hill climbing algorithm, often result in a local maximum.

  6. Legal and Political Implications of Offensive Actions from and Against the Space Segment

    Science.gov (United States)

    de Angelis, Iole M.

    2002-01-01

    deployment of strategic weapons, kinetic energy weapons and directed energy weapons are already contained within existing rules and such issues are being actively addressed by the international community. At the same time, the use of cyberwar and electronic warfare to counter space technology not only encounters a void of international rules, but it is a question that is very rarely taken into consideration while addressing to the issues of preventing space warfare. Finally, these techniques are easily available to non-state organisations - terrorist organisations and commercial companies - and individuals. In conclusion, the issues related to offensive actions towards and from space shall be taken into consideration not only in a military perspective, but also in a political perspective - terrorist actions against the space segment - and from an economical point of view.

  7. Capabilities of a Laser Guide Star for a Large Segmented Space Telescope

    Science.gov (United States)

    Clark, James R.; Carlton, Ashley; Douglas, Ewan S.; Males, Jared R.; Lumbres, Jennifer; Feinberg, Lee; Guyon, Olivier; Marlow, Weston; Cahoy, Kerri L.

    2018-01-01

    Large segmented mirror telescopes are planned for future space telescope missions such as LUVOIR (Large UV Optical Infrared Surveyor) to enable the improvement in resolution and contrast necessary to directly image Earth-like exoplanets, in addition to making contributions to general astrophysics. The precision surface control of these complex, large optical systems, which may have over a hundred meter-sized segments, is a challenge. Our initial simulations show that imaging a star of 2nd magnitude or brighter with a Zernike wavefront sensor should relax the segment stability requirements by factors between 10 and 50 depending on the wavefront control strategy. Fewer than fifty stars brighter than magnitude 2 can be found in the sky. A laser guide star (LGS) on a companion spacecraft will allow the telescope to target a dimmer science star and achieve wavefront control to the required stability without requiring slew or repointing maneuvers.We present initial results for one possible mission architecture, with a LGS flying at 100,000 km range from the large telescope in an L2 halo orbit, using a laser transmit power of vector can be held anywhere on the sky for extended durations (>8 days) for an expenditure of <10 m/s of delta-V per day, or an average thrust <1 mN for a satellite of mass <47 kg. If the LGS uses a low-thrust electric propulsion system, it can be accommodated in a 6U CubeSat bus, but may require an extended period of time to transition between targets and match velocities with the telescope (e.g. 6 days to transit 10 degrees). If the LGS uses monopropellant propulsion, it must use at least a 27U bus to achieve the the same delta-V capability, but can transition between targets much more rapidly (<1 day to transit 10 degrees).Architecture trades on formation flying distance, laser wavelength and power are ongoing. The models of the segments and their disturbances and of the formation flight are being refined. A low-cost prototype mission (e

  8. A segmented K-space velocity mapping protocol for quantification of renal artery blood flow during breath-holding

    DEFF Research Database (Denmark)

    Thomsen, C; Cortsen, M; Söndergaard, L

    1995-01-01

    Two important prerequisites for MR velocity mapping of pulsatile motion are synchronization of the sequence execution to the time course of the flow pattern and robustness toward loss of signal in complex flow fields. Synchronization is normally accomplished by using either prospective ECG...... the segmented k-space technique, in which the entire data acquisition can be made within a breath-hold by the sampling of several phase-encoding lines within a small time window during each heart cycle. The aim of this study was to investigate the performance of a segmented k-space velocity mapping protocol...

  9. [MODERN INSTRUMENTS FOR EAR, NOSE AND THROAT RENDERING AND EVALUATION IN RESEARCHES ON RUSSIAN SEGMENT OF THE INTERNATIONAL SPACE STATION].

    Science.gov (United States)

    Popova, I I; Orlov, O I; Matsnev, E I; Revyakin, Yu G

    2016-01-01

    The paper reports the results of testing some diagnostic video systems enabling digital rendering of TNT teeth and jaws. The authors substantiate the criteria of choosing and integration of imaging systems in future on Russian segment of the International space station kit LOR developed for examination and download of high-quality images of cosmonauts' TNT, parodentium and teeth.

  10. On-board Payload Data Processing from Earth to Space Segment

    Science.gov (United States)

    Tragni, M.; Abbattista, C.; Amoruso, L.; Cinquepalmi, L.; Bgongiari, F.; Errico, W.

    2013-09-01

    Matching the users application requirements with the more and more huge data streaming of the satellite missions is becoming very complex. But we need both of them. To face both the data management (memory availability) and their transmission (band availability) many recent R&D activities are studying the right way to move the data processing from the ground segment to the space segment by the development of the so-called On-board Payload Data Processing (OPDP). The space designer are trying to find new strategies to increase the on board computation capacity and its viability to overcome such limitations, memory and band, focusing the transmission of remote sensing information (not only data) towards their final use. Some typical applications which can benefit of the on board payload data processing include the automatic control of a satellites constellation which can modify its scheduled acquisitions directly on-board and according to the information extracted from the just acquired data, increasing, for example, the capability of monitoring a specific objective (such as oil spills, illegal traffic) with a greater versatility than a traditional ground segment workflow. The authors and their companies can count on a sound experience in design and development of open, modular and compact on-board processing systems. Actually they are involved in a program, the Space Payload Data Processing (SpacePDP) whose main objective is to develop an hardware and a software framework able to perform both the space mission standard tasks (sensors control, mass storage devices management, uplink and downlink) and the specific tasks required by each mission. SpacePDP is an Open and modular Payload Data Processing system, composed of Hardware and Software modules included a SDK. The whole system is characterised by flexible and customizable building blocks that form the system architectures and by a very easy way to be integrated in the missions by the SDK (a development

  11. EEG alpha map series: brain micro-states by space-oriented adaptive segmentation.

    Science.gov (United States)

    Lehmann, D; Ozaki, H; Pal, I

    1987-09-01

    The spontaneous EEG, viewed as a series of momentary scalp field maps, shows stable map configurations (of periodically reversed polarity) for varying durations, and discontinuous changes of the configurations. For adaptive segmentation of map series into spatially stationary epochs, the maps at the times of maximal map relief are selected and spatially described by the two locations of maximal and minimal (extreme) potentials; a segment ends if over time an extreme leaves its pre-set spatial window. Over 6 subjects, the resting alpha EEG showed 210 msec mean segment duration; segments longer than 323 msec covered 50% of the total time; the most prominent segment class (1.5% of all classes) covered 20% of total time (prominence varied strongly over classes; not all possible classes occurred). Spectral power and phase of averages of adaptive and pre-determined segments demonstrated the adequacy of the strategy, and the homogeneity of adaptive segment classes by their reduced within-class variance. It is suggested that different segment classes manifest different brain functional states exerting different effects on information processing. The spatially stationary segments might be basic building blocks of brain information processing, possibly operationalizing consciousness time and offering a common phenomenology for spontaneous activity and event-related potentials. The functional significance of segments might be modes or steps of information processing or performance, tested, e.g., as reaction time.

  12. International two-way satellite time transfers using INTELSAT space segment and small Earth stations

    Science.gov (United States)

    Veenstra, Lester B.

    1990-05-01

    The satellite operated by the International Telecommunications Satellite Organization (INTELSAT) provides new and unique capabilities for the coordinates of international time scales on a world wide basis using the two-way technique. A network of coordinated clocks using small earth stations collocated with the scales is possible. Antennas as small as 1.8 m at K-band and 3 m at C-band transmitting powers of less than 1 W will provide signals with time jitters of less than 1 ns existing spread spectrum modems. One way time broadcasting is also possible, under the INTELSAT INTELNET system, possibly using existing international data distribution (press and financial) systems that are already operating spread spectrum systems. The technical details of the satellite and requirements on satellite earth stations are given. The resources required for a regular operational international time transfer service are analyzed with respect to the existing international digital service offerings of the INTELSAT Business Service (IBS) and INTELNET. Coverage areas, typical link budgets, and a summary of previous domestic and international work using this technique are provided. Administrative procedures for gaining access to the space segment are outlined. Contact information for local INTELSAT signatories is listed.

  13. Data Transformation Functions for Expanded Search Spaces in Geographic Sample Supervised Segment Generation

    OpenAIRE

    Fourie, Christoffel Ettienne; Schöpfer, Elisabeth

    2014-01-01

    Sample supervised image analysis, in particular sample supervised segment generation, shows promise as a methodological avenue applicable within Geographic Object-Based Image Analysis (GEOBIA). Segmentation is acknowledged as a constituent component within typically expansive image analysis processes. A general extension to the basic formulation of an empirical discrepancy measure directed segmentation algorithm parameter tuning approach is proposed. An expanded search landscape is defined, c...

  14. A NEW FRAMEWORK FOR OBJECT-BASED IMAGE ANALYSIS BASED ON SEGMENTATION SCALE SPACE AND RANDOM FOREST CLASSIFIER

    Directory of Open Access Journals (Sweden)

    A. Hadavand

    2015-12-01

    Full Text Available In this paper a new object-based framework is developed for automate scale selection in image segmentation. The quality of image objects have an important impact on further analyses. Due to the strong dependency of segmentation results to the scale parameter, choosing the best value for this parameter, for each class, becomes a main challenge in object-based image analysis. We propose a new framework which employs pixel-based land cover map to estimate the initial scale dedicated to each class. These scales are used to build segmentation scale space (SSS, a hierarchy of image objects. Optimization of SSS, respect to NDVI and DSM values in each super object is used to get the best scale in local regions of image scene. Optimized SSS segmentations are finally classified to produce the final land cover map. Very high resolution aerial image and digital surface model provided by ISPRS 2D semantic labelling dataset is used in our experiments. The result of our proposed method is comparable to those of ESP tool, a well-known method to estimate the scale of segmentation, and marginally improved the overall accuracy of classification from 79% to 80%.

  15. Data Transformation Functions for Expanded Search Spaces in Geographic Sample Supervised Segment Generation

    Directory of Open Access Journals (Sweden)

    Christoff Fourie

    2014-04-01

    Full Text Available Sample supervised image analysis, in particular sample supervised segment generation, shows promise as a methodological avenue applicable within Geographic Object-Based Image Analysis (GEOBIA. Segmentation is acknowledged as a constituent component within typically expansive image analysis processes. A general extension to the basic formulation of an empirical discrepancy measure directed segmentation algorithm parameter tuning approach is proposed. An expanded search landscape is defined, consisting not only of the segmentation algorithm parameters, but also of low-level, parameterized image processing functions. Such higher dimensional search landscapes potentially allow for achieving better segmentation accuracies. The proposed method is tested with a range of low-level image transformation functions and two segmentation algorithms. The general effectiveness of such an approach is demonstrated compared to a variant only optimising segmentation algorithm parameters. Further, it is shown that the resultant search landscapes obtained from combining mid- and low-level image processing parameter domains, in our problem contexts, are sufficiently complex to warrant the use of population based stochastic search methods. Interdependencies of these two parameter domains are also demonstrated, necessitating simultaneous optimization.

  16. Marginal space learning for medical image analysis efficient detection and segmentation of anatomical structures

    CERN Document Server

    Zheng, Yefeng

    2014-01-01

    Presents an award winning image analysis technology (Thomas Edison Patent Award, MICCAI Young Investigator Award) that achieves object detection and segmentation with state-of-the-art accuracy and efficiency Flexible, machine learning-based framework, applicable across multiple anatomical structures and imaging modalities Thirty five clinical applications on detecting and segmenting anatomical structures such as heart chambers and valves, blood vessels, liver, kidney, prostate, lymph nodes, and sub-cortical brain structures, in CT, MRI, X-Ray and Ultrasound.

  17. MOST: Modeling of SpaceWire & SpaceFibre Traffic- Applications and Operations: On-Board Segment

    Science.gov (United States)

    Dellandrea, Brice; Gouin, Baptiste; Parkes, Steve; Jameux, David

    2014-08-01

    MOST(Modeling of SpaceWire Traffic) is a representative and powerful SpaceWire traffic simulator designed to support conception, development and validation of SpaceWire networks. MOST is developed by Thales Alenia Space France (TAS-F) for the European Space Agency (ESA) and for the benefits of the SpaceWire communityThis tool was already presented in DASIA 2011 [6] and DASIA 2012 [7] as Thales Alenia Space was finishing its first step of development. Since then, the software has reached a TRL mature enough to start distributing MOST v2.2r2 to the SpaceWire community under ESA license. This released version will be presented in this paperMoreover, TAS-F is currently developing a major extension of the MOST library targeting the inclusion of S paceFibre [5] components under an University of Du ndee sub-contract. These new features will be also presented in this document.

  18. Concurrent Chemoradiotherapy Followed by Consolidation Chemotherapy With Bi-Weekly Docetaxel and Carboplatin for Stage III Unresectable, Non-Small-Cell Lung Cancer: Clinical Application of a Protocol Used in a Previous Phase II Study

    International Nuclear Information System (INIS)

    Saitoh, Jun-Ichi; Saito, Yoshihiro; Kazumoto, Tomoko; Kudo, Shigehiro; Yoshida, Daisaku; Ichikawa, Akihiro; Sakai, Hiroshi; Kurimoto, Futoshi; Kato, Shingo; Shibuya, Kei

    2012-01-01

    Purpose: To assess the clinical applicability of a protocol evaluated in a previously reported phase II study of concurrent chemoradiotherapy followed by consolidation chemotherapy with bi-weekly docetaxel and carboplatin in patients with stage III, unresectable, non-small-cell lung cancer (NSCLC). Methods and Materials: Between January 2000 and March 2006, 116 previously untreated patients with histologically proven, stage III NSCLC were treated with concurrent chemoradiotherapy. Radiation therapy was administered in 2-Gy daily fractions to a total dose of 60 Gy in combination with docetaxel, 30 mg/m 2 , and carboplatin at an area under the curve value of 3 every 2 weeks during and after radiation therapy. Results: The median survival time for the entire group was 25.5 months. The actuarial 2-year and 5-year overall survival rates were 53% and 31%, respectively. The 3-year cause-specific survival rate was 60% in patients with stage IIIA disease, whereas it was 35% in patients with stage IIIB disease (p = 0.007). The actuarial 2-year and 5-year local control rates were 62% and 55%, respectively. Acute hematologic toxicities of Grade ≥3 severity were observed in 20.7% of patients, while radiation pneumonitis and esophagitis of Grade ≥3 severity were observed in 2.6% and 1.7% of patients, respectively. Conclusions: The feasibility of the protocol used in the previous phase II study was reconfirmed in this series, and excellent treatment results were achieved.

  19. Concurrent Chemoradiotherapy Followed by Consolidation Chemotherapy With Bi-Weekly Docetaxel and Carboplatin for Stage III Unresectable, Non-Small-Cell Lung Cancer: Clinical Application of a Protocol Used in a Previous Phase II Study

    Energy Technology Data Exchange (ETDEWEB)

    Saitoh, Jun-Ichi, E-mail: junsaito@sannet.ne.jp [Division of Radiation Oncology, Saitama Cancer Center, Saitama (Japan); Saito, Yoshihiro; Kazumoto, Tomoko; Kudo, Shigehiro; Yoshida, Daisaku; Ichikawa, Akihiro [Division of Radiation Oncology, Saitama Cancer Center, Saitama (Japan); Sakai, Hiroshi; Kurimoto, Futoshi [Division of Respiratory Disease, Saitama Cancer Center, Saitama (Japan); Kato, Shingo [Research Center Hospital for Charged Particle Therapy, National Institute of Radiological Sciences, Chiba (Japan); Shibuya, Kei [Department of Radiation Oncology, Gunma University Graduate School of Medicine, Gunma (Japan)

    2012-04-01

    Purpose: To assess the clinical applicability of a protocol evaluated in a previously reported phase II study of concurrent chemoradiotherapy followed by consolidation chemotherapy with bi-weekly docetaxel and carboplatin in patients with stage III, unresectable, non-small-cell lung cancer (NSCLC). Methods and Materials: Between January 2000 and March 2006, 116 previously untreated patients with histologically proven, stage III NSCLC were treated with concurrent chemoradiotherapy. Radiation therapy was administered in 2-Gy daily fractions to a total dose of 60 Gy in combination with docetaxel, 30 mg/m{sup 2}, and carboplatin at an area under the curve value of 3 every 2 weeks during and after radiation therapy. Results: The median survival time for the entire group was 25.5 months. The actuarial 2-year and 5-year overall survival rates were 53% and 31%, respectively. The 3-year cause-specific survival rate was 60% in patients with stage IIIA disease, whereas it was 35% in patients with stage IIIB disease (p = 0.007). The actuarial 2-year and 5-year local control rates were 62% and 55%, respectively. Acute hematologic toxicities of Grade {>=}3 severity were observed in 20.7% of patients, while radiation pneumonitis and esophagitis of Grade {>=}3 severity were observed in 2.6% and 1.7% of patients, respectively. Conclusions: The feasibility of the protocol used in the previous phase II study was reconfirmed in this series, and excellent treatment results were achieved.

  20. Optimizing Societal Benefit using a Systems Engineering Approach for Implementation of the GEOSS Space Segment

    Science.gov (United States)

    Killough, Brian D., Jr.; Sandford, Stephen P.; Cecil, L DeWayne; Stover, Shelley; Keith, Kim

    2008-01-01

    The Group on Earth Observations (GEO) is driving a paradigm shift in the Earth Observation community, refocusing Earth observing systems on GEO Societal Benefit Areas (SBA). Over the short history of space-based Earth observing systems most decisions have been made based on improving our scientific understanding of the Earth with the implicit assumption that this would serve society well in the long run. The space agencies responsible for developing the satellites used for global Earth observations are typically science driven. The innovation of GEO is the call for investments by space agencies to be driven by global societal needs. This paper presents the preliminary findings of an analysis focused on the observational requirements of the GEO Energy SBA. The analysis was performed by the Committee on Earth Observation Satellites (CEOS) Systems Engineering Office (SEO) which is responsible for facilitating the development of implementation plans that have the maximum potential for success while optimizing the benefit to society. The analysis utilizes a new taxonomy for organizing requirements, assesses the current gaps in spacebased measurements and missions, assesses the impact of the current and planned space-based missions, and presents a set of recommendations.

  1. A Novel Axial Foldable Mechanism for a Segmented Primary Mirror of Space Telescope

    Directory of Open Access Journals (Sweden)

    Dignesh Thesiya

    2015-09-01

    Full Text Available Future space missions will have larger telescopes in order to look deeper into space while improvising on spatial resolution. The primary mirrors for these telescopes will be so large that using a monolithic mirror will be nearly impossible because of the difficulties associated with its fabrication, transportation, and installation on a launch vehicle. The feasibility of launching these huge mirrors is limited because of their small launch fairing diameter. The aerodynamic shape of the fairing requires a small diameter, but the height of the launch vehicle, which is available for designers to utilize, is larger than the fairing diameter. This paper presents the development of an axial deployment mechanism based on the screw jack principle. The mechanism was designed and developed, and a prototype was constructed in order to demonstrate a lab model.

  2. Langmuir Probes for Obstanovka Experiment Aboard the Russian Segment of the International Space Station

    Science.gov (United States)

    2010-08-04

    charged due to the operation of so many instruments, solar batteries, life supporting devices, etc. The present grant is for the elaboration and tests of...sensors (in RKK “ Energia ” – Moscow)  Updating of the technological instruments - a new power supply block (PSB) was elaborated, which made it possible to...depending on space weather, Year of Astronomy: Solar and Solar - Terrestrial Physics 2009, Proceedings of the All-Russian Yearly Conference on Solar

  3. a Prealiminary Study of Ship Detection from Uav Images Based on Color Space Conversion and Image Segmentation

    Science.gov (United States)

    Klimkowska, A. M.; Lee, I.

    2017-08-01

    Ship detection is an inherent process supporting tasks such as fishery management, ship search, marine traffic monitoring and control, and helps in the prevention of illegal activities. So far, sea and shore monitoring has been carried out by ship patrols and aircrafts along with sea vessel detection from data from space-borne platforms. Recently an increase interest in applying images delivered by UAV for marine application due to their advantages such as high spatial resolution, independence on time acquisition can be noticed. While investigating state of the art methods used for ship detection from different platforms using optical images, we found a significant problem with occurrence of a ship wake. This phenomena may prohibit correct detection of ship location and results in overestimating the ship size as the ship and its wake are often considered as being part of the same object in image or wakes are distinguished as a separate ship due to their possible similar brightness compared with sea vessel. In order to reduce the impact of ship wakes we investigated the behavior of images in different color spaces to provide data with little or almost no trace of ship wake. We took into consideration following color spaces: HSV, YCbCr, NTSC, XYZ and L*a*b and investigated each channel from new images. Finally we decided to use 2nd channel of L*a*b space where the ship wakes occurrence were significantly reduced. Object of interest were detected through the use of image segmentation. Applied method uses edge detection based on the gradient magnitude calculation. Afterwards several characteristics such as centroids, major and minor axis, size and orientation were calculated for later use to remove false positives and thus improve accuracy of the proposed method.

  4. A PREALIMINARY STUDY OF SHIP DETECTION FROM UAV IMAGES BASED ON COLOR SPACE CONVERSION AND IMAGE SEGMENTATION

    Directory of Open Access Journals (Sweden)

    A. M. Klimkowska

    2017-08-01

    Full Text Available Ship detection is an inherent process supporting tasks such as fishery management, ship search, marine traffic monitoring and control, and helps in the prevention of illegal activities. So far, sea and shore monitoring has been carried out by ship patrols and aircrafts along with sea vessel detection from data from space-borne platforms. Recently an increase interest in applying images delivered by UAV for marine application due to their advantages such as high spatial resolution, independence on time acquisition can be noticed. While investigating state of the art methods used for ship detection from different platforms using optical images, we found a significant problem with occurrence of a ship wake. This phenomena may prohibit correct detection of ship location and results in overestimating the ship size as the ship and its wake are often considered as being part of the same object in image or wakes are distinguished as a separate ship due to their possible similar brightness compared with sea vessel. In order to reduce the impact of ship wakes we investigated the behavior of images in different color spaces to provide data with little or almost no trace of ship wake. We took into consideration following color spaces: HSV, YCbCr, NTSC, XYZ and L*a*b and investigated each channel from new images. Finally we decided to use 2nd channel of L*a*b space where the ship wakes occurrence were significantly reduced. Object of interest were detected through the use of image segmentation. Applied method uses edge detection based on the gradient magnitude calculation. Afterwards several characteristics such as centroids, major and minor axis, size and orientation were calculated for later use to remove false positives and thus improve accuracy of the proposed method.

  5. Calocube—A highly segmented calorimeter for a space based experiment

    International Nuclear Information System (INIS)

    D'Alessandro, R.; Adriani, O.; Agnesi, A.; Albergo, S.; Auditore, L.; Basti, A.; Berti, E.; Bigongiari, G.; Bonechi, L.; Bonechi, S.; Bongi, M.; Bonvicini, V.

    2016-01-01

    Future research in High Energy Cosmic Ray Physics concerns fundamental questions on their origin, acceleration mechanism, and composition. Unambiguous measurements of the energy spectra and of the composition of cosmic rays at the “knee” region could provide some of the answers to the above questions. Only ground based observations, which rely on sophisticated models describing high energy interactions in the earth's atmosphere, have been possible so far due to the extremely low particle rates at these energies. A calorimeter based space experiment can provide not only flux measurements but also energy spectra and particle identification, especially when coupled to a dE/dx measuring detector, and thus overcome some of the limitations plaguing ground based experiments. For this to be possible very large acceptances are needed if enough statistic is to be collected in a reasonable time. This contrasts with the lightness and compactness requirements for space based experiments. A novel idea in calorimetry is discussed here which addresses these issues while limiting the mass and volume of the detector. In fact a small prototype is currently being built and tested with ions. In this paper the results obtained will be presented in light of the simulations performed.

  6. Large aperture telescope technology: a design for an active lightweight multi-segmented fold-out space mirror

    Science.gov (United States)

    Thompson, S. J.; Doel, A. P.; Whalley, M.; Edeson, R.; Edeson, R.; Tosh, I.; Poyntz-Wright, O.; Atad-Ettedgui, E.; Montgomery, D.; Nawasra, J.

    2017-11-01

    Large aperture telescope technology (LATT) is a design study for a differential lidar (DIAL) system; the main investigation being into suitable methods, technologies and materials for a 4-metre diameter active mirror that can be stowed to fit into a typical launch vehicle (e.g. ROKOT launcher with 2.1-metre diameter cargo) and can self-deploy - in terms of both leaving the space vehicle and that the mirrors unfold and self-align to the correct optical form within the tolerances specified. The primary mirror requirements are: main wavelength of 935.5 nm, RMS corrected wavefront error of λ/6, optical surface roughness better than 5 nm, areal density of less than 16 kg/m2 and 1-2 mirror shape corrections per orbit. The primary mirror consists of 7 segments - a central hexagonal mirror and 6 square mirror petals which unfold to form the 4-meter diameter aperture. The focus of the UK LATT consortium for this European Space Agency (ESA) funded project is on using lightweighted aluminium or carbon-fibre-composite materials for the mirror substrate in preference to more traditional materials such as glass and ceramics; these materials have a high strength and stiffness to weight ratio, significantly reducing risk of damage due to launch forces and subsequent deployment in orbit. We present an overview of the design, which includes suitable actuators for wavefront correction, petal deployment mechanisms and lightweight mirror technologies. Preliminary testing results from manufactured lightweight mirror samples will also be summarised.

  7. Audio segmentation using Flattened Local Trimmed Range for ecological acoustic space analysis

    Directory of Open Access Journals (Sweden)

    Giovany Vega

    2016-06-01

    Full Text Available The acoustic space in a given environment is filled with footprints arising from three processes: biophony, geophony and anthrophony. Bioacoustic research using passive acoustic sensors can result in thousands of recordings. An important component of processing these recordings is to automate signal detection. In this paper, we describe a new spectrogram-based approach for extracting individual audio events. Spectrogram-based audio event detection (AED relies on separating the spectrogram into background (i.e., noise and foreground (i.e., signal classes using a threshold such as a global threshold, a per-band threshold, or one given by a classifier. These methods are either too sensitive to noise, designed for an individual species, or require prior training data. Our goal is to develop an algorithm that is not sensitive to noise, does not need any prior training data and works with any type of audio event. To do this, we propose: (1 a spectrogram filtering method, the Flattened Local Trimmed Range (FLTR method, which models the spectrogram as a mixture of stationary and non-stationary energy processes and mitigates the effect of the stationary processes, and (2 an unsupervised algorithm that uses the filter to detect audio events. We measured the performance of the algorithm using a set of six thoroughly validated audio recordings and obtained a sensitivity of 94% and a positive predictive value of 89%. These sensitivity and positive predictive values are very high, given that the validated recordings are diverse and obtained from field conditions. The algorithm was then used to extract audio events in three datasets. Features of these audio events were plotted and showed the unique aspects of the three acoustic communities.

  8. Estimulação Magnética Transcraniana na depressão: resultados obtidos com duas aplicações semanais Transcranial Magnetic Stimulation in depression: results of bi-weekly treatment

    Directory of Open Access Journals (Sweden)

    Raphael Boechat-Barros

    2004-06-01

    Full Text Available OBJETIVO: A Estimulação Magnética Transcraniana (EMT tem se mostrado útil como forma terapêutica para a depressão. Este artigo avalia os resultados da aplicação da EMT de baixa freqüência, duas vezes por semana, durante quatro semanas, em 10 pacientes com depressão, não responsivos ou intolerantes à utilização de antidepressivos. MÉTODOS: Trata-se de um estudo descritivo, ou não controlado, do tipo série de casos. Para diagnosticar a depressão, foram utilizados os critérios do DSM-IV. Com o intuito de avaliar uma possível melhora, utilizamos a escala de Hamilton-17 itens em três momentos: no início, meio e final do tratamento. Para análise estatística dos resultados, utilizamos o teste x², de Friedman. RESULTADOS: Foi observada melhora > 50% na escala em cinco pacientes e > 75% em três destes ao longo de todo o tratamento. CONCLUSÕES: O emprego da EMT de baixa freqüência, aplicada duas vezes por semana, pode ser seguro, prático e eficaz no tratamento da depressão, como um coadjuvante ao antidepressivo. Porém, não podemos afirmar se o efeito clínico apresentado se deve a uma potencialização dos antidepressivos ou a um efeito direto da EMT, já que esta não foi testada isoladamente.OBJECTIVE: Transcranial Magnetic Stimulation (TMS has been shown to be a useful therapy for depression. This paper evaluates the results of bi-weekly low-frequency TMS of 4 weeks duration, in 10 patients with depression who do not respond or are intolerant to antidepressive medication. METHODS: This is a case series study. DMS-IV criteria were used to diagnose depression. In order to disclose possible improvements in depressive symptoms, the 17 items Hamilton scale was used at three different moments: at the beginning, middle and end of the treatment period. Results were analysed using Friedman's x² test. RESULTS: Hamilton's scale score improvement was > 50% in five patients and > 75% in 3 of these. CONCLUSIONS: TMS may be

  9. The Proposal to “Snapshot” Raim Method for Gnss Vessel Receivers Working in Poor Space Segment Geometry

    Directory of Open Access Journals (Sweden)

    Nowak Aleksander

    2015-12-01

    Full Text Available Nowadays, we can observe an increase in research on the use of small unmanned autonomous vessel (SUAV to patrol and guiding critical areas including harbours. The proposal to “snapshot” RAIM (Receiver Autonomous Integrity Monitoring method for GNSS receivers mounted on SUAV operating in poor space segment geometry is presented in the paper. Existing “snapshot” RAIM methods and algorithms which are used in practical applications have been developed for airborne receivers, thus two main assumptions have been made. The first one is that the geometry of visible satellites is strong. It means that the exclusion of any satellite from the positioning solution don’t cause significant deterioration of Dilution of Precision (DOP coefficients. The second one is that only one outlier could appear in pseudorange measurements. In case of SUAV operating in harbour these two assumptions cannot be accepted. Because of their small dimensions, GNSS antenna is only a few decimetres above sea level and regular ships, buildings and harbour facilities block and reflect satellite signals. Thus, different approach to “snapshot” RAIM is necessary. The proposal to method based on analyses of allowable maximal separation of positioning sub-solutions with using some information from EGNOS messages is described in the paper. Theoretical assumptions and results of numerical experiments are presented.

  10. Automatic Segmentation of Impaired Joint Space Area for Osteoarthritis Knee on X-ray Image using Gabor Filter Based Morphology Process

    Directory of Open Access Journals (Sweden)

    Lilik Anifah

    2011-08-01

    Full Text Available Segmentation is the first step in osteoarthritis classification. Manual selection is time-consuming, tedious, and expensive. The system is designed to help medical doctors to determine the region of interest of visual characteristics found in knee Osteoarthritis (OA. We propose a fully automatic method without human interaction to segment Junction Space Area (JSA for OA classification on impaired x-ray image. In this proposed system, right and left knee detection is performed using using Contrast-Limited Adaptive Histogram Equalization (CLAHE and template macthing. The row sum graph and moment methods are used to segment the junction space area of knee. Overall we evaluated 98 kneess of patients. Experimental results demonstrate an accuracy of the system of up to 100% for detection of both left and right knee and for junction space detection an accuracy 84.38% for the right knee and 85.42% for the left. The second experiment using gabor filter with parameter α=8, θ=0, Ψ=[0 Π/2], γ=0,8 and N=8 and row sum graph give an accuracy 92.63% for the right knee and 87.37% for the left. And the average time needs to process is 65.79 second. For obvious reasons we chose the results of the fourth to segment junction area in both right and the left knee.

  11. Classification and segmentation of orbital space based objects against terrestrial distractors for the purpose of finding holes in shape from motion 3D reconstruction

    Science.gov (United States)

    Mundhenk, T. Nathan; Flores, Arturo; Hoffman, Heiko

    2013-12-01

    3D reconstruction of objects via Shape from Motion (SFM) has made great strides recently. Utilizing images from a variety of poses, objects can be reconstructed in 3D without knowing a priori the camera pose. These feature points can then be bundled together to create large scale scene reconstructions automatically. A shortcoming of current methods of SFM reconstruction is in dealing with specular or flat low feature surfaces. The inability of SFM to handle these places creates holes in a 3D reconstruction. This can cause problems when the 3D reconstruction is used for proximity detection and collision avoidance by a space vehicle working around another space vehicle. As such, we would like the automatic ability to recognize when a hole in a 3D reconstruction is in fact not a hole, but is a place where reconstruction has failed. Once we know about such a location, methods can be used to try to either more vigorously fill in that region or to instruct a space vehicle to proceed with more caution around that area. Detecting such areas in earth orbiting objects is non-trivial since we need to parse out complex vehicle features from complex earth features, particularly when the observing vehicle is overhead the target vehicle. To do this, we have created a Space Object Classifier and Segmenter (SOCS) hole finder. The general principle we use is to classify image features into three categories (earth, man-made, space). Classified regions are then clustered into probabilistic regions which can then be segmented out. Our categorization method uses an augmentation of a state of the art bag of visual words method for object categorization. This method works by first extracting PHOW (dense SIFT like) features which are computed over an image and then quantized via KD Tree. The quantization results are then binned into histograms and results classified by the PEGASOS support vector machine solver. This gives a probability that a patch in the image corresponds to one of three

  12. Segmentation of burn images using the L*u*v* space and classification of their depths by color and texture imformation

    Science.gov (United States)

    Acha Pinero, Begona; Serrano, Carmen; Acha, Jose I.

    2002-05-01

    In this paper a burn color image segmentation and classification algorithm is proposed. The aim of the algorithm is to separate the burn wounds from healthy skin, and the different types of burns (burn depths) among themselves. We use digital color photographs. The system is based on the color and texture information, as these are the characteristics observed by physicians in order to give a diagnosis. We use a perceptually uniform color space (L*u*v*), since Euclidean distances calculated in this space correspond to perceptually color differences. After the burn is segmented, some color and texture descriptors features are calculated and they are the inputs to a Fuzzy-ARTMAP neural network. The neural network classifies them into three types of burns: superficial dermal, depth dermal and full thickness. We get an average classification success rate of 88.89%.

  13. 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.

  14. 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)

  15. Four-chamber heart modeling and automatic segmentation for 3-D cardiac CT volumes using marginal space learning and steerable features.

    Science.gov (United States)

    Zheng, Yefeng; Barbu, Adrian; Georgescu, Bogdan; Scheuering, Michael; Comaniciu, Dorin

    2008-11-01

    We propose an automatic four-chamber heart segmentation system for the quantitative functional analysis of the heart from cardiac computed tomography (CT) volumes. Two topics are discussed: heart modeling and automatic model fitting to an unseen volume. Heart modeling is a nontrivial task since the heart is a complex nonrigid organ. The model must be anatomically accurate, allow manual editing, and provide sufficient information to guide automatic detection and segmentation. Unlike previous work, we explicitly represent important landmarks (such as the valves and the ventricular septum cusps) among the control points of the model. The control points can be detected reliably to guide the automatic model fitting process. Using this model, we develop an efficient and robust approach for automatic heart chamber segmentation in 3-D CT volumes. We formulate the segmentation as a two-step learning problem: anatomical structure localization and boundary delineation. In both steps, we exploit the recent advances in learning discriminative models. A novel algorithm, marginal space learning (MSL), is introduced to solve the 9-D similarity transformation search problem for localizing the heart chambers. After determining the pose of the heart chambers, we estimate the 3-D shape through learning-based boundary delineation. The proposed method has been extensively tested on the largest dataset (with 323 volumes from 137 patients) ever reported in the literature. To the best of our knowledge, our system is the fastest with a speed of 4.0 s per volume (on a dual-core 3.2-GHz processor) for the automatic segmentation of all four chambers.

  16. An Efficient SAR Image Segmentation Framework Using Transformed Nonlocal Mean and Multi-Objective Clustering in Kernel Space

    Directory of Open Access Journals (Sweden)

    Dongdong Yang

    2015-02-01

    Full Text Available Synthetic aperture radar (SAR image segmentation usually involves two crucial issues: suitable speckle noise removing technique and effective image segmentation methodology. Here, an efficient SAR image segmentation method considering both of the two aspects is presented. As for the first issue, the famous nonlocal mean (NLM filter is introduced in this study to suppress the multiplicative speckle noise in SAR image. Furthermore, to achieve a higher denoising accuracy, the local neighboring pixels in the searching window are projected into a lower dimensional subspace by principal component analysis (PCA. Thus, the nonlocal mean filter is implemented in the subspace. Afterwards, a multi-objective clustering algorithm is proposed using the principals of artificial immune system (AIS and kernel-induced distance measures. The multi-objective clustering has been shown to discover the data distribution with different characteristics and the kernel methods can improve its robustness to noise and outliers. Experiments demonstrate that the proposed method is able to partition the SAR image robustly and accurately than the conventional approaches.

  17. 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.

  18. Comparison of manual and automatic segmentation methods for brain structures in the presence of space-occupying lesions: a multi-expert study

    Science.gov (United States)

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

    2011-07-01

    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.

  19. Comparison of manual and automatic segmentation methods for brain structures in the presence of space-occupying lesions: a multi-expert study

    Energy Technology Data Exchange (ETDEWEB)

    Deeley, M A; Cmelak, A J; Malcolm, A W; Moretti, L; Jaboin, J; Niermann, K; Yang, Eddy S; Yu, David S; Ding, G X [Department of Radiation Oncology, Vanderbilt University, Nashville, TN (United States); Chen, A; Datteri, R; Noble, J H; Dawant, B M [Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN (United States); Donnelly, E F [Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN (United States); Yei, F; Koyama, T, E-mail: matthew.deeley@uvm.edu [Department of Biostatistics, Vanderbilt University, Nashville, TN (United States)

    2011-07-21

    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.

  20. 3D multi-slab diffusion-weighted readout-segmented EPI with real-time cardiac-reordered K-space acquisition.

    Science.gov (United States)

    Frost, Robert; Miller, Karla L; Tijssen, Rob H N; Porter, David A; Jezzard, Peter

    2014-12-01

    The aim of this study was to develop, implement, and demonstrate a three-dimensional (3D) extension of the readout-segmented echo-planar imaging (rs-EPI) sequence for diffusion imaging. Potential k-space acquisition schemes were assessed by simulating their associated spatial point spread functions. Motion-induced phase artifacts were also simulated to test navigator corrections and a real-time reordering of the k-space acquisition relative to the cardiac cycle. The cardiac reordering strategy preferentially chooses readout segments closer to the center of 3D k-space during diastole. Motion-induced phase artifacts were quantified by calculating the voxel-wise temporal variation in a set of repeated diffusion-weighted acquisitions. Based on the results of these simulations, a 2D navigated multi-slab rs-EPI sequence with real-time cardiac reordering was implemented. The multi-slab implementation enables signal-to-noise ratio-optimal repetition times of 1-2 s. Cardiac reordering was validated in simulations and in vivo using the multi-slab rs-EPI sequence. In comparisons with standard k-space acquisitions, cardiac reordering was shown to reduce the variability due to motion-induced phase artifacts by 30-50%. High-resolution diffusion tensor imaging data acquired with the cardiac-reordered multi-slab rs-EPI sequence are presented. A 3D multi-slab rs-EPI sequence with cardiac reordering has been demonstrated in vivo and is shown to provide high-quality 3D diffusion-weighted data sets. © 2013 Wiley Periodicals, Inc.

  1. Design and fabrication of a large vertical travel silicon inchworm microactuator for advanced segmented silicon space telescope (ASSIST)

    Science.gov (United States)

    Yang, E.; Dekany, R.; Padin, S.

    2003-01-01

    The goal of this research is to develop inchworm motor systems capable of simultaneously providing nanometer resolution, high stiffness, large output force, long travel range, and compactness for ultraprecision positioning applications in space.

  2. Seismicity of Romania: fractal properties of earthquake space, time and energy distributions and their correlation with segmentation of subducted lithosphere and Vrancea seismic source

    International Nuclear Information System (INIS)

    Popescu, E.; Ardeleanu, L.; Bazacliu, O.; Popa, M.; Radulian, M.; Rizescu, M.

    2002-01-01

    For any strategy of seismic hazard assessment, it is important to set a realistic seismic input such as: delimitation of seismogenic zones, geometry of seismic sources, seismicity regime, focal mechanism and stress field. The aim of the present project is a systematic investigation focused on the problem of Vrancea seismic regime at different time, space and energy scales which can offer a crucial information on the seismogenic process of this peculiar seismic area. The departures from linearity of the time, space and energy distributions are associated with inhomogeneities in the subducting slab, rheology, tectonic stress distribution and focal mechanism. The significant variations are correlated with the existence of active and inactive segments along the seismogenic zone, the deviation from linearity of the frequency-magnitude distribution is associated with the existence of different earthquake generation models and the nonlinearities showed in the time series are related with the occurrence of the major earthquakes. Another important purpose of the project is to analyze the main crustal seismic sequences generated on the Romanian territory in the following regions: Ramnicu Sarat, Fagaras-Campulung, Banat. Time, space and energy distributions together with the source parameters and scaling relations are investigated. The analysis of the seismicity and clustering properties of the earthquakes generated in both Vrancea intermediate-depth region and Romanian crustal seismogenic zones, achieved within this project, constitutes the starting point for the study of seismic zoning, seismic hazard and earthquake prediction. The data set consists of Vrancea subcrustal earthquake catalogue (since 1974 and continuously updated) and catalogues with events located in the other crustal seimogenic zones of Romania. To build up these data sets, high-quality information made available through multiple international cooperation programs is considered. The results obtained up to

  3. The 2014 Pisagua-Iquique (Chile) earthquake sequence : geodetic constraints on space-time slip behaviour of a megathrust segment

    Science.gov (United States)

    Grandin, R.; Ruiz, S.; Metois, M.; Bejar, M.; Vigny, C.; Boudin, F.; Allgeyer, S.; Motagh, M.; Fuenzalida, A.; Leyton, F.; Ruiz, J. A.; Rivera, E.; Vallee, M.; Jara, J.; Cotte, N.; de Chabalier, J. B.; Lacassin, R.; Carrizo, D.; Socquet, A.; Armijo, R.; Ruegg, J. C.

    2014-12-01

    providing a first-order interpretation of the heterogeneity of frictional properties of the megathrust segment, alongside with the initial stress conditions that prevailed before the main rupture. The existence of major structural / geometric complexities within the megathrust system may also be inferred.

  4. Ensemble segmentation using efficient integer linear programming.

    Science.gov (United States)

    Alush, Amir; Goldberger, Jacob

    2012-10-01

    We present a method for combining several segmentations of an image into a single one that in some sense is the average segmentation in order to achieve a more reliable and accurate segmentation result. The goal is to find a point in the "space of segmentations" which is close to all the individual segmentations. We present an algorithm for segmentation averaging. The image is first oversegmented into superpixels. Next, each segmentation is projected onto the superpixel map. An instance of the EM algorithm combined with integer linear programming is applied on the set of binary merging decisions of neighboring superpixels to obtain the average segmentation. Apart from segmentation averaging, the algorithm also reports the reliability of each segmentation. The performance of the proposed algorithm is demonstrated on manually annotated images from the Berkeley segmentation data set and on the results of automatic segmentation algorithms.

  5. Exo-planet Direct Imaging with On-Axis and/or Segmented Apertures in Space: Adaptive Compensation of Aperture Discontinuities

    Science.gov (United States)

    Soummer, Remi

    Capitalizing on a recent breakthrough in wavefront control theory for obscured apertures made by our group, we propose to demonstrate a method to achieve high contrast exoplanet imaging with on-axis obscured apertures. Our new algorithm, which we named Adaptive Compensation of Aperture Discontinuities (ACAD), provides the ability to compensate for aperture discontinuities (segment gaps and/or secondary mirror supports) by controlling deformable mirrors in a nonlinear wavefront control regime not utilized before but conceptually similar to the beam reshaping used in PIAA coronagraphy. We propose here an in-air demonstration at 1E- 7 contrast, enabled by adding a second deformable mirror to our current test-bed. This expansion of the scope of our current efforts in exoplanet imaging technologies will enabling us to demonstrate an integrated solution for wavefront control and starlight suppression on complex aperture geometries. It is directly applicable at scales from moderate-cost exoplanet probe missions to the 2.4 m AFTA telescopes to future flagship UVOIR observatories with apertures potentially 16-20 m. Searching for nearby habitable worlds with direct imaging is one of the top scientific priorities established by the Astro2010 Decadal Survey. Achieving this ambitious goal will require 1e-10 contrast on a telescope large enough to provide angular resolution and sensitivity to planets around a significant sample of nearby stars. Such a mission must of course also be realized at an achievable cost. Lightweight segmented mirror technology allows larger diameter optics to fit in any given launch vehicle as compared to monolithic mirrors, and lowers total life-cycle costs from construction through integration & test, making it a compelling option for future large space telescopes. At smaller scales, on-axis designs with secondary obscurations and supports are less challenging to fabricate and thus more affordable than the off-axis unobscured primary mirror designs

  6. AGOR 28: SIO Shipyard Representative Bi-Weekly Progress Report

    Science.gov (United States)

    2016-02-15

    Prepared by: Paul D. Bueren Scripps Institution of Oceanography (SIO) 297 Rosecrans St. San Diego, CA 98106 Date: 15 February, 2016 Program Officer ...Robert (Tim) Schnoor Office of Naval Research 875 Randolph St ONR 321 Arlington, VA 22203-1995 Distribution Statement A: Approved for public...the DC Links cubicle . These meters are redundant as the voltage reading is available on the motor controller HMI’s. • Crew Fam – The crew fam

  7. AGOR 28 SIO Shipyard Representative Bi-Weekly Progress Report

    Science.gov (United States)

    2015-11-06

    or MMR bilge tops, if any. • Anchor Windlass – The test of Armstrong’s port side anchor windlass failed while the third shot was being paid out...Armstrong port side did not appear to work. Chain jumped the wildcat three different times while lowering the port anchor under power. Anchor may...have been on bottom during major “slip”….even if it was chain should not jump wildcat. • Single engine running on Ride during Boat Davit weight testing

  8. AGOR 28: SIO Shipyard Representative Bi-Weekly Progress Report

    Science.gov (United States)

    2015-12-12

    Ride Anti-Fouling Paint – The anti-fouling paint has failed due to an application error. The yard will correct this issue during a planned docking...prior to Builder’s Trials. With the dry docking cancelled the paint repairs will most likely be during Phase III if it is occurs at DCI. 5...exhaust hood wash-down system cabinet has been installed, plumbed and connected to electrical service. Yard will next install the wash-down spray bar and

  9. AGOR 28: SIO Shipyard Representative Bi-Weekly Progress Report

    Science.gov (United States)

    2015-10-23

    procedure is complete, except for the anti-two block device requiring adjustment, the lack of a cleat for attaching the sea painter to the ship, and the...be worth it. No connection point provided for Rescue Boat Sea Painter, no bitts or cleats provided mid-ships. Armstrong mounted small cleat to

  10. AGOR 28: SIO Shipyard Representative Bi-Weekly Progress Report

    Science.gov (United States)

    2016-06-18

    an open Trial Card. I believe Kongsberg is scheduled to retune the system. • Blue Drive Shore-based Spares – ALM, AIM and Propulsion Motor drives...failed due to shorted temperature sensor at the Tunnel Thruster motor . A small rectifier was found to have failed in the terminal block found in the...J-1 at sustained speed. See Airborne Noise Survey Report (DI-032-006) for more information (Delete after RFW approved) 1137 HVAC - There were no

  11. 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...

  12. 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.

  13. 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.

  14. 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.

  15. Mixed segmentation

    DEFF Research Database (Denmark)

    Hansen, Allan Grutt; Bonde, Anders; Aagaard, Morten

    This book is about using recent developments in the fields of data analytics and data visualization to frame new ways of identifying target groups in media communication. Based on a mixed-methods approach, the authors combine psychophysiological monitoring (galvanic skin response) with textual...... content analysis and audience segmentation in a single-source perspective. The aim is to explain and understand target groups in relation to, on the one hand, emotional response to commercials or other forms of audio-visual communication and, on the other hand, living preferences and personality traits...

  16. 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.

  17. Image Segmentation Algorithms Overview

    OpenAIRE

    Yuheng, Song; Hao, Yan

    2017-01-01

    The technology of image segmentation is widely used in medical image processing, face recognition pedestrian detection, etc. The current image segmentation techniques include region-based segmentation, edge detection segmentation, segmentation based on clustering, segmentation based on weakly-supervised learning in CNN, etc. This paper analyzes and summarizes these algorithms of image segmentation, and compares the advantages and disadvantages of different algorithms. Finally, we make a predi...

  18. Constraint-based Word Segmentation for Chinese

    DEFF Research Database (Denmark)

    Christiansen, Henning; Bo, Li

    2014-01-01

    Written Chinese text has no separators between words in the same way as European languages use space characters, and this creates the Chinese Word Segmentation Problem, CWSP: given a text in Chinese, divide it in a correct way into segments corresponding to words. Good solutions are in demand...

  19. Efficient threshold for volumetric segmentation

    Science.gov (United States)

    Burdescu, Dumitru D.; Brezovan, Marius; Stanescu, Liana; Stoica Spahiu, Cosmin; Ebanca, Daniel

    2015-07-01

    Image segmentation plays a crucial role in effective understanding of digital images. However, the research on the existence of general purpose segmentation algorithm that suits for variety of applications is still very much active. Among the many approaches in performing image segmentation, graph based approach is gaining popularity primarily due to its ability in reflecting global image properties. Volumetric image segmentation can simply result an image partition composed by relevant regions, but the most fundamental challenge in segmentation algorithm is to precisely define the volumetric extent of some object, which may be represented by the union of multiple regions. The aim in this paper is to present a new method to detect visual objects from color volumetric images and efficient threshold. We present a unified framework for volumetric image segmentation and contour extraction that uses a virtual tree-hexagonal structure defined on the set of the image voxels. The advantage of using a virtual tree-hexagonal network superposed over the initial image voxels is that it reduces the execution time and the memory space used, without losing the initial resolution of the image.

  20. Pitch Synchronous Segmentation of Speech Signals

    Data.gov (United States)

    National Aeronautics and Space Administration — The Pitch Synchronous Segmentation (PSS) that accelerates speech without changing its fundamental frequency method could be applied and evaluated for use at NASA....

  1. Segmentation and segment connection of obstructed colon

    Science.gov (United States)

    Medved, Mario; Truyen, Roel; Likar, Bostjan; Pernus, Franjo

    2004-05-01

    Segmentation of colon CT images is the main factor that inhibits automation of virtual colonoscopy. There are two main reasons that make efficient colon segmentation difficult. First, besides the colon, the small bowel, lungs, and stomach are also gas-filled organs in the abdomen. Second, peristalsis or residual feces often obstruct the colon, so that it consists of multiple gas-filled segments. In virtual colonoscopy, it is very useful to automatically connect the centerlines of these segments into a single colon centerline. Unfortunately, in some cases this is a difficult task. In this study a novel method for automated colon segmentation and connection of colon segments' centerlines is proposed. The method successfully combines features of segments, such as centerline and thickness, with information on main colon segments. The results on twenty colon cases show that the method performs well in cases of small obstructions of the colon. Larger obstructions are mostly also resolved properly, especially if they do not appear in the sigmoid part of the colon. Obstructions in the sigmoid part of the colon sometimes cause improper classification of the small bowel segments. If a segment is too small, it is classified as the small bowel segment. However, such misclassifications have little impact on colon analysis.

  2. Nonlocal Means Denoising of Self-Gated and k-Space Sorted 4-Dimensional Magnetic Resonance Imaging Using Block-Matching and 3-Dimensional Filtering: Implications for Pancreatic Tumor Registration and Segmentation.

    Science.gov (United States)

    Jin, Jun; McKenzie, Elizabeth; Fan, Zhaoyang; Tuli, Richard; Deng, Zixin; Pang, Jianing; Fraass, Benedick; Li, Debiao; Sandler, Howard; Yang, Guang; Sheng, Ke; Gou, Shuiping; Yang, Wensha

    2016-07-01

    To denoise self-gated k-space sorted 4-dimensional magnetic resonance imaging (SG-KS-4D-MRI) by applying a nonlocal means denoising filter, block-matching and 3-dimensional filtering (BM3D), to test its impact on the accuracy of 4D image deformable registration and automated tumor segmentation for pancreatic cancer patients. Nine patients with pancreatic cancer and abdominal SG-KS-4D-MRI were included in the study. Block-matching and 3D filtering was adapted to search in the axial slices/frames adjacent to the reference image patch in the spatial and temporal domains. The patches with high similarity to the reference patch were used to collectively denoise the 4D-MRI image. The pancreas tumor was manually contoured on the first end-of-exhalation phase for both the raw and the denoised 4D-MRI. B-spline deformable registration was applied to the subsequent phases for contour propagation. The consistency of tumor volume defined by the standard deviation of gross tumor volumes from 10 breathing phases (σ_GTV), tumor motion trajectories in 3 cardinal motion planes, 4D-MRI imaging noise, and image contrast-to-noise ratio were compared between the raw and denoised groups. Block-matching and 3D filtering visually and quantitatively reduced image noise by 52% and improved image contrast-to-noise ratio by 56%, without compromising soft tissue edge definitions. Automatic tumor segmentation is statistically more consistent on the denoised 4D-MRI (σ_GTV = 0.6 cm(3)) than on the raw 4D-MRI (σ_GTV = 0.8 cm(3)). Tumor end-of-exhalation location is also more reproducible on the denoised 4D-MRI than on the raw 4D-MRI in all 3 cardinal motion planes. Block-matching and 3D filtering can significantly reduce random image noise while maintaining structural features in the SG-KS-4D-MRI datasets. In this study of pancreatic tumor segmentation, automatic segmentation of GTV in the registered image sets is shown to be more consistent on the denoised 4D-MRI than on the raw 4D

  3. Space Operations

    Science.gov (United States)

    2013-05-29

    attack Laser attack Jamming Indications and warning Cyber attack Environmental monitoring System status     Re-entry Detect and track Cataloging...vulnerable to interference or attack. Space segments are vulnerable to attacks or interference such as direct-ascent anti- satellite interceptors, laser ...blinding, and dazzling . Additionally, ground-to-satellite link segments are susceptible to jamming and other forms of interference, and ground

  4. Protein-segment universe exhibiting transitions at intermediate segment length in conformational subspaces

    Directory of Open Access Journals (Sweden)

    Hirokawa Takatsugu

    2008-08-01

    Full Text Available Abstract Background Many studies have examined rules governing two aspects of protein structures: short segments and proteins' structural domains. Nevertheless, the organization and nature of the conformational space of segments with intermediate length between short segments and domains remain unclear. Conformational spaces of intermediate length segments probably differ from those of short segments. We investigated the identification and characterization of the boundary(s between peptide-like (short segment and protein-like (long segment distributions. We generated ensembles embedded in globular proteins comprising segments 10–50 residues long. We explored the relationships between the conformational distribution of segments and their lengths, and also protein structural classes using principal component analysis based on the intra-segment Cα-Cα atomic distances. Results Our statistical analyses of segment conformations and length revealed critical dual transitions in their conformational distribution with segments derived from all four structural classes. Dual transitions were identified with the intermediate phase between the short segments and domains. Consequently, protein segment universes were categorized. i Short segments (10–22 residues showed a distribution with a high frequency of secondary structure clusters. ii Medium segments (23���26 residues showed a distribution corresponding to an intermediate state of transitions. iii Long segments (27–50 residues showed a distribution converging on one huge cluster containing compact conformations with a smaller radius of gyration. This distribution reflects the protein structures' organization and protein domains' origin. Three major conformational components (radius of gyration, structural symmetry with respect to the N-terminal and C-terminal halves, and single-turn/two-turn structure well define most of the segment universes. Furthermore, we identified several

  5. 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.

  6. Methodologies to determine forces on bones and muscles of body segments during exercise, employing compact sensors suitable for use in crowded space vehicles

    Science.gov (United States)

    Figueroa, Fernando

    1995-01-01

    Work under this grant was carried out by the author and by a graduate research assistant. An instrumented bicycle ergometer was implemented focusing on the stated objective: to estimate the forces exerted by each muscle of the feet, calf, and thigh of an individual while bicycling. The sensors used were light and compact. These were probes to measure muscle EMG activity, miniature accelerometers, miniature load sensors, and small encoders to measure angular positions of the pedal. A methodology was developed and implemented to completely describe the kinematics of the limbs using data from the sensors. This work has been published as a Master's Thesis by the Graduate student supported by the grant. The instrumented ergometer along with the sensors and instrumentation were tested during a KC-135 Zero-Gravity flight in July, 1994. A complete description of the system and the tests performed have been published as a report submitted to NASA Johnson Space Center. The data collected during the KC-135 flight is currently being processed so that a kinematic description of the bicycling experiment will be soon determined. A methodology to estimate the muscle forces has been formulated based on previous work. The methodology involves the use of optimization concepts so that the individual muscle forces that represent variables in dynamic equations of motion may be estimated. Optimization of a criteria (goal) function such as minimization of energy will be used along with constraint equations defined by rigid body equations of motion. Use of optimization principles is necessary, because the equations of motion alone constitute an indeterminate system of equations with respect to the large amount of muscle forces which constitute the variables in these equations. The number of variables is reduced somewhat by using forces measured by the load cells installed on the pedal. These load cells measure pressure and shear forces on the foot. The author and his collaborators at NASA

  7. 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.

  8. Hierarchical morphological segmentation for image sequence coding.

    Science.gov (United States)

    Salembier, P; Pardas, M

    1994-01-01

    This paper deals with a hierarchical morphological segmentation algorithm for image sequence coding. Mathematical morphology is very attractive for this purpose because it efficiently deals with geometrical features such as size, shape, contrast, or connectivity that can be considered as segmentation-oriented features. The algorithm follows a top-down procedure. It first takes into account the global information and produces a coarse segmentation, that is, with a small number of regions. Then, the segmentation quality is improved by introducing regions corresponding to more local information. The algorithm, considering sequences as being functions on a 3-D space, directly segments 3-D regions. A 3-D approach is used to get a segmentation that is stable in time and to directly solve the region correspondence problem. Each segmentation stage relies on four basic steps: simplification, marker extraction, decision, and quality estimation. The simplification removes information from the sequence to make it easier to segment. Morphological filters based on partial reconstruction are proven to be very efficient for this purpose, especially in the case of sequences. The marker extraction identifies the presence of homogeneous 3-D regions. It is based on constrained flat region labeling and morphological contrast extraction. The goal of the decision is to precisely locate the contours of regions detected by the marker extraction. This decision is performed by a modified watershed algorithm. Finally, the quality estimation concentrates on the coding residue, all the information about the 3-D regions that have not been properly segmented and therefore coded. The procedure allows the introduction of the texture and contour coding schemes within the segmentation algorithm. The coding residue is transmitted to the next segmentation stage to improve the segmentation and coding quality. Finally, segmentation and coding examples are presented to show the validity and interest of

  9. 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

  10. Sipunculans and segmentation.

    Science.gov (United States)

    Wanninger, Andreas; Kristof, Alen; Brinkmann, Nora

    2009-01-01

    Comparative molecular, developmental and morphogenetic analyses show that the three major segmented animal groups-Lophotrochozoa, Ecdysozoa and Vertebrata-use a wide range of ontogenetic pathways to establish metameric body organization. Even in the life history of a single specimen, different 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 nervous system form in anterior-posterior progression. Contrary to traditional belief, loss of segmentation may have occurred more often than commonly assumed, as exemplified in the sipunculans, which show remnants of segmentation in larval stages but are unsegmented as adults. The developmental plasticity and potential evolutionary lability of segmentation nourishes the controversy of a segmented bilaterian ancestor versus multiple independent evolution of segmentation in respective metazoan lineages.

  11. 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

  12. Improving image segmentation by learning region affinities

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-11-03

    We utilize the context information of other regions in hierarchical image segmentation to learn new regions affinities. It is well known that a single choice of quantization of an image space is highly unlikely to be a common optimal quantization level for all categories. Each level of quantization has its own benefits. Therefore, we utilize the hierarchical information among different quantizations as well as spatial proximity of their regions. The proposed affinity learning takes into account higher order relations among image regions, both local and long range relations, making it robust to instabilities and errors of the original, pairwise region affinities. Once the learnt affinities are obtained, we use a standard image segmentation algorithm to get the final segmentation. Moreover, the learnt affinities can be naturally unutilized in interactive segmentation. Experimental results on Berkeley Segmentation Dataset and MSRC Object Recognition Dataset are comparable and in some aspects better than the state-of-art methods.

  13. 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%).

  14. Morphological segmentation for sagittal plane image analysis.

    Science.gov (United States)

    Bezerra, F N; Paula, I C; Medeiros, F S; Ushizima, D M; Cintra, L S

    2010-01-01

    This paper introduces a morphological image segmentation method by applying watershed transform with markers to scale-space smoothed images and furthermore provides images for clinical monitoring and analysis of patients. The database comprises sagittal plane images taken from a digital camera of patients submitted to Global Postural Reeducation (GPR) physiotherapy treatment. Orthopaedic specialists can use these segmented images to diagnose posture problems, assess physiotherapy treatment evolution and thus reduce diagnostic errors due to subjective analysis.

  15. Unraveling Pancreatic Segmentation.

    Science.gov (United States)

    Renard, Yohann; de Mestier, Louis; Perez, Manuela; Avisse, Claude; Lévy, Philippe; Kianmanesh, Reza

    2018-04-01

    Limited pancreatic resections are increasingly performed, but the rate of postoperative fistula is higher than after classical resections. Pancreatic segmentation, anatomically and radiologically identifiable, may theoretically help the surgeon removing selected anatomical portions with their own segmental pancreatic duct and thus might decrease the postoperative fistula rate. We aimed at systematically and comprehensively reviewing the previously proposed pancreatic segmentations and discuss their relevance and limitations. PubMed database was searched for articles investigating pancreatic segmentation, including human or animal anatomy, and cadaveric or surgical studies. Overall, 47/99 articles were selected and grouped into 4 main hypotheses of pancreatic segmentation methodology: anatomic, vascular, embryologic and lymphatic. The head, body and tail segments are gross description without distinct borders. The arterial territories defined vascular segments and isolate an isthmic paucivascular area. The embryological theory relied on the fusion plans of the embryological buds. The lymphatic drainage pathways defined the lymphatic segmentation. These theories had differences, but converged toward separating the head and body/tail parts, and the anterior from posterior and inferior parts of the pancreatic head. The rate of postoperative fistula was not decreased when surgical resection was performed following any of these segmentation theories; hence, none of them appeared relevant enough to guide pancreatic transections. Current pancreatic segmentation theories do not enable defining anatomical-surgical pancreatic segments. Other approaches should be explored, in particular focusing on pancreatic ducts, through pancreatic ducts reconstructions and embryologic 3D modelization.

  16. Space space space

    CERN Document Server

    Trembach, Vera

    2014-01-01

    Space is an introduction to the mysteries of the Universe. Included are Task Cards for independent learning, Journal Word Cards for creative writing, and Hands-On Activities for reinforcing skills in Math and Language Arts. Space is a perfect introduction to further research of the Solar System.

  17. Cervical Adjacent Segment Disease

    OpenAIRE

    Özbek, Zühtü; Özkara, Emre; Yağmur, İpek; Arslantaş, Ali

    2017-01-01

    Cervical adjacent segment disease; is the general name ofdisc pathologies that develop in adjacent levels after cervical surgery. If thecervical adjacent segment disease that do not require reoperation and it doesnot cause clinical signs is called radiological cervical adjacent segmentpathology, but those causing radiculopathy, myelopathy or instability is calledclinic cervical adjacent segment pathology. The incidence of cervical adjacentsegment disease in 10-year follow-up is 2.4% -2.9%. Wh...

  18. Adjacent segment degeneration

    OpenAIRE

    Birjandi, Alireza

    2012-01-01

    Abstract: Adjacent segment disease (ASD) is defined as degeneration that develops at mobile segments above or below a fused spinal segment and usually develops after spinal fusion or other back surgeries. Nearly 5 decades ago, the medical findings related to ASD were usually released in case reports as a relatively unusual complication of lumbar or lumbosacral fusions. Since the initial reports, ASD has been found to occur more often than the earlier predictions for its prospect incidence. It...

  19. Segmented conjugated polymers

    Indian Academy of Sciences (India)

    Segmented conjugated polymers, wherein the conjugation is randomly truncated by varying lengths of non-conjugated segments, form an interesting class of polymers as they not only represent systems of varying stiffness, but also ones where the backbone can be construed as being made up of chromophores of varying ...

  20. 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

  1. a segmentation approach

    African Journals Online (AJOL)

    kirstam

    Once the market has been segmented into different segments or target markets, a customised marketing mix aimed ... restaurant managers need to understand what motivates consumers to dine out and to choose one ... Customers might consider food quality, price, promotions and recommendations, among other desirable ...

  2. CNN-aware Binary Map for General Semantic Segmentation

    OpenAIRE

    Ravanbakhsh, Mahdyar; Mousavi, Hossein; Nabi, Moin; Rastegari, Mohammad; Regazzoni, Carlo

    2016-01-01

    In this paper we introduce a novel method for general semantic segmentation that can benefit from general semantics of Convolutional Neural Network (CNN). Our segmentation proposes visually and semantically coherent image segments. We use binary encoding of CNN features to overcome the difficulty of the clustering on the high-dimensional CNN feature space. These binary codes are very robust against noise and non-semantic changes in the image. These binary encoding can be embedded into the CNN...

  3. Local label learning (LLL) for subcortical structure segmentation: application to hippocampus segmentation.

    Science.gov (United States)

    Hao, Yongfu; Wang, Tianyao; Zhang, Xinqing; Duan, Yunyun; Yu, Chunshui; Jiang, Tianzi; Fan, Yong

    2014-06-01

    Automatic and reliable segmentation of subcortical structures is an important but difficult task in quantitative brain image analysis. Multi-atlas based segmentation methods have attracted great interest due to their promising performance. Under the multi-atlas based segmentation framework, using deformation fields generated for registering atlas images onto a target image to be segmented, labels of the atlases are first propagated to the target image space and then fused to get the target image segmentation based on a label fusion strategy. While many label fusion strategies have been developed, most of these methods adopt predefined weighting models that are not necessarily optimal. In this study, we propose a novel local label learning strategy to estimate the target image's segmentation label using statistical machine learning techniques. In particular, we use a L1-regularized support vector machine (SVM) with a k nearest neighbor (kNN) based training sample selection strategy to learn a classifier for each of the target image voxel from its neighboring voxels in the atlases based on both image intensity and texture features. Our method has produced segmentation results consistently better than state-of-the-art label fusion methods in validation experiments on hippocampal segmentation of over 100 MR images obtained from publicly available and in-house datasets. Volumetric analysis has also demonstrated the capability of our method in detecting hippocampal volume changes due to Alzheimer's disease. Copyright © 2013 Wiley Periodicals, Inc.

  4. Semi-automated segment generation for geographic novelty ...

    African Journals Online (AJOL)

    Charles

    traverses the parameter space of the segmentation algorithm, searching for results most closely resembling the user-provided reference. Because segmentation is typically computationally expensive, population-based stochastic search methods, such as genetic algorithms, are recommended to produce usable results in a ...

  5. 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

  6. 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

  7. Segmentation of SAR images

    Science.gov (United States)

    Kwok, Ronald

    1989-01-01

    The statistical characteristics of image speckle are reviewed. Existing segmentation techniques that have been used for speckle filtering, edge detection, and texture extraction are sumamrized. The relative effectiveness of each technique is briefly discussed.

  8. Image segmentation survey

    Science.gov (United States)

    Haralick, R. M.

    1982-01-01

    The methodologies and capabilities of image segmentation techniques are reviewed. Single linkage schemes, hybrid linkage schemes, centroid linkage schemes, histogram mode seeking, spatial clustering, and split and merge schemes are addressed.

  9. Adjacent segment disease.

    Science.gov (United States)

    Virk, Sohrab S; Niedermeier, Steven; Yu, Elizabeth; Khan, Safdar N

    2014-08-01

    EDUCATIONAL OBJECTIVES As a result of reading this article, physicians should be able to: 1. Understand the forces that predispose adjacent cervical segments to degeneration. 2. Understand the challenges of radiographic evaluation in the diagnosis of cervical and lumbar adjacent segment disease. 3. Describe the changes in biomechanical forces applied to adjacent segments of lumbar vertebrae with fusion. 4. Know the risk factors for adjacent segment disease in spinal fusion. Adjacent segment disease (ASD) is a broad term encompassing many complications of spinal fusion, including listhesis, instability, herniated nucleus pulposus, stenosis, hypertrophic facet arthritis, scoliosis, and vertebral compression fracture. The area of the cervical spine where most fusions occur (C3-C7) is adjacent to a highly mobile upper cervical region, and this contributes to the biomechanical stress put on the adjacent cervical segments postfusion. Studies have shown that after fusion surgery, there is increased load on adjacent segments. Definitive treatment of ASD is a topic of continuing research, but in general, treatment choices are dictated by patient age and degree of debilitation. Investigators have also studied the risk factors associated with spinal fusion that may predispose certain patients to ASD postfusion, and these data are invaluable for properly counseling patients considering spinal fusion surgery. Biomechanical studies have confirmed the added stress on adjacent segments in the cervical and lumbar spine. The diagnosis of cervical ASD is complicated given the imprecise correlation of radiographic and clinical findings. Although radiological and clinical diagnoses do not always correlate, radiographs and clinical examination dictate how a patient with prolonged pain is treated. Options for both cervical and lumbar spine ASD include fusion and/or decompression. Current studies are encouraging regarding the adoption of arthroplasty in spinal surgery, but more long

  10. Advanced Lightweight Metal Matrix Composite Segmented Optic Manufacture Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Design, manufacture and test a flat segmented mirror made of optical grade AlBeMet 162 material and fusion bonded through the use of E Beam welding to demonstrate...

  11. Extreme-Precision MEMS Segmented Deformable Mirror, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — In Phase I research, Iris AO developed enhanced electromechanical models and calibration techniques for MEMS-based segmented deformable mirrors (DMs) applicable to a...

  12. Improved Large Segmented Optics Fabrication Using Magnetorheological Finishing, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Primary mirrors for large aperture telescopes (> 10 m) are collections of smaller (1-2 m), typically hexagonal, often aspheric, optical segments. NASA's next...

  13. Improved Large Segmented Optics Fabrication Using Magnetorheological Finishing Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Primary mirrors for large aperture telescopes (> 10 m) are collections of smaller (1-2 m), typically hexagonal, often aspheric, optical segments. NASA's next...

  14. Improved Large Segmented Optics Fabrication Using Magnetorheological Finishing Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Primary mirrors for large aperture telescopes (>10m) are collections of smaller (1-2m), typically hexagonal, often aspheric, optical segments. NASA?s next...

  15. Strategic market segmentation

    Directory of Open Access Journals (Sweden)

    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.

  16. Constraint-based Word Segmentation for Chinese

    DEFF Research Database (Denmark)

    Christiansen, Henning; Bo, Li

    2014-01-01

    Written Chinese text has no separators between words in the same way as European languages use space characters, and this creates the Chinese Word Segmentation Problem, CWSP: given a text in Chinese, divide it in a correct way into segments corresponding to words. Good solutions are in demand...... for virtually any nontrivial computational processing of Chinese text, ranging from spellchecking over internet search to deep analysis. Isolating the single words is usually the first phase in the analysis of a text, but as for many other language analysis tasks, to do that perfectly, an insight in syntactic...

  17. Tensile properties of segmented block copolymers with monodisperse hard segments

    NARCIS (Netherlands)

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

    2008-01-01

    The tensile properties of segmented block copolymers with mono-disperse hard segments were studied with respect to the hard segment content (16–44 wt.%) and the temperature (20–110 °C). The copolymers were comprised of poly(tetramethylene oxide) segments with the molecular weights of 650–2,900 Da

  18. 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.

  19. Progress report (interface segment)

    International Nuclear Information System (INIS)

    Fukahori, T.

    2008-01-01

    Full text: 1. Presentations and status reports. T. Fukahori (JAEA) reported on the plans for the www interface layout. Discussions included which functions were needed for new RIPL-3 web pages. The results are summarized in next section. 2. Layout of the interfaces and retrieval tools and web. RIPL-3 home page will include some description about RIPL-3 and link to the Technical report in pdf-format. The web page for 'mass' segment contains same contents as RIPL-2 except the removal of the information about ground state deformation. The abundance data will be replaced by data from the new BNL wallet card (2005 version). The Q-value calculation tool will be also improved. The 'Nuclear Matter Density' will be renamed 'Nucleon Density Distribution'. 'Levels' segment will be same as before, and the deformation parameters for excited levels will be moved from 'optical' segment and given the name 'deformation'. 'Resonances' segment will be same as before - may be replaced with the new Mughabghab tables. 'Optical' segment will be same as before, and the deformation parameters for excited levels will be moved to 'optical' segment and given the name 'deformation'. The optical model calculation with ECIS and OPTMAN will be considered and double-folding calculation tool will possibly be provided. 'Densities' segment will be same as before, and the plotting programs will be checked. The 3-7 sets of combination of GC, BSFG, GSFM with/without enhancement factors will be given. 'Gamma' segment will be same as before, with addition of MLO and theoretical GDR calculation. 'Fission' segment will be same as before, and 'Exp.' will be renamed. New barrier evaluations will be added, for example, transition (2+) states. The fission spectrum calculation tool (codes and inputs) may be added. The fundamental format will be kept as before. For new items such as deformed 'nucleon density distribution', double-folding potential, evaluated fission barrier (extension into 3 or more) and fission

  20. Cooperative processes in image segmentation

    Science.gov (United States)

    Davis, L. S.

    1982-01-01

    Research into the role of cooperative, or relaxation, processes in image segmentation is surveyed. Cooperative processes can be employed at several levels of the segmentation process as a preprocessing enhancement step, during supervised or unsupervised pixel classification and, finally, for the interpretation of image segments based on segment properties and relations.

  1. Segmented heterochromia in scalp hair.

    Science.gov (United States)

    Yoon, Kyeong Han; Kim, Daehwan; Sohn, Seonghyang; Lee, Won Soo

    2003-12-01

    Segmented heterochromia of scalp hair is characterized by the irregularly alternating segmentation of hair into dark and light bands and is known to be associated with iron deficiency anemia. The authors report the case of an 11-year-old boy with segmented heterochromia associated with iron deficiency anemia. After 11 months of iron replacement, the boy's segmented heterochromic hair recovered completely.

  2. Novel block segmentation and processing for Chinese-English document

    Science.gov (United States)

    Chien, Bing-Shan; Jeng, Bor-Shenn; Sun, San-Wei; Chang, Gan-How; Shyu, Keh-Hwa; Shih, Chun-Hsi

    1991-11-01

    The block segmentation and block classification of digitized printed documents segmented into regions of texts, graphics, tables, and images are very important in automatic document analysis and understanding. Conventionally, the constrained run length algorithm (CRLA) has been proposed to segment digitized documents, however, it is space-consuming and time- consuming. The CRLA method must define some constrained parameters, so it cannot proceed automatically, and its performance may degrade significantly due to improper parameters. This paper proposes an efficient and effective method for document analysis, sequence connected segmentation and mapping matrix cell algorithm (SCSMMC). This method can analyze both simple and complex documents automatically and it need not define any constraint parameters. This method, which only needs one-reading image of document, can proceed completely and the techniques of segmentation, classification, labeling, and character segmentation proceed at the same time. The proposed document analysis method may also combine with the optical character recognizer to form an adaptive document understanding system.

  3. Trajectory Based Optimal Segment Computation in Road Network Databases

    DEFF Research Database (Denmark)

    Li, Xiaohui; Ceikute, Vaida; Jensen, Christian S.

    traversal is assigned a score that is distributed among the road segments covered by the route according to a score distribution model. The query returns the road segment(s) with the highest score. To achieve low latency, it is essential to prune the very large search space. We propose two algorithms...... that are shown empirically to be scalable. Given a road network, a set of existing facilities, and a collection of customer route traversals, an optimal segment query returns the optimal road network segment(s) for a new facility. We propose a practical framework for computing this query, where each route...... that adopt different approaches to computing the query. Algorithm AUG uses graph augmentation, and ITE uses iterative road-network partitioning. Empirical studies with real data sets demonstrate that the algorithms are capable of offering high performance in realistic settings....

  4. Organization of arm movements. Motion is segmented.

    Science.gov (United States)

    Soechting, J F; Terzuolo, C A

    1987-10-01

    A kinematic analysis of human arm trajectories which underlie the production of learned, continuous movements (such as drawing of 'figure 8s' and stars) in free space is presented. The objective of this investigation was to see if a set of rules, which had been identified previously and which are appropriate for generating circular or elliptical motion of the wrist in an arbitrary plane, also hold true for arbitrary, learned trajectories provided one additional assumption is made: that apparently continuous complex movements are composed of unit segments. The results presented in this paper are consistent with this hypothesis. Furthermore, as predicted by the hypothesis, the wrist trajectory deviates little from planar motion in each segment while the plane of motion can change abruptly from one segment to the next.

  5. Segmentation of complex document

    Directory of Open Access Journals (Sweden)

    Souad Oudjemia

    2014-06-01

    Full Text Available In this paper we present a method for segmentation of documents image with complex structure. This technique based on GLCM (Grey Level Co-occurrence Matrix used to segment this type of document in three regions namely, 'graphics', 'background' and 'text'. Very briefly, this method is to divide the document image, in block size chosen after a series of tests and then applying the co-occurrence matrix to each block in order to extract five textural parameters which are energy, entropy, the sum entropy, difference entropy and standard deviation. These parameters are then used to classify the image into three regions using the k-means algorithm; the last step of segmentation is obtained by grouping connected pixels. Two performance measurements are performed for both graphics and text zones; we have obtained a classification rate of 98.3% and a Misclassification rate of 1.79%.

  6. Image segmentation, evaluation, and applications

    OpenAIRE

    McGuinness, Kevin

    2010-01-01

    This thesis aims to advance research in image segmentation by developing robust techniques for evaluating image segmentation algorithms. The key contributions of this work are as follows. First, we investigate the characteristics of existing measures for supervised evaluation of automatic image segmentation algorithms. We show which of these measures is most effective at distinguishing perceptually accurate image segmentation from inaccurate segmentation. We then apply these measures to evalu...

  7. Connecting textual segments

    DEFF Research Database (Denmark)

    Brügger, Niels

    2017-01-01

    In “Connecting textual segments: A brief history of the web hyperlink” Niels Brügger investigates the history of one of the most fundamental features of the web: the hyperlink. Based on the argument that the web hyperlink is best understood if it is seen as another step in a much longer and broader...... history than just the years of the emergence of the web, the chapter traces the history of how segments of text have deliberately been connected to each other by the use of specific textual and media features, from clay tablets, manuscripts on parchment, and print, among others, to hyperlinks on stand...

  8. Optimal graph based segmentation using flow lines with application to airway wall segmentation

    DEFF Research Database (Denmark)

    Petersen, Jens; Nielsen, Mads; Lo, Pechin Chien Pau

    2011-01-01

    This paper introduces a novel optimal graph construction method that is applicable to multi-dimensional, multi-surface segmentation problems. Such problems are often solved by refining an initial coarse surface within the space given by graph columns. Conventional columns are not well suited for ...

  9. Optimal graph based segmentation using flow lines with application to airway wall segmentation

    DEFF Research Database (Denmark)

    Petersen, Jens; Nielsen, Mads; Lo, Pechin

    2011-01-01

    This paper introduces a novel optimal graph construction method that is applicable to multi-dimensional, multi-surface segmentation problems. Such problems are often solved by refining an initial coarse surface within the space given by graph columns. Conventional columns are not well suited...

  10. Multidimensional Brain MRI segmentation using graph cuts

    International Nuclear Information System (INIS)

    Lecoeur, Jeremy

    2010-01-01

    This thesis deals with the segmentation of multimodal brain MRIs by graph cuts method. First, we propose a method that utilizes three MRI modalities by merging them. The border information given by the spectral gradient is then challenged by a region information, given by the seeds selected by the user, using a graph cut algorithm. Then, we propose three enhancements of this method. The first consists in finding an optimal spectral space because the spectral gradient is based on natural images and then inadequate for multimodal medical images. This results in a learning based segmentation method. We then explore the automation of the graph cut method. Here, the various pieces of information usually given by the user are inferred from a robust expectation-maximization algorithm. We show the performance of these two enhanced versions on multiple sclerosis lesions. Finally, we integrate atlases for the automatic segmentation of deep brain structures. These three new techniques show the adaptability of our method to various problems. Our different segmentation methods are better than most of nowadays techniques, speaking of computation time or segmentation accuracy. (authors)

  11. Optimally segmented magnetic structures

    DEFF Research Database (Denmark)

    Insinga, Andrea Roberto; Bahl, Christian; Bjørk, Rasmus

    We present a semi-analytical algorithm for magnet design problems, which calculates the optimal way to subdivide a given design region into uniformly magnetized segments.The availability of powerful rare-earth magnetic materials such as Nd-Fe-B has broadened the range of applications of permanent...

  12. The LOFT Ground Segment

    DEFF Research Database (Denmark)

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

    2014-01-01

    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...

  13. Sipunculans and segmentation

    DEFF Research Database (Denmark)

    Wanninger, Andreas; Kristof, Alen; Brinkmann, Nora

    2009-01-01

    Comparative molecular, developmental and morphogenetic analyses show that the three major segmented animal groups- Lophotrochozoa, Ecdysozoa and Vertebrata-use a wide range of ontogenetic pathways to establish metameric body organization. Even in the life history of a single specimen, different...

  14. Unsupervised Image Segmentation

    Czech Academy of Sciences Publication Activity Database

    Haindl, Michal; Mikeš, Stanislav

    2014-01-01

    Roč. 36, č. 4 (2014), s. 23-23 R&D Projects: GA ČR(CZ) GA14-10911S Institutional support: RVO:67985556 Keywords : unsupervised image segmentation Subject RIV: BD - Theory of Information http:// library .utia.cas.cz/separaty/2014/RO/haindl-0434412.pdf

  15. 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.

  16. Dictionary Based Image Segmentation

    DEFF Research Database (Denmark)

    Dahl, Anders Bjorholm; Dahl, Vedrana Andersen

    2015-01-01

    We propose a method for weakly supervised segmentation of natural images, which may contain both textured or non-textured regions. Our texture representation is based on a dictionary of image patches. To divide an image into separated regions with similar texture we use an implicit level sets...

  17. A Cooperative Learning-Based Clustering Approach to Lip Segmentation Without Knowing Segment Number.

    Science.gov (United States)

    Cheung, Yiu-Ming; Li, Meng; Peng, Qinmu; Chen, C L Philip

    2017-01-01

    It is usually hard to predetermine the true number of segments in lip segmentation. This paper, therefore, presents a clustering-based approach to lip segmentation without knowing the true segment number. The objective function in the proposed approach is a variant of the partition entropy (PE) and features that the coincident cluster centroids in pattern space can be equivalently substituted by one centroid with the function value unchanged. It is shown that the minimum of the proposed objective function can be reached provided that: 1) the number of positions occupied by cluster centroids in pattern space is equal to the true number of clusters and 2) these positions are coincident with the optimal cluster centroids obtained under PE criterion. In implementation, we first randomly initialize the clusters provided that the number of clusters is greater than or equal to the ground truth. Then, an iterative algorithm is utilized to minimize the proposed objective function. For each iterative step, not only is the winner, i.e., the centroid with the maximum membership degree, updated to adapt to the corresponding input data, but also the other centroids are adjusted with a specific cooperation strength, so that they are each close to the winner. Subsequently, the initial overpartition will be gradually faded out with the redundant centroids superposed over the convergence of the algorithm. Based upon the proposed algorithm, we present a lip segmentation scheme. Empirical studies have shown its efficacy in comparison with the existing methods.

  18. Membrane Shell Reflector Segment Antenna

    Science.gov (United States)

    Fang, Houfei; Im, Eastwood; Lin, John; Moore, James

    2012-01-01

    The mesh reflector is the only type of large, in-space deployable antenna that has successfully flown in space. However, state-of-the-art large deployable mesh antenna systems are RF-frequency-limited by both global shape accuracy and local surface quality. The limitations of mesh reflectors stem from two factors. First, at higher frequencies, the porosity and surface roughness of the mesh results in loss and scattering of the signal. Second, the mesh material does not have any bending stiffness and thus cannot be formed into true parabolic (or other desired) shapes. To advance the deployable reflector technology at high RF frequencies from the current state-of-the-art, significant improvements need to be made in three major aspects: a high-stability and highprecision deployable truss; a continuously curved RF reflecting surface (the function of the surface as well as its first derivative are both continuous); and the RF reflecting surface should be made of a continuous material. To meet these three requirements, the Membrane Shell Reflector Segment (MSRS) antenna was developed.

  19. End-to-End Neural Segmental Models for Speech Recognition

    Science.gov (United States)

    Tang, Hao; Lu, Liang; Kong, Lingpeng; Gimpel, Kevin; Livescu, Karen; Dyer, Chris; Smith, Noah A.; Renals, Steve

    2017-12-01

    Segmental models are an alternative to frame-based models for sequence prediction, where hypothesized path weights are based on entire segment scores rather than a single frame at a time. Neural segmental models are segmental models that use neural network-based weight functions. Neural segmental models have achieved competitive results for speech recognition, and their end-to-end training has been explored in several studies. In this work, we review neural segmental models, which can be viewed as consisting of a neural network-based acoustic encoder and a finite-state transducer decoder. We study end-to-end segmental models with different weight functions, including ones based on frame-level neural classifiers and on segmental recurrent neural networks. We study how reducing the search space size impacts performance under different weight functions. We also compare several loss functions for end-to-end training. Finally, we explore training approaches, including multi-stage vs. end-to-end training and multitask training that combines segmental and frame-level losses.

  20. Computer aided wireless capsule endoscopy video segmentation.

    Science.gov (United States)

    Li, Baopu; Xu, Guoqing; Zhou, Ran; Wang, Tianfu

    2015-02-01

    Wireless capsule endoscopy (WCE) opens a new door for the digestive tract examination and diagnosis. However, the examination of its video data is tedious. This study aims to assist a physician to interpret a WCE video by segmenting it into different anatomic parts in the digestive tract. A two level WCE video segmentation scheme is proposed to locate the boundary between the stomach, small intestine, and large intestine. In the rough level, the authors utilize color feature to draw a dissimilarity curve for a WCE video and obtain an approximate boundary. Meanwhile, training data for the fine level segmentation can be collected automatically between the two approximate boundaries of organs to overcome the difficulty of training data collection in traditional approaches. In the fine level, color histogram in the HSI color space is used to segment the stomach and small intestine. Then, color uniform local binary pattern (CULBP) algorithm is applied for discrimination of the small intestine and large intestine, which includes two patterns, namely, color norm and color angle pattern. The CULBP feature is robust to variation of illumination and discriminative for classification. In order to increase the performance of support vector machine, the authors integrate it with the Adaboost approach. Finally, the authors refine the classification results to segment a WCE video into different parts, that is, the stomach, small intestine, and large intestine. The average precision and recall are 91.2% and 90.6% for the stomach/small intestine classification, 89.2% and 88.7% for the small/large intestine discrimination. Paired t-test also demonstrates a significant better performance of the proposed scheme compared to some traditional methods. The average segmentation error is 8 frames for the stomach/small intestine discrimination, and 14 frames for the small/large intestine segmentation. The results have demonstrated that the new video segmentation method can accurately locate

  1. Market segmentation: Venezuelan ADRs

    Directory of Open Access Journals (Sweden)

    Urbi Garay

    2012-12-01

    Full Text Available The control on foreign exchange imposed by Venezuela in 2003 constitute a natural experiment that allows researchers to observe the effects of exchange controls on stock market segmentation. This paper provides empirical evidence that although the Venezuelan capital market as a whole was highly segmented before the controls were imposed, the shares in the firm CANTV were, through their American Depositary Receipts (ADRs, partially integrated with the global market. Following the imposition of the exchange controls this integration was lost. Research also documents the spectacular and apparently contradictory rise experienced by the Caracas Stock Exchange during the serious economic crisis of 2003. It is argued that, as it happened in Argentina in 2002, the rise in share prices occurred because the depreciation of the Bolívar in the parallel currency market increased the local price of the stocks that had associated ADRs, which were negotiated in dollars.

  2. Scintillation counter, segmented shield

    International Nuclear Information System (INIS)

    Olson, R.E.; Thumim, A.D.

    1975-01-01

    A scintillation counter, particularly for counting gamma ray photons, includes a massive lead radiation shield surrounding a sample-receiving zone. The shield is disassembleable into a plurality of segments to allow facile installation and removal of a photomultiplier tube assembly, the segments being so constructed as to prevent straight-line access of external radiation through the shield into radiation-responsive areas. Provisions are made for accurately aligning the photomultiplier tube with respect to one or more sample-transmitting bores extending through the shield to the sample receiving zone. A sample elevator, used in transporting samples into the zone, is designed to provide a maximum gamma-receiving aspect to maximize the gamma detecting efficiency. (U.S.)

  3. Identifying anterior segment crystals.

    OpenAIRE

    Hurley, I W; Brooks, A M; Reinehr, D P; Grant, G B; Gillies, W E

    1991-01-01

    A series of 22 patients with crystals in the anterior segment of the eye was examined by specular microscopy. Of 10 patients with hypermature cataract and hyperrefringent bodies in the anterior chamber cholesterol crystals were identified in four patients and in six of the 10 in whom aspirate was obtained cholesterol crystals were demonstrated in three, two of these having shown crystals on specular microscopy. In 10 patients with intracorneal crystalline deposits, cholesterol crystals were f...

  4. Head segmentation in vertebrates

    OpenAIRE

    Kuratani, Shigeru; Schilling, Thomas

    2008-01-01

    Classic theories of vertebrate head segmentation clearly exemplify the idealistic nature of comparative embryology prior to the 20th century. Comparative embryology aimed at recognizing the basic, primary structure that is shared by all vertebrates, either as an archetype or an ancestral developmental pattern. Modern evolutionary developmental (Evo-Devo) studies are also based on comparison, and therefore have a tendency to reduce complex embryonic anatomy into overly simplified patterns. Her...

  5. 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...

  6. Spinal segmental dysgenesis CASE SERIES

    African Journals Online (AJOL)

    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 in nature, with vertebrae above and below the malformation. It is commonly associated with various abnormalities that ...

  7. 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…

  8. 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)

  9. Joint Rendering and Segmentation of Free-Viewpoint Video

    Directory of Open Access Journals (Sweden)

    Ishii Masato

    2010-01-01

    Full Text Available Abstract This paper presents a method that jointly performs synthesis and object segmentation of free-viewpoint video using multiview video as the input. This method is designed to achieve robust segmentation from online video input without per-frame user interaction and precomputations. This method shares a calculation process between the synthesis and segmentation steps; the matching costs calculated through the synthesis step are adaptively fused with other cues depending on the reliability in the segmentation step. Since the segmentation is performed for arbitrary viewpoints directly, the extracted object can be superimposed onto another 3D scene with geometric consistency. We can observe that the object and new background move naturally along with the viewpoint change as if they existed together in the same space. In the experiments, our method can process online video input captured by a 25-camera array and show the result image at 4.55 fps.

  10. Validation tools for image segmentation

    Science.gov (United States)

    Padfield, Dirk; Ross, James

    2009-02-01

    A large variety of image analysis tasks require the segmentation of various regions in an image. For example, segmentation is required to generate accurate models of brain pathology that are important components of modern diagnosis and therapy. While the manual delineation of such structures gives accurate information, the automatic segmentation of regions such as the brain and tumors from such images greatly enhances the speed and repeatability of quantifying such structures. The ubiquitous need for such algorithms has lead to a wide range of image segmentation algorithms with various assumptions, parameters, and robustness. The evaluation of such algorithms is an important step in determining their effectiveness. Therefore, rather than developing new segmentation algorithms, we here describe validation methods for segmentation algorithms. Using similarity metrics comparing the automatic to manual segmentations, we demonstrate methods for optimizing the parameter settings for individual cases and across a collection of datasets using the Design of Experiment framework. We then employ statistical analysis methods to compare the effectiveness of various algorithms. We investigate several region-growing algorithms from the Insight Toolkit and compare their accuracy to that of a separate statistical segmentation algorithm. The segmentation algorithms are used with their optimized parameters to automatically segment the brain and tumor regions in MRI images of 10 patients. The validation tools indicate that none of the ITK algorithms studied are able to outperform with statistical significance the statistical segmentation algorithm although they perform reasonably well considering their simplicity.

  11. Electrocardiogram ST-Segment Morphology Delineation Method Using Orthogonal Transformations.

    Directory of Open Access Journals (Sweden)

    Miha Amon

    Full Text Available Differentiation between ischaemic and non-ischaemic transient ST segment events of long term ambulatory electrocardiograms is a persisting weakness in present ischaemia detection systems. Traditional ST segment level measuring is not a sufficiently precise technique due to the single point of measurement and severe noise which is often present. We developed a robust noise resistant orthogonal-transformation based delineation method, which allows tracing the shape of transient ST segment morphology changes from the entire ST segment in terms of diagnostic and morphologic feature-vector time series, and also allows further analysis. For these purposes, we developed a new Legendre Polynomials based Transformation (LPT of ST segment. Its basis functions have similar shapes to typical transient changes of ST segment morphology categories during myocardial ischaemia (level, slope and scooping, thus providing direct insight into the types of time domain morphology changes through the LPT feature-vector space. We also generated new Karhunen and Lo ève Transformation (KLT ST segment basis functions using a robust covariance matrix constructed from the ST segment pattern vectors derived from the Long Term ST Database (LTST DB. As for the delineation of significant transient ischaemic and non-ischaemic ST segment episodes, we present a study on the representation of transient ST segment morphology categories, and an evaluation study on the classification power of the KLT- and LPT-based feature vectors to classify between ischaemic and non-ischaemic ST segment episodes of the LTST DB. Classification accuracy using the KLT and LPT feature vectors was 90% and 82%, respectively, when using the k-Nearest Neighbors (k = 3 classifier and 10-fold cross-validation. New sets of feature-vector time series for both transformations were derived for the records of the LTST DB which is freely available on the PhysioNet website and were contributed to the LTST DB. The

  12. Effective phonocardiogram segmentation using time statistics and nonlinear prediction

    Science.gov (United States)

    Sridharan, Rajeswari; Janet, J.

    2010-02-01

    In the fields of image processing, signal processing and recognition, image Segmentation is an efficient method for segmenting the phonocardiograph signals (PCG) is offered. Primarily, inter-beat segmentation is approved and carried out by means of DII lead of the ECG recording for identifying the happenings of the very first heart sound (S1). Then, the intra-beat segmentation is attained by the use of recurrence time statistics (RTS), and that is very sensitive to variations of the renovated attractor in a state space derived from nonlinear dynamic analysis. Apart from this if the segmentation with RTS is unsuccessful, a special segmentation is proposed using threshold that is extracted from the high frequency rate decomposition and the feature extraction of the disorder is classified based on the murmur sounds. In the Inter-beat segmentation process the accuracy was 100% of the over all PCG recording. Taking into account a different level of PCG beats were strongly concerned by different types of cardiac murmurs and intra-beat segmentation are give up for an accurate result.

  13. Application of reinforcement learning for segmentation of transrectal ultrasound images

    Directory of Open Access Journals (Sweden)

    Tizhoosh Hamid R

    2008-04-01

    Full Text Available Abstract Background Among different medical image modalities, ultrasound imaging has a very widespread clinical use. But, due to some factors, such as poor image contrast, noise and missing or diffuse boundaries, the ultrasound images are inherently difficult to segment. An important application is estimation of the location and volume of the prostate in transrectal ultrasound (TRUS images. For this purpose, manual segmentation is a tedious and time consuming procedure. Methods We introduce a new method for the segmentation of the prostate in transrectal ultrasound images, using a reinforcement learning scheme. This algorithm is used to find the appropriate local values for sub-images and to extract the prostate. It contains an offline stage, where the reinforcement learning agent uses some images and manually segmented versions of these images to learn from. The reinforcement agent is provided with reward/punishment, determined objectively to explore/exploit the solution space. After this stage, the agent has acquired knowledge stored in the Q-matrix. The agent can then use this knowledge for new input images to extract a coarse version of the prostate. Results We have carried out experiments to segment TRUS images. The results demonstrate the potential of this approach in the field of medical image segmentation. Conclusion By using the proposed method, we can find the appropriate local values and segment the prostate. This approach can be used for segmentation tasks containing one object of interest. To improve this prototype, more investigations are needed.

  14. Local manifold learning for multiatlas segmentation: application to hippocampal segmentation in healthy population and Alzheimer's disease.

    Science.gov (United States)

    Li, Xin-Wei; Li, Qiong-Ling; Li, Shu-Yu; Li, De-Yu

    2015-10-01

    Automated hippocampal segmentation is an important issue in many neuroscience studies. We presented and evaluated a novel segmentation method that utilized a manifold learning technique under the multiatlas-based segmentation scenario. A manifold representation of local patches for each voxel was achieved by applying an Isomap algorithm, which can then be used to obtain spatially local weights of atlases for label fusion. The obtained atlas weights potentially depended on all pairwise similarities of the population, which is in contrast to most existing label fusion methods that only rely on similarities between the target image and the atlases. The performance of the proposed method was evaluated for hippocampal segmentation and compared with two representative local weighted label fusion methods, that is, local majority voting and local weighted inverse distance voting, on an in-house dataset of 28 healthy adolescents (age range: 10-17 years) and two ADNI datasets of 100 participants (age range: 60-89 years). We also implemented hippocampal volumetric analysis and evaluated segmentation performance using atlases from a different dataset. The median Dice similarities obtained by our proposed method were approximately 0.90 for healthy subjects and above 0.88 for two mixed diagnostic groups of ADNI subjects. The experimental results demonstrated that the proposed method could obtain consistent and significant improvements over label fusion strategies that are implemented in the original space. © 2015 John Wiley & Sons Ltd.

  15. Segmentation Using Symmetry Deviation

    DEFF Research Database (Denmark)

    Hollensen, Christian; Højgaard, L.; Specht, L.

    2011-01-01

    and evaluate the method. The method uses deformable registration on computed tomography(CT) to find anatomical symmetry deviations of Head & Neck squamous cell carcinoma and combining it with positron emission tomography (PET) images. The method allows the use anatomical and symmetrical information of CT scans...... segmentations on manual contours was evaluated using concordance index and sensitivity for the hypopharyngeal patients. The resulting concordance index and sensitivity was compared with the result of using a threshold of 3 SUV using a paired t-test. Results: The anatomical and symmetrical atlas was constructed...... and sensitivity of respectively 0.43±0.15 and 0.56±0.18 was acquired. It was compared to the concordance index of segmentation using absolute threshold of 3 SUV giving respectively 0.41±0.16 and 0.51±0.19 for concordance index and sensitivity yielding p-values of 0.33 and 0.01 for a paired t-test respectively....

  16. 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...

  17. 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.

  18. Segmented rail linear induction motor

    Science.gov (United States)

    Cowan, M. Jr.; Marder, B.M.

    1996-09-03

    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. 6 figs.

  19. Robotic Arm Comprising Two Bending Segments

    Science.gov (United States)

    Mehling, Joshua S.; Difler, Myron A.; Ambrose, Robert O.; Chu, Mars W.; Valvo, Michael C.

    2010-01-01

    The figure shows several aspects of an experimental robotic manipulator that includes a housing from which protrudes a tendril- or tentacle-like arm 1 cm thick and 1 m long. The arm consists of two collinear segments, each of which can be bent independently of the other, and the two segments can be bent simultaneously in different planes. The arm can be retracted to a minimum length or extended by any desired amount up to its full length. The arm can also be made to rotate about its own longitudinal axis. Some prior experimental robotic manipulators include single-segment bendable arms. Those arms are thicker and shorter than the present one. The present robotic manipulator serves as a prototype of future manipulators that, by virtue of the slenderness and multiple- bending capability of their arms, are expected to have sufficient dexterity for operation within spaces that would otherwise be inaccessible. Such manipulators could be especially well suited as means of minimally invasive inspection during construction and maintenance activities. Each of the two collinear bending arm segments is further subdivided into a series of collinear extension- and compression-type helical springs joined by threaded links. The extension springs occupy the majority of the length of the arm and engage passively in bending. The compression springs are used for actively controlled bending. Bending is effected by means of pairs of antagonistic tendons in the form of spectra gel spun polymer lines that are attached at specific threaded links and run the entire length of the arm inside the spring helix from the attachment links to motor-driven pulleys inside the housing. Two pairs of tendons, mounted in orthogonal planes that intersect along the longitudinal axis, are used to effect bending of each segment. The tendons for actuating the distal bending segment are in planes offset by an angle of 45 from those of the proximal bending segment: This configuration makes it possible to

  20. Segmented heat exchanger

    Science.gov (United States)

    Baldwin, Darryl Dean; Willi, Martin Leo; Fiveland, Scott Byron; Timmons, Kristine Ann

    2010-12-14

    A segmented heat exchanger system for transferring heat energy from an exhaust fluid to a working fluid. The heat exchanger system may include a first heat exchanger for receiving incoming working fluid and the exhaust fluid. The working fluid and exhaust fluid may travel through at least a portion of the first heat exchanger in a parallel flow configuration. In addition, the heat exchanger system may include a second heat exchanger for receiving working fluid from the first heat exchanger and exhaust fluid from a third heat exchanger. The working fluid and exhaust fluid may travel through at least a portion of the second heat exchanger in a counter flow configuration. Furthermore, the heat exchanger system may include a third heat exchanger for receiving working fluid from the second heat exchanger and exhaust fluid from the first heat exchanger. The working fluid and exhaust fluid may travel through at least a portion of the third heat exchanger in a parallel flow configuration.

  1. International EUREKA: Market Segment

    International Nuclear Information System (INIS)

    1982-03-01

    The purpose of the Market Segment of the EUREKA model is to simultaneously project uranium market prices, uranium supply and purchasing activities. The regional demands are extrinsic. However, annual forward contracting activities to meet these demands as well as inventory requirements are calculated. The annual price forecast is based on relatively short term, forward balances between available supply and desired purchases. The forecasted prices and extrapolated price trends determine decisions related to exploration and development, new production operations, and the operation of existing capacity. Purchasing and inventory requirements are also adjusted based on anticipated prices. The calculation proceeds one year at a time. Conditions calculated at the end of one year become the starting conditions for the calculation in the subsequent year

  2. 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.

  3. 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

  4. Segmenting Words from Natural Speech: Subsegmental Variation in Segmental Cues

    Science.gov (United States)

    Rytting, C. Anton; Brew, Chris; Fosler-Lussier, Eric

    2010-01-01

    Most computational models of word segmentation are trained and tested on transcripts of speech, rather than the speech itself, and assume that speech is converted into a sequence of symbols prior to word segmentation. We present a way of representing speech corpora that avoids this assumption, and preserves acoustic variation present in speech. We…

  5. A variational approach to bone segmentation in CT images

    Science.gov (United States)

    Calder, Jeff; Tahmasebi, Amir M.; Mansouri, Abdol-Reza

    2011-03-01

    We present a variational approach for segmenting bone structures in Computed Tomography (CT) images. We introduce a novel functional on the space of image segmentations, and subsequently minimize this functional through a gradient descent partial differential equation. The functional we propose provides a measure of similarity of the intensity characteristics of the bone and tissue regions through a comparison of their cumulative distribution functions; minimizing this similarity measure therefore yields the maximal separation between the two regions. We perform the minimization of our proposed functional using level set partial differential equations; in addition to numerical stability, this yields topology independence, which is especially useful in the context of CT bone segmentation where a bone region may consist of several disjoint pieces. Finally, we present an extensive validation of our method against expert manual segmentation on CT images of the wrist, ankle, foot, and pelvis.

  6. [Tumor segmentation of brain MRI with adaptive bandwidth mean shift].

    Science.gov (United States)

    Hou, Xiaowen; Liu, Qi

    2014-10-01

    In order to get the adaptive bandwidth of mean shift to make the tumor segmentation of brain magnetic resonance imaging (MRI) to be more accurate, we in this paper present an advanced mean shift method. Firstly, we made use of the space characteristics of brain image to eliminate the impact on segmentation of skull; and then, based on the characteristics of spatial agglomeration of different tissues of brain (includes tumor), we applied edge points to get the optimal initial mean value and the respectively adaptive bandwidth, in order to improve the accuracy of tumor segmentation. The results of experiment showed that, contrast to the fixed bandwidth mean shift method, the method in this paper could segment the tumor more accurately.

  7. 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…

  8. The Importance of Marketing Segmentation

    Science.gov (United States)

    Martin, Gillian

    2011-01-01

    The rationale behind marketing segmentation is to allow businesses to focus on their consumers' behaviors and purchasing patterns. If done effectively, marketing segmentation allows an organization to achieve its highest return on investment (ROI) in turn for its marketing and sales expenses. If an organization markets its products or services to…

  9. Automatic segmentation of the colon

    Science.gov (United States)

    Wyatt, Christopher L.; Ge, Yaorong; Vining, David J.

    1999-05-01

    Virtual colonoscopy is a minimally invasive technique that enables detection of colorectal polyps and cancer. Normally, a patient's bowel is prepared with colonic lavage and gas insufflation prior to computed tomography (CT) scanning. An important step for 3D analysis of the image volume is segmentation of the colon. The high-contrast gas/tissue interface that exists in the colon lumen makes segmentation of the majority of the colon relatively easy; however, two factors inhibit automatic segmentation of the entire colon. First, the colon is not the only gas-filled organ in the data volume: lungs, small bowel, and stomach also meet this criteria. User-defined seed points placed in the colon lumen have previously been required to spatially isolate only the colon. Second, portions of the colon lumen may be obstructed by peristalsis, large masses, and/or residual feces. These complicating factors require increased user interaction during the segmentation process to isolate additional colon segments. To automate the segmentation of the colon, we have developed a method to locate seed points and segment the gas-filled lumen with no user supervision. We have also developed an automated approach to improve lumen segmentation by digitally removing residual contrast-enhanced fluid resulting from a new bowel preparation that liquefies and opacifies any residual feces.

  10. 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...

  11. 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…

  12. 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

  13. Segmentation-DrivenTomographic Reconstruction

    DEFF Research Database (Denmark)

    Kongskov, Rasmus Dalgas

    ), the classical reconstruction methods suffer from their inability to handle limited and/ or corrupted data. Form any analysis tasks computationally demanding segmentation methods are used to automatically segment an object, after using a simple reconstruction method as a first step. In the literature, methods...... problem. The tests showed a clear improvement for realistic materials simulations and that the one-stage method was clearly more robust toward noise. The noise-robustness result could be a step toward making this method more applicable for lab-scale experiments. We have introduced a segmentation...... that completely combine reconstruction and segmentation have been suggested, but these are often non-convex and have very high computational demand. We propose to move the computational effort from the segmentation process to the reconstruction process, and instead design reconstruction methods...

  14. Fast approximation for joint optimization of segmentation, shape, and location priors, and its application in gallbladder segmentation.

    Science.gov (United States)

    Saito, Atsushi; Nawano, Shigeru; Shimizu, Akinobu

    2017-05-01

    This paper addresses joint optimization for segmentation and shape priors, including translation, to overcome inter-subject variability in the location of an organ. Because a simple extension of the previous exact optimization method is too computationally complex, we propose a fast approximation for optimization. The effectiveness of the proposed approximation is validated in the context of gallbladder segmentation from a non-contrast computed tomography (CT) volume. After spatial standardization and estimation of the posterior probability of the target organ, simultaneous optimization of the segmentation, shape, and location priors is performed using a branch-and-bound method. Fast approximation is achieved by combining sampling in the eigenshape space to reduce the number of shape priors and an efficient computational technique for evaluating the lower bound. Performance was evaluated using threefold cross-validation of 27 CT volumes. Optimization in terms of translation of the shape prior significantly improved segmentation performance. The proposed method achieved a result of 0.623 on the Jaccard index in gallbladder segmentation, which is comparable to that of state-of-the-art methods. The computational efficiency of the algorithm is confirmed to be good enough to allow execution on a personal computer. Joint optimization of the segmentation, shape, and location priors was proposed, and it proved to be effective in gallbladder segmentation with high computational efficiency.

  15. Nonparametric Facial Feature Localization Using Segment-Based Eigenfeatures

    Directory of Open Access Journals (Sweden)

    Hyun-Chul Choi

    2016-01-01

    Full Text Available We present a nonparametric facial feature localization method using relative directional information between regularly sampled image segments and facial feature points. Instead of using any iterative parameter optimization technique or search algorithm, our method finds the location of facial feature points by using a weighted concentration of the directional vectors originating from the image segments pointing to the expected facial feature positions. Each directional vector is calculated by linear combination of eigendirectional vectors which are obtained by a principal component analysis of training facial segments in feature space of histogram of oriented gradient (HOG. Our method finds facial feature points very fast and accurately, since it utilizes statistical reasoning from all the training data without need to extract local patterns at the estimated positions of facial features, any iterative parameter optimization algorithm, and any search algorithm. In addition, we can reduce the storage size for the trained model by controlling the energy preserving level of HOG pattern space.

  16. Segmental vitiligo with segmental morphea: An autoimmune link?

    Directory of Open Access Journals (Sweden)

    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.

  17. A Segmental Framework for Representing Signs Phonetically

    Science.gov (United States)

    Johnson, Robert E.; Liddell, Scott K.

    2011-01-01

    The arguments for dividing the signing stream in signed languages into sequences of phonetic segments are compelling. The visual records of instances of actually occurring signs provide evidence of two basic types of segments: postural segments and trans-forming segments. Postural segments specify an alignment of articulatory features, both manual…

  18. Sometimes spelling is easier than phonemic segmentation

    NARCIS (Netherlands)

    Bon, W.H.J. van; Duighuisen, H.C.M.

    1995-01-01

    Poor spellers from the Netherlands segmented and spelled the same words on different occasions. If they base their spellings on the segmentations that they produce in the segmentation task, the correlation between segmentation and spelling scores should be high, and segmentation should not be more

  19. Histological image segmentation using fast mean shift clustering method.

    Science.gov (United States)

    Wu, Geming; Zhao, Xinyan; Luo, Shuqian; Shi, Hongli

    2015-03-20

    Colour image segmentation is fundamental and critical for quantitative histological image analysis. The complexity of the microstructure and the approach to make histological images results in variable staining and illumination variations. And ultra-high resolution of histological images makes it is hard for image segmentation methods to achieve high-quality segmentation results and low computation cost at the same time. Mean Shift clustering approach is employed for histological image segmentation. Colour histological image is transformed from RGB to CIE L*a*b* colour space, and then a* and b* components are extracted as features. To speed up Mean Shift algorithm, the probability density distribution is estimated in feature space in advance and then the Mean Shift scheme is used to separate the feature space into different regions by finding the density peaks quickly. And an integral scheme is employed to reduce the computation cost of mean shift vector significantly. Finally image pixels are classified into clusters according to which region their features fall into in feature space. Numerical experiments are carried on liver fibrosis histological images. Experimental results demonstrate that Mean Shift clustering achieves more accurate results than k-means but is computational expensive, and the speed of the improved Mean Shift method is comparable to that of k-means while the accuracy of segmentation results is the same as that achieved using standard Mean Shift method. An effective and reliable histological image segmentation approach is proposed in this paper. It employs improved Mean Shift clustering, which is speed up by using probability density distribution estimation and the integral scheme.

  20. Automatic segmentation of blood vessels from retinal fundus images ...

    Indian Academy of Sciences (India)

    through image processing and data mining techniques. Retinal image data, which is given as input for data mining process is considered as Big Data since every pixel forms a tuple. Blood vessel network is segmented through color space conversion and channel extraction, image pre-processing, Gabor filtering, application ...

  1. Direct volume estimation without segmentation

    Science.gov (United States)

    Zhen, X.; Wang, Z.; Islam, A.; Bhaduri, M.; Chan, I.; Li, S.

    2015-03-01

    Volume estimation plays an important role in clinical diagnosis. For example, cardiac ventricular volumes including left ventricle (LV) and right ventricle (RV) are important clinical indicators of cardiac functions. Accurate and automatic estimation of the ventricular volumes is essential to the assessment of cardiac functions and diagnosis of heart diseases. Conventional methods are dependent on an intermediate segmentation step which is obtained either manually or automatically. However, manual segmentation is extremely time-consuming, subjective and highly non-reproducible; automatic segmentation is still challenging, computationally expensive, and completely unsolved for the RV. Towards accurate and efficient direct volume estimation, our group has been researching on learning based methods without segmentation by leveraging state-of-the-art machine learning techniques. Our direct estimation methods remove the accessional step of segmentation and can naturally deal with various volume estimation tasks. Moreover, they are extremely flexible to be used for volume estimation of either joint bi-ventricles (LV and RV) or individual LV/RV. We comparatively study the performance of direct methods on cardiac ventricular volume estimation by comparing with segmentation based methods. Experimental results show that direct estimation methods provide more accurate estimation of cardiac ventricular volumes than segmentation based methods. This indicates that direct estimation methods not only provide a convenient and mature clinical tool for cardiac volume estimation but also enables diagnosis of cardiac diseases to be conducted in a more efficient and reliable way.

  2. 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.

  3. Giotto: the european space probe

    International Nuclear Information System (INIS)

    Berner, C.; Vandenbussche, F.C.

    1986-01-01

    The Giotto mission is an in situ exploration of the comet Halley. It will be the European Space Agency's first operational deep-space mission, with a spacecraft-Earth distance at comet encounter of approximately 1 AU (150 000 000 km). This paper gives a summary of the mission profile, of the spacecraft design with its associated payload and ground segment [fr

  4. Segmented copolymers with monodisperse crystallizable hard segments: novel semi-crystalline materials

    NARCIS (Netherlands)

    Gaymans, R.J.

    2011-01-01

    Segmented block copolymers with short monodisperse crystallizable hard segments have interesting structures and properties. In the melt, such short monodisperse segments are miscible with the matrix segments. Moreover, upon cooling, they crystallize fast, demonstrating a very high crystallinity, and

  5. 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.

  6. Multiple Segmentation of Image Stacks

    DEFF Research Database (Denmark)

    Smets, Jonathan; Jaeger, Manfred

    2014-01-01

    We propose a method for the simultaneous construction of multiple image segmentations by combining a recently proposed “convolution of mixtures of Gaussians” model with a multi-layer hidden Markov random field structure. The resulting method constructs for a single image several, alternative...... segmentations that capture different structural elements of the image. We also apply the method to collections of images with identical pixel dimensions, which we call image stacks. Here it turns out that the method is able to both identify groups of similar images in the stack, and to provide segmentations...

  7. Lightweight Radiator Fins for Space Nuclear Power, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This SBIR Phase 1 project shall investigate concept radiator fins that incorporate novel carbon materials for improved performance of segmented high temperature...

  8. 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.

  9. Using expected localization in segmentation

    Science.gov (United States)

    Shemlon, Stephen; Cho, Kyugon; Dunn, Stanley M.

    1992-02-01

    Segmentation paradigms are based on manipulating some distinguishing characteristic of the various objects that are present in the image being analyzed. These characteristics are often well known for given objects in a given class of images. The intelligent use of this knowledge can simplify the segmentation process without necessarily targeting it for a particular class of images. This paper outlines a segmentation paradigm that uses models which characterize the expected presentation of possible image objects. It explains how knowledge of the expected localization of certain objects can be used to refine the segmentation process, to optimize object extraction and identification, and to learn some invariant characteristics of the objects and their surroundings, for use by high level intelligent processes. We present results of experiments with MRI human brain scans, dental radiographs, and transmission electron microscope (TEM) serial sections of hemocytes (insect blood cells).

  10. Allegheny County Addressing Segment Aliases

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — This table contains the segment aliases for roads in Allegheny County that may have an alternate street nameIf viewing this description on the Western Pennsylvania...

  11. Co-Segmentation Guided Hough Transform for Robust Feature Matching.

    Science.gov (United States)

    Chen, Hsin-Yi; Lin, Yen-Yu; Chen, Bing-Yu

    2015-12-01

    We present an algorithm that integrates image co-segmentation into feature matching, and can robustly yield accurate and dense feature correspondences. Inspired by the fact that correct feature correspondences on the same object typically have coherent transformations, we cast the task of feature matching as a density estimation problem in the homography space. Specifically, we project the homographies of correspondence candidates into the parametric Hough space, in which geometric verification of correspondences can be activated by voting. The precision of matching is then boosted. On the other hand, we leverage image co-segmentation, which discovers object boundaries, to determine relevant voters and speed up Hough voting. In addition, correspondence enrichment can be achieved by inferring the concerted homographies that are propagated between the features within the same segments. The recall is hence increased. In our approach, feature matching and image co-segmentation are tightly coupled. Through an iterative optimization process, more and more correct correspondences are detected owing to object boundaries revealed by co-segmentation. The proposed approach is comprehensively evaluated. Promising experimental results on four datasets manifest its effectiveness.

  12. IRIS: Intelligent Roadway Image Segmentation

    OpenAIRE

    Brown, Ryan Charles

    2014-01-01

    The problem of roadway navigation and obstacle avoidance for unmanned ground vehicles has typically needed very expensive sensing to operate properly. To reduce the cost of sensing, it is proposed that an algorithm be developed that uses a single visual camera to image the roadway, determine where the lane of travel is in the image, and segment that lane. The algorithm would need to be as accurate as current lane finding algorithms as well as faster than a standard k- means segmentation acros...

  13. Market segmentation, targeting and positioning

    OpenAIRE

    Camilleri, Mark Anthony

    2017-01-01

    Businesses may not be in a position to satisfy all of their customers, every time. It may prove difficult to meet the exact requirements of each individual customer. People do not have identical preferences, so rarely does one product completely satisfy everyone. Many companies may usually adopt a strategy that is known as target marketing. This strategy involves dividing the market into segments and developing products or services to these segments. A target marketing strategy is focused on ...

  14. Recognition Using Classification and Segmentation Scoring

    National Research Council Canada - National Science Library

    Kimball, Owen; Ostendorf, Mari; Rohlicek, Robin

    1992-01-01

    .... We describe an approach to connected word recognition that allows the use of segmental information through an explicit decomposition of the recognition criterion into classification and segmentation scoring...

  15. Disjunctive Normal Parametric Level Set With Application to Image Segmentation.

    Science.gov (United States)

    Mesadi, Fitsum; Cetin, Mujdat; Tasdizen, Tolga

    2017-06-01

    Level set methods are widely used for image segmentation because of their convenient shape representation for numerical computations and capability to handle topological changes. However, in spite of the numerous works in the literature, the use of level set methods in image segmentation still has several drawbacks. These shortcomings include formation of irregularities of the signed distance function, sensitivity to initialization, lack of locality, and expensive computational cost, which increases dramatically as the number of objects to be simultaneously segmented grows. In this paper, we propose a novel parametric level set method called disjunctive normal level set (DNLS), and apply it to both two-phase (single object) and multiphase (multiobject) image segmentations. DNLS is a differentiable model formed by the union of polytopes, which themselves are created by intersections of half-spaces. We formulate the segmentation algorithm in a Bayesian framework and use a variational approach to minimize the energy with respect to the parameters of the model. The proposed DNLS can be considered as an open framework that allows the use of different appearance models and shape priors. Compared with the conventional level sets available in the literature, the proposed DNLS has the following major advantages: it requires significantly less computational time and memory, it naturally keeps the level set function regular during the evolution, it is more suitable for multiphase and local region-based image segmentations, and it is less sensitive to noise and initialization. The experimental results show the potential of the proposed method.

  16. 10^3 Segment MEMS Deformable-Mirror Process Development, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Iris AO will extend its proven segmented MEMS deformable mirror architecture to large array sizes required for high-contrast astrophysical imagers. Current...

  17. Segmentation of endpoint trajectories does not imply segmented control.

    Science.gov (United States)

    Sternad, D; Schaal, S

    1999-01-01

    While it is generally assumed that complex movements consist of a sequence of simpler units, the quest to define these units of action, or movement primitives, remains an open question. In this context, two hypotheses of movement segmentation of endpoint trajectories in three-dimensional human drawing movements are reexamined: (1) the stroke-based segmentation hypothesis based on the results that the proportionality coefficient of the two-thirds power law changes discontinuously with each new "stroke," and (2) the segmentation hypothesis inferred from the observation of piecewise planar endpoint trajectories of three-dimensional drawing movements. In two experiments human subjects performed a set of elliptical and figure eight patterns of different sizes and orientations using their whole arm in three dimensions. The kinematic characteristics of the endpoint trajectories and the seven joint angles of the arm were analyzed. While the endpoint trajectories produced similar segmentation features to those reported in the literature, analyses of the joint angles show no obvious segmentation but rather continuous oscillatory patterns. By approximating the joint angle data of human subjects with sinusoidal trajectories, and by implementing this model on a 7-degree-of-freedom (DOF) anthropomorphic robot arm, it is shown that such a continuous movement strategy can produce exactly the same features as observed by the above segmentation hypotheses. The origin of this apparent segmentation of endpoint trajectories is traced back to the nonlinear transformations of the forward kinematics of human arms. The presented results demonstrate that principles of discrete movement generation may not be reconciled with those of rhythmic movement as easily as has been previously suggested, while the generalization of nonlinear pattern generators to arm movements can offer an interesting alternative to approach the question of units of action.

  18. An overview of the GOES-R ground segment architecture

    Science.gov (United States)

    Hansen, Dennis; Bristow, John; Kalluri, Satya; Weiner, Allan; Dittberner, Gerald

    2010-08-01

    The next generation of NOAA's Geostationary Operational Environmental Satellite system, Series R (GOES-R) provides continuity of the GOES mission and improvement of its remotely-sensed environmental data. The GOES-R system consists of the Space and Ground Segments. The Space Segment consists of spacecraft bus, its remote-sensing instruments, and communications payloads; while the Ground Segment consists of all Earth-based functions, provides satellite operations and instrument product generation and distribution. This paper presents an overview of the GOES-R Ground Segment (GS) architecture as it continues to evolve consistent with the GOES-R Ground Segment Project (GSP) approved requirements documents. The GOES-R Ground Segment operates from three sites. The first is the NOAA Satellite Operations Facility (NSOF) in Suitland, MD which houses the primary Mission Management (MM), and selected Enterprise Management (EM), Product Generation (PG), and Product Distribution (PD) functions. The Wallops Command and Data Acquisition Station (WCDAS), located in Wallops, VA, provides the primary space communications services, EM and MM functions, and selected PG and PD functions. The third site is a geographically diverse remote backup facility (RBU) located at Fairmont, WV. The architecture has been developed to allow integrated operation within a geographically distributed framework. Because of the unique configuration of the Mission Management Element, the Wallops Command and Data Acquisition Site will have the ability to assume control of satellite operations in the event of an emergency - when authorized by the primary NSOF controllers. This concept allows the Enterprise Management element to have available a wide range of capabilities governed by operations policy rather than the need for system upgrades. This concept also provides flexibility for addition and deletion of modules for major functions. The use of Service Based Architecture concepts within the Product

  19. Kidney segmentation in CT sequences using SKFCM and improved GrowCut algorithm.

    Science.gov (United States)

    Song, Hong; Kang, Wei; Zhang, Qian; Wang, Shuliang

    2015-01-01

    Organ segmentation is an important step in computer-aided diagnosis and pathology detection. Accurate kidney segmentation in abdominal computed tomography (CT) sequences is an essential and crucial task for surgical planning and navigation in kidney tumor ablation. However, kidney segmentation in CT is a substantially challenging work because the intensity values of kidney parenchyma are similar to those of adjacent structures. In this paper, a coarse-to-fine method was applied to segment kidney from CT images, which consists two stages including rough segmentation and refined segmentation. The rough segmentation is based on a kernel fuzzy C-means algorithm with spatial information (SKFCM) algorithm and the refined segmentation is implemented with improved GrowCut (IGC) algorithm. The SKFCM algorithm introduces a kernel function and spatial constraint into fuzzy c-means clustering (FCM) algorithm. The IGC algorithm makes good use of the continuity of CT sequences in space which can automatically generate the seed labels and improve the efficiency of segmentation. The experimental results performed on the whole dataset of abdominal CT images have shown that the proposed method is accurate and efficient. The method provides a sensitivity of 95.46% with specificity of 99.82% and performs better than other related methods. Our method achieves high accuracy in kidney segmentation and considerably reduces the time and labor required for contour delineation. In addition, the method can be expanded to 3D segmentation directly without modification.

  20. Image Segmentation, Registration, Compression, and Matching

    Science.gov (United States)

    Yadegar, Jacob; Wei, Hai; Yadegar, Joseph; Ray, Nilanjan; Zabuawala, Sakina

    2011-01-01

    A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity

  1. Fast CEUS image segmentation based on self organizing maps

    Science.gov (United States)

    Paire, Julie; Sauvage, Vincent; Albouy-Kissi, Adelaïde; Ladam Marcus, Viviane; Marcus, Claude; Hoeffel, Christine

    2014-03-01

    Contrast-enhanced ultrasound (CEUS) has recently become an important technology for lesion detection and characterization. CEUS is used to investigate the perfusion kinetics in tissue over time, which relates to tissue vascularization. In this paper, we present an interactive segmentation method based on the neural networks, which enables to segment malignant tissue over CEUS sequences. We use Self-Organizing-Maps (SOM), an unsupervised neural network, to project high dimensional data to low dimensional space, named a map of neurons. The algorithm gathers the observations in clusters, respecting the topology of the observations space. This means that a notion of neighborhood between classes is defined. Adjacent observations in variables space belong to the same class or related classes after classification. Thanks to this neighborhood conservation property and associated with suitable feature extraction, this map provides user friendly segmentation tool. It will assist the expert in tumor segmentation with fast and easy intervention. We implement SOM on a Graphics Processing Unit (GPU) to accelerate treatment. This allows a greater number of iterations and the learning process to converge more precisely. We get a better quality of learning so a better classification. Our approach allows us to identify and delineate lesions accurately. Our results show that this method improves markedly the recognition of liver lesions and opens the way for future precise quantification of contrast enhancement.

  2. 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.

  3. Periodic sequence of stabilized wave segments in an excitable medium

    Science.gov (United States)

    Zykov, V. S.; Bodenschatz, E.

    2018-03-01

    Numerical computations show that a stabilization of a periodic sequence of wave segments propagating through an excitable medium is possible only in a restricted domain within the parameter space. By application of a free-boundary approach, we demonstrate that at the boundary of this domain the parameter H introduced in our Rapid Communication is constant. We show also that the discovered parameter predetermines the propagation velocity and the shape of the wave segments. The predictions of the free-boundary approach are in good quantitative agreement with results from numerical reaction-diffusion simulations performed on the modified FitzHugh-Nagumo model.

  4. Development of the WDS Russian-Ukrainian Segment

    Directory of Open Access Journals (Sweden)

    Marsel Shaimardanov

    2013-01-01

    Full Text Available Establishment of the Russian-Ukrainian WDS Segment and its state of the art, main priorities and research activities are described. One of the high priority tasks for Segment members is development of a common information space - transition from Legacy Systems and individual services to a common, globally interoperable, distributed data system that incorporates emerging technologies and new scientific data activities. The new system will build on the potential and added value offered by advanced interconnections between data management and data processing components for disciplinary and multidisciplinary applications. Thus, the principles of the architectural organization of intelligent data processing systems are discussed in this paper.

  5. CUDA Accelerated Multi-domain Volumetric Image Segmentation and Using a Higher Order Level Set Method

    DEFF Research Database (Denmark)

    Sharma, Ojaswa; Anton, François; Zhang, Qin

    2009-01-01

    In this paper we present a methodology for smooth surface segmentation (partition) of volumetric images using higher order level set scheme. The segmentation allows for a multi-domain partitioning by minimizing modi-fied Mumford-Shah functional. Since, volumetric images tend to be de......-manding in terms of computation and memory space, we employ a CUDA based fast GPU segmentation and provide accuracy measures compared with an equivalent CPU implementation. Our resulting surfaces are C2-smooth resulting from tri-cubic spline interpolation algorithm. We also provide error bounds...... on the reconstruction/segmentation....

  6. 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

  7. 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.

  8. Segmentation by Large Scale Hypothesis Testing - Segmentation as Outlier Detection

    DEFF Research Database (Denmark)

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

    2010-01-01

    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...

  9. The posterior segment of the temporomandibular joint capsule and its anatomic relationship.

    Science.gov (United States)

    Mérida-Velasco, J Ramón; Rodríguez, J Francisco; de la Cuadra, Crótida; Peces, M Dolores; Mérida, J Antonio; Sánchez, Indalecio

    2007-01-01

    The aim of this work was to clarify the arrangement of the posterior segment of the temporomandibular joint capsule and its pertinent relationships. The temporomandibular region was dissected bilaterally in 20 adult cadavers. Natural stained latex was injected into 16 cadavers through the external carotid artery to facilitate the dissection of the arterial vessels. The posterior segment of the joint capsule is made up of the so-called "bilaminar zone" of the articular disc. The upper internal portion of the posterior segment of the capsule was reinforced by the discomalleolar ligament. The retroarticular space was filled with loose connective tissue and the anterior branches of the anterior tympanic artery were distributed throughout the posterior segment of the joint capsule. The posterior segment of the temporomandibular joint capsule corresponds to the bilaminar zone of the articular disc. The structures of the retroarticular space are extracapsular.

  10. Shape-tailored local descriptors and their application to segmentation and tracking

    KAUST Repository

    Khan, Naeemullah

    2015-06-07

    We propose new dense descriptors for texture segmentation. Given a region of arbitrary shape in an image, these descriptors are formed from shape-dependent scale spaces of oriented gradients. These scale spaces are defined by Poisson-like partial differential equations. A key property of our new descriptors is that they do not aggregate image data across the boundary of the region, in contrast to existing descriptors based on aggregation of oriented gradients. As an example, we show how the descriptor can be incorporated in a Mumford-Shah energy for texture segmentation. We test our method on several challenging datasets for texture segmentation and textured object tracking. Experiments indicate that our descriptors lead to more accurate segmentation than non-shape dependent descriptors and the state-of-the-art in texture segmentation.

  11. An interactive segmentation method based on superpixel

    DEFF Research Database (Denmark)

    Yang, Shu; Zhu, Yaping; Wu, Xiaoyu

    2015-01-01

    This paper proposes an interactive image-segmentation method which is based on superpixel. To achieve fast segmentation, the method is used to establish a Graphcut model using superpixels as nodes, and a new energy function is proposed. Experimental results demonstrate that the authors' method has...... excellent performance in terms of segmentation accuracy and computation efficiency compared with other segmentation algorithm based on pixels....

  12. Segmentation models diversity for object proposals

    NARCIS (Netherlands)

    Manfredi, M.; Grana, C.; Cucchiara, R.; Smeulders, A.W.M.

    In this paper we present a segmentation proposal method which employs a box-hypotheses generation step followed by a lightweight segmentation strategy. Inspired by interactive segmentation, for each automatically placed bounding-box we compute a precise segmentation mask. We introduce diversity in

  13. 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.

  14. Liver segmentation: indications, techniques and future directions.

    Science.gov (United States)

    Gotra, Akshat; Sivakumaran, Lojan; Chartrand, Gabriel; Vu, Kim-Nhien; Vandenbroucke-Menu, Franck; Kauffmann, Claude; Kadoury, Samuel; Gallix, Benoît; de Guise, Jacques A; Tang, An

    2017-08-01

    Liver volumetry has emerged as an important tool in clinical practice. Liver volume is assessed primarily via organ segmentation of computed tomography (CT) and magnetic resonance imaging (MRI) images. The goal of this paper is to provide an accessible overview of liver segmentation targeted at radiologists and other healthcare professionals. Using images from CT and MRI, this paper reviews the indications for liver segmentation, technical approaches used in segmentation software and the developing roles of liver segmentation in clinical practice. Liver segmentation for volumetric assessment is indicated prior to major hepatectomy, portal vein embolisation, associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) and transplant. Segmentation software can be categorised according to amount of user input involved: manual, semi-automated and fully automated. Manual segmentation is considered the "gold standard" in clinical practice and research, but is tedious and time-consuming. Increasingly automated segmentation approaches are more robust, but may suffer from certain segmentation pitfalls. Emerging applications of segmentation include surgical planning and integration with MRI-based biomarkers. Liver segmentation has multiple clinical applications and is expanding in scope. Clinicians can employ semi-automated or fully automated segmentation options to more efficiently integrate volumetry into clinical practice. • Liver volume is assessed via organ segmentation on CT and MRI examinations. • Liver segmentation is used for volume assessment prior to major hepatic procedures. • Segmentation approaches may be categorised according to the amount of user input involved. • Emerging applications include surgical planning and integration with MRI-based biomarkers.

  15. Discourse segmentation and ambiguity in discourse structure

    NARCIS (Netherlands)

    Hoek, J.; Evers-Vermeul, J.; Sanders, T.J.M.

    2016-01-01

    Discourse relations hold between two or more text segments. The process of discourse annotation not only involves determining what type of relation holds between segments, but also indicating the segments themselves. Often, segmentation and annotation are treated as individual steps, and separate

  16. Image Information Mining Utilizing Hierarchical Segmentation

    Science.gov (United States)

    Tilton, James C.; Marchisio, Giovanni; Koperski, Krzysztof; Datcu, Mihai

    2002-01-01

    The Hierarchical Segmentation (HSEG) algorithm is an approach for producing high quality, hierarchically related image segmentations. The VisiMine image information mining system utilizes clustering and segmentation algorithms for reducing visual information in multispectral images to a manageable size. The project discussed herein seeks to enhance the VisiMine system through incorporating hierarchical segmentations from HSEG into the VisiMine system.

  17. [Evaluation of Image Quality of Readout Segmented EPI with Readout Partial Fourier Technique].

    Science.gov (United States)

    Yoshimura, Yuuki; Suzuki, Daisuke; Miyahara, Kanae

    Readout segmented EPI (readout segmentation of long variable echo-trains: RESOLVE) segmented k-space in the readout direction. By using the partial Fourier method in the readout direction, the imaging time was shortened. However, the influence on image quality due to insufficient data sampling is concerned. The setting of the partial Fourier method in the readout direction in each segment was changed. Then, we examined signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and distortion ratio for changes in image quality due to differences in data sampling. As the number of sampling segments decreased, SNR and CNR showed a low value. In addition, the distortion ratio did not change. The image quality of minimum sampling segments is greatly different from full data sampling, and caution is required when using it.

  18. Chinese license plate character segmentation using multiscale template matching

    Science.gov (United States)

    Tian, Jiangmin; Wang, Guoyou; Liu, Jianguo; Xia, Yuanchun

    2016-09-01

    Character segmentation (CS) plays an important role in automatic license plate recognition and has been studied for decades. A method using multiscale template matching is proposed to settle the problem of CS for Chinese license plates. It is carried out on a binary image integrated from maximally stable extremal region detection and Otsu thresholding. Afterward, a uniform harrow-shaped template with variable length is designed, by virtue of which a three-dimensional matching space is constructed for searching of candidate segmentations. These segmentations are detected at matches with local minimum responses. Finally, the vertical boundaries of each single character are located for subsequent recognition. Experiments on a data set including 2349 license plate images of different quality levels show that the proposed method can achieve a higher accuracy at comparable time cost and is robust to images in poor conditions.

  19. Segmented Aperture Interferometric Nulling Testbed (SAINT) II: component systems update

    Science.gov (United States)

    Hicks, Brian A.; Bolcar, Matthew R.; Helmbrecht, Michael A.; Petrone, Peter; Burke, Elliot; Corsetti, James; Dillon, Thomas; Lea, Andrew; Pellicori, Samuel; Sheets, Teresa; Shiri, Ron; Agolli, Jack; DeVries, John; Eberhardt, Andrew; McCabe, Tyler

    2017-09-01

    This work presents updates to the coronagraph and telescope components of the Segmented Aperture Interferometric Nulling Testbed (SAINT). The project pairs an actively-controlled macro-scale segmented mirror with the Visible Nulling Coronagraph (VNC) towards demonstrating capabilities for the future space observatories needed to directly detect and characterize a significant sample of Earth-sized worlds around nearby stars in the quest for identifying those which may be habitable and possibly harbor life. Efforts to improve the VNC wavefront control optics and mechanisms towards repeating narrowband results are described. A narrative is provided for the design of new optical components aimed at enabling broadband performance. Initial work with the hardware and software interface for controlling the segmented telescope mirror is also presented.

  20. Automated segmentation of pigmented skin lesions in multispectral imaging

    International Nuclear Information System (INIS)

    Carrara, Mauro; Tomatis, Stefano; Bono, Aldo; Bartoli, Cesare; Moglia, Daniele; Lualdi, Manuela; Colombo, Ambrogio; Santinami, Mario; Marchesini, Renato

    2005-01-01

    The aim of this study was to develop an algorithm for the automatic segmentation of multispectral images of pigmented skin lesions. The study involved 1700 patients with 1856 cutaneous pigmented lesions, which were analysed in vivo by a novel spectrophotometric system, before excision. The system is able to acquire a set of 15 different multispectral images at equally spaced wavelengths between 483 and 951 nm. An original segmentation algorithm was developed and applied to the whole set of lesions and was able to automatically contour them all. The obtained lesion boundaries were shown to two expert clinicians, who, independently, rejected 54 of them. The 97.1% contour accuracy indicates that the developed algorithm could be a helpful and effective instrument for the automatic segmentation of skin pigmented lesions. (note)

  1. A Novel Iris Segmentation Scheme

    Directory of Open Access Journals (Sweden)

    Chen-Chung Liu

    2014-01-01

    Full Text Available One of the key steps in the iris recognition system is the accurate iris segmentation from its surrounding noises including pupil, sclera, eyelashes, and eyebrows of a captured eye-image. This paper presents a novel iris segmentation scheme which utilizes the orientation matching transform to outline the outer and inner iris boundaries initially. It then employs Delogne-Kåsa circle fitting (instead of the traditional Hough transform to further eliminate the outlier points to extract a more precise iris area from an eye-image. In the extracted iris region, the proposed scheme further utilizes the differences in the intensity and positional characteristics of the iris, eyelid, and eyelashes to detect and delete these noises. The scheme is then applied on iris image database, UBIRIS.v1. The experimental results show that the presented scheme provides a more effective and efficient iris segmentation than other conventional methods.

  2. Object Recognition and Segmentation of Wounds

    OpenAIRE

    Wåsjø, Robin

    2015-01-01

    Object recognition and segmentation of objects is a complex task. Our goal is to develop an algorithm that can recognize and segment wound objects in images. We attempt to solve the object recognition and segmentation problem by using a hypothesis optimization framework. This method optimizes the object segmentation by assigning objective function values to the object segmentation hypotheses. The optimization algorithm is a genetic algorithm. The objective function relies on textural and shap...

  3. Optimally segmented permanent magnet structures

    DEFF Research Database (Denmark)

    Insinga, Andrea Roberto; Bjørk, Rasmus; Smith, Anders

    2016-01-01

    We present an optimization approach which can be employed to calculate the globally optimal segmentation of a two-dimensional magnetic system into uniformly magnetized pieces. For each segment the algorithm calculates the optimal shape and the optimal direction of the remanent flux density vector......, with respect to a linear objective functional. We illustrate the approach with results for magnet design problems from different areas, such as a permanent magnet electric motor, a beam focusing quadrupole magnet for particle accelerators and a rotary device for magnetic refrigeration....

  4. Advanced composite materials for precision segmented reflectors

    Science.gov (United States)

    Stein, Bland A.; Bowles, David E.

    1988-01-01

    The objective in the NASA Precision Segmented Reflector (PSR) project is to develop new composite material concepts for highly stable and durable reflectors with precision surfaces. The project focuses on alternate material concepts such as the development of new low coefficient of thermal expansion resins as matrices for graphite fiber reinforced composites, quartz fiber reinforced epoxies, and graphite reinforced glass. Low residual stress fabrication methods will be developed. When coupon specimens of these new material concepts have demonstrated the required surface accuracies and resistance to thermal distortion and microcracking, reflector panels will be fabricated and tested in simulated space environments. An important part of the program is the analytical modeling of environmental stability of these new composite materials concepts through constitutive equation development, modeling of microdamage in the composite matrix, and prediction of long term stability (including viscoelasticity). These analyses include both closed form and finite element solutions at the micro and macro levels.

  5. Deep Learning on Sparse Manifolds for Faster Object Segmentation.

    Science.gov (United States)

    Nascimento, Jacinto C; Carneiro, Gustavo

    2017-07-11

    We propose a new combination of deep belief networks and sparse manifold learning strategies for the 2D segmentation of non-rigid visual objects. With this novel combination, we aim to reduce the training and inference complexities while maintaining the accuracy of machine learning based non-rigid segmentation methodologies. Typical non-rigid object segmentation methodologies divide the problem into a rigid detection followed by a non-rigid segmentation, where the low dimensionality of the rigid detection allows for a robust training (i.e., a training that does not require a vast amount of annotated images to estimate robust appearance and shape models) and a fast search process during inference. Therefore, it is desirable that the dimensionality of this rigid transformation space is as small as possible in order to enhance the advantages brought by the aforementioned division of the problem. In this paper, we propose the use of sparse manifolds to reduce the dimensionality of the rigid detection space. Furthermore, we propose the use of deep belief networks to allow for a training process that can produce robust appearance models without the need of large annotated training sets. We test our approach in the segmentation of the left ventricle of the heart from ultrasound images and lips from frontal face images. Our experiments show that the use of sparse manifolds and deep belief networks for the rigid detection stage leads to segmentation results that are as accurate as the current state of the art, but with lower search complexity and training processes that require a small amount of annotated training data.

  6. Supervised learning-based cell image segmentation for p53 immunohistochemistry.

    Science.gov (United States)

    Mao, K Z; Zhao, Peng; Tan, Puay-Hoon

    2006-06-01

    In this paper, we present two new algorithms for cell image segmentation. First, we demonstrate that pixel classification-based color image segmentation in color space is equivalent to performing segmentation on grayscale image through thresholding. Based on this result, we develop a supervised learning-based two-step procedure for color cell image segmentation, where color image is first mapped to grayscale via a transform learned through supervised learning, thresholding is then performed on the grayscale image to segment objects out of background. Experimental results show that the supervised learning-based two-step procedure achieved a boundary disagreement (mean absolute distance) of 0.85 while the disagreement produced by the pixel classification-based color image segmentation method is 3.59. Second, we develop a new marker detection algorithm for watershed-based separation of overlapping or touching cells. The merit of the new algorithm is that it employs both photometric and shape information and combines the two naturally in the framework of pattern classification to provide more reliable markers. Extensive experiments show that the new marker detection algorithm achieved 0.4% and 0.2% over-segmentation and under-segmentation, respectively, while reconstruction-based method produced 4.4% and 1.1% over-segmentation and under-segmentation, respectively.

  7. 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

  8. 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.

  9. 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.

  10. Essays in Space Science

    International Nuclear Information System (INIS)

    Ramaty, R.; Cline, T.L.; Ormes, J.F.

    1987-06-01

    The papers presented cover a broad segment of space research and are an acknowledgement of the personal involvement of Frank McDonald in many of these efforts. The totality of the papers were chosen so as to sample the scientific areas influenced by him in a significant manner. Three broad areas are covered: particles and fields of the solar system; cosmic ray astrophysics; and gamma ray, x ray, and infrared astronomics

  11. Segmentation strategies for the irradiated and tritium contaminated PPPL TFTR

    Energy Technology Data Exchange (ETDEWEB)

    Walton, G.R. [Princeton Univ., NJ (United States). Plasma Physics Lab.; Litka, T.J. [Advanced Consulting Group, Inc., Chicago, IL (United States); Spampinato, P.T. [RHD Consultants, Inc., Princeton, NJ (United States)

    1995-02-09

    The Tokamak Fusion Test Reactor (TFTR) at Princeton Plasma Physics Laboratory is scheduled to complete its final experiments in the Fall of 1995. As a result, the TFTR will be activated and tritium contaminated. After the experiments are complete, the TFTR will undergo Shutdown and Removal (S and R). The space vacated by the TFTR will be used for a new test reactor, the Tokamak Physics Experiment (TPX). Remote methods may be required to remove components and to segment the Vacuum Vessel. The TFTR has been studied to determine alternatives for the segmentation of the Vacuum Vessel from the inside (In-Vessel). The methodology to determine suitable strategies to segment the Vacuum Vessel from In-Vessel included several areas of concentration. These areas were segmentation locations, cutting/removal technologies, pros and cons, and cutting/removal technology delivery systems. The segmentation locations for easiest implementation and minimal steps in cutting and removal have been identified. Each of these will also achieve the baseline for packaging and shipment. The methods for cutting and removal of components were determined. In addition, the delivery systems were conceptualized.

  12. Segmentation strategies for the irradiated and tritium contaminated PPPL TFTR

    International Nuclear Information System (INIS)

    Walton, G.R.; Spampinato, P.T.

    1995-01-01

    The Tokamak Fusion Test Reactor (TFTR) at Princeton Plasma Physics Laboratory is scheduled to complete its final experiments in the Fall of 1995. As a result, the TFTR will be activated and tritium contaminated. After the experiments are complete, the TFTR will undergo Shutdown and Removal (S and R). The space vacated by the TFTR will be used for a new test reactor, the Tokamak Physics Experiment (TPX). Remote methods may be required to remove components and to segment the Vacuum Vessel. The TFTR has been studied to determine alternatives for the segmentation of the Vacuum Vessel from the inside (In-Vessel). The methodology to determine suitable strategies to segment the Vacuum Vessel from In-Vessel included several areas of concentration. These areas were segmentation locations, cutting/removal technologies, pros and cons, and cutting/removal technology delivery systems. The segmentation locations for easiest implementation and minimal steps in cutting and removal have been identified. Each of these will also achieve the baseline for packaging and shipment. The methods for cutting and removal of components were determined. In addition, the delivery systems were conceptualized

  13. Human-Like Room Segmentation for Domestic Cleaning Robots

    Directory of Open Access Journals (Sweden)

    David Fleer

    2017-11-01

    Full Text Available Autonomous mobile robots have recently become a popular solution for automating cleaning tasks. In one application, the robot cleans a floor space by traversing and covering it completely. While fulfilling its task, such a robot may create a map of its surroundings. For domestic indoor environments, these maps often consist of rooms connected by passageways. Segmenting the map into these rooms has several uses, such as hierarchical planning of cleaning runs by the robot, or the definition of cleaning plans by the user. Especially in the latter application, the robot-generated room segmentation should match the human understanding of rooms. Here, we present a novel method that solves this problem for the graph of a topo-metric map: first, a classifier identifies those graph edges that cross a border between rooms. This classifier utilizes data from multiple robot sensors, such as obstacle measurements and camera images. Next, we attempt to segment the map at these room–border edges using graph clustering. By training the classifier on user-annotated data, this produces a human-like room segmentation. We optimize and test our method on numerous realistic maps generated by our cleaning-robot prototype and its simulated version. Overall, we find that our method produces more human-like room segmentations compared to mere graph clustering. However, unusual room borders that differ from the training data remain a challenge.

  14. Segmental Colitis Complicating Diverticular Disease

    Directory of Open Access Journals (Sweden)

    Guido Ma Van Rosendaal

    1996-01-01

    Full Text Available Two cases of idiopathic colitis affecting the sigmoid colon in elderly patients with underlying diverticulosis are presented. Segmental resection has permitted close review of the histopathology in this syndrome which demonstrates considerable similarity to changes seen in idiopathic ulcerative colitis. The reported experience with this syndrome and its clinical features are reviewed.

  15. Increasing Enrollment through Benefit Segmentation.

    Science.gov (United States)

    Goodnow, Betty

    1982-01-01

    The applicability of benefit segmentation, a market research technique which groups people according to benefits expected from a program offering, was tested at the College of DuPage. Preferences and demographic characteristics were analyzed and program improvements adopted, increasing enrollment by 20 percent. (Author/SK)

  16. Segmenting Trajectories by Movement States

    NARCIS (Netherlands)

    Buchin, M.; Kruckenberg, H.; Kölzsch, A.; Timpf, S.; Laube, P.

    2013-01-01

    Dividing movement trajectories according to different movement states of animals has become a challenge in movement ecology, as well as in algorithm development. In this study, we revisit and extend a framework for trajectory segmentation based on spatio-temporal criteria for this purpose. We adapt

  17. Dictionary Based Segmentation in Volumes

    DEFF Research Database (Denmark)

    Emerson, Monica Jane; Jespersen, Kristine Munk; Jørgensen, Peter Stanley

    Method for supervised segmentation of volumetric data. The method is trained from manual annotations, and these annotations make the method very flexible, which we demonstrate in our experiments. Our method infers label information locally by matching the pattern in a neighborhood around a voxel ...... to a dictionary, and hereby accounts for the volume texture....

  18. Leaf segmentation in plant phenotyping

    NARCIS (Netherlands)

    Scharr, Hanno; Minervini, Massimo; French, Andrew P.; Klukas, Christian; Kramer, David M.; Liu, Xiaoming; Luengo, Imanol; Pape, Jean Michel; Polder, Gerrit; Vukadinovic, Danijela; Yin, Xi; Tsaftaris, Sotirios A.

    2016-01-01

    Image-based plant phenotyping is a growing application area of computer vision in agriculture. A key task is the segmentation of all individual leaves in images. Here we focus on the most common rosette model plants, Arabidopsis and young tobacco. Although leaves do share appearance and shape

  19. Clavicle segmentation in chest radiographs

    NARCIS (Netherlands)

    Hogeweg, L.E.; Sanchez, C.I.; Jong, P.A. de; Maduskar, P.; Ginneken, B. van

    2012-01-01

    Automated delineation of anatomical structures in chest radiographs is difficult due to superimposition of multiple structures. In this work an automated technique to segment the clavicles in posterior-anterior chest radiographs is presented in which three methods are combined. Pixel classification

  20. 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.

  1. Metric Learning to Enhance Hyperspectral Image Segmentation

    Science.gov (United States)

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

    2013-01-01

    Unsupervised hyperspectral image segmentation can reveal spatial trends that show the physical structure of the scene to an analyst. They highlight borders and reveal areas of homogeneity and change. Segmentations are independently helpful for object recognition, and assist with automated production of symbolic maps. Additionally, a good segmentation can dramatically reduce the number of effective spectra in an image, enabling analyses that would otherwise be computationally prohibitive. Specifically, using an over-segmentation of the image instead of individual pixels can reduce noise and potentially improve the results of statistical post-analysis. In this innovation, a metric learning approach is presented to improve the performance of unsupervised hyperspectral image segmentation. The prototype demonstrations attempt a superpixel segmentation in which the image is conservatively over-segmented; that is, the single surface features may be split into multiple segments, but each individual segment, or superpixel, is ensured to have homogenous mineralogy.

  2. Competition between influenza A virus genome segments.

    Directory of Open Access Journals (Sweden)

    Ivy Widjaja

    Full Text Available Influenza A virus (IAV contains a segmented negative-strand RNA genome. How IAV balances the replication and transcription of its multiple genome segments is not understood. We developed a dual competition assay based on the co-transfection of firefly or Gaussia luciferase-encoding genome segments together with plasmids encoding IAV polymerase subunits and nucleoprotein. At limiting amounts of polymerase subunits, expression of the firefly luciferase segment was negatively affected by the presence of its Gaussia luciferase counterpart, indicative of competition between reporter genome segments. This competition could be relieved by increasing or decreasing the relative amounts of firefly or Gaussia reporter segment, respectively. The balance between the luciferase expression levels was also affected by the identity of the untranslated regions (UTRs as well as segment length. In general it appeared that genome segments displaying inherent higher expression levels were more efficient competitors of another segment. When natural genome segments were tested for their ability to suppress reporter gene expression, shorter genome segments generally reduced firefly luciferase expression to a larger extent, with the M and NS segments having the largest effect. The balance between different reporter segments was most dramatically affected by the introduction of UTR panhandle-stabilizing mutations. Furthermore, only reporter genome segments carrying these mutations were able to efficiently compete with the natural genome segments in infected cells. Our data indicate that IAV genome segments compete for available polymerases. Competition is affected by segment length, coding region, and UTRs. This competition is probably most apparent early during infection, when limiting amounts of polymerases are present, and may contribute to the regulation of segment-specific replication and transcription.

  3. Dual-circuit segmented rail phased induction motor

    Science.gov (United States)

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

    2002-01-01

    An improved linear motor utilizes two circuits, rather that one circuit and an opposed plate, to gain efficiency. The powered circuit is a flat conductive coil. The opposed segmented rail circuit is either a plurality of similar conductive coils that are shorted, or a plurality of ladders formed of opposed conductive bars connected by a plurality of spaced conductors. In each embodiment, the conductors are preferably cables formed from a plurality of intertwined insulated wires to carry current evenly.

  4. Retinal Vessel Segmentation via Structure Tensor Coloring and Anisotropy Enhancement

    Directory of Open Access Journals (Sweden)

    Mehmet Nergiz

    2017-11-01

    Full Text Available Retinal vessel segmentation is one of the preliminary tasks for developing diagnosis software systems related to various retinal diseases. In this study, a fully automated vessel segmentation system is proposed. Firstly, the vessels are enhanced using a Frangi Filter. Afterwards, Structure Tensor is applied to the response of the Frangi Filter and a 4-D tensor field is obtained. After decomposing the Eigenvalues of the tensor field, the anisotropy between the principal Eigenvalues are enhanced exponentially. Furthermore, this 4-D tensor field is converted to the 3-D space which is composed of energy, anisotropy and orientation and then a Contrast Limited Adaptive Histogram Equalization algorithm is applied to the energy space. Later, the obtained energy space is multiplied by the enhanced mean surface curvature of itself and the modified 3-D space is converted back to the 4-D tensor field. Lastly, the vessel segmentation is performed by using Otsu algorithm and tensor coloring method which is inspired by the ellipsoid tensor visualization technique. Finally, some post-processing techniques are applied to the segmentation result. In this study, the proposed method achieved mean sensitivity of 0.8123, 0.8126, 0.7246 and mean specificity of 0.9342, 0.9442, 0.9453 as well as mean accuracy of 0.9183, 0.9442, 0.9236 for DRIVE, STARE and CHASE_DB1 datasets, respectively. The mean execution time of this study is 6.104, 6.4525 and 18.8370 s for the aforementioned three datasets respectively.

  5. Structured prediction for urban scene semantic segmentation with geographic context

    OpenAIRE

    Volpi, M.; Ferrari, V.

    2015-01-01

    In this work we address the problem of semantic segmentation of urban remote sensing images into land cover maps. We propose to tackle this task by learning the geographic context of classes and use it to favor or discourage certain spatial configuration of label assignments. For this reason, we learn from training data two spatial priors enforcing different key aspects of the geographical space: local co-occurrence and relative location of land cover classes. We propose to embed these geogra...

  6. Representing diffusion MRI in 5-D simplifies regularization and segmentation of white matter tracts.

    Science.gov (United States)

    Jonasson, Lisa; Bresson, Xavier; Thiran, Jean-Philippe; Wedeen, Van J; Hagmann, Patric

    2007-11-01

    We present a new five-dimensional (5-D) space representation of diffusion magnetic resonance imaging (dMRI) of high angular resolution. This 5-D space is basically a non-Euclidean space of position and orientation in which crossing fiber tracts can be clearly disentangled, that cannot be separated in three-dimensional position space. This new representation provides many possibilities for processing and analysis since classical methods for scalar images can be extended to higher dimensions even if the spaces are not Euclidean. In this paper, we show examples of how regularization and segmentation of dMRI is simplified with this new representation. The regularization is used with the purpose of denoising and but also to facilitate the segmentation task by using several scales, each scale representing a different level of resolution. We implement in five dimensions the Chan-Vese method combined with active contours without edges for the segmentation and the total variation functional for the regularization. The purpose of this paper is to explore the possibility of segmenting white matter structures directly as entirely separated bundles in this 5-D space. We will present results from a synthetic model and results on real data of a human brain acquired with diffusion spectrum magnetic resonance imaging (MRI), one of the dMRI of high angular resolution available. These results will lead us to the conclusion that this new high-dimensional representation indeed simplifies the problem of segmentation and regularization.

  7. Spondylosis deformans and diffuse idiopathic skeletal hyperostosis (dish) resulting in adjacent segment disease.

    Science.gov (United States)

    Ortega, Maria; Gonçalves, Rita; Haley, Allison; Wessmann, Annette; Penderis, Jacques

    2012-01-01

    Spondylosis deformans and diffuse idiopathic skeletal hyperostosis (DISH) are usually incidental findings and in most dogs are either asymptomatic or associated with mild clinical signs. Severe spondylosis deformans and DISH can result in complete bony fusion of consecutive vertebral segments. One of the recognised complications following vertebral fusion in human patients is the development of adjacent segment disease, which is defined as degenerative changes, most commonly degenerative intervertebral disc disease, in the mobile vertebral segment neighboring a region of complete vertebral fusion. A similar syndrome following cervical fusion in dogs has been termed the domino effect. The purpose of this retrospective study was to investigate the hypothesis that vertebral fusion occurring secondary to spondylosis deformans or DISH in dogs would protect fused intervertebral disc spaces from undergoing degeneration, but result in adjacent segment disease at neighbouring unfused intervertebral disc spaces. Eight dogs with clinical signs of thoracolumbar myelopathy, magnetic resonance imaging of the thoracolumbar vertebral column, and spondylosis deformans or DISH producing fusion of > or = 2 consecutive intervertebral disc spaces were evaluated. Vertebral fusion of > or = 2 consecutive intervertebral disc spaces was correlated (P = 0.0017) with adjacent segment disease at the neighbouring unfused intervertebral disc space. Vertebral fusion appeared to protect fused intervertebral disc spaces from undergoing degeneration (P spondylosis deformans or DISH occurring in conjunction with a thoracolumbar myelopathy.

  8. Fast prostate segmentation for brachytherapy based on joint fusion of images and labels

    Science.gov (United States)

    Nouranian, Saman; Ramezani, Mahdi; Mahdavi, S. Sara; Spadinger, Ingrid; Morris, William J.; Salcudean, Septimiu E.; Abolmaesumi, Purang

    2014-03-01

    Brachytherapy as one of the treatment methods for prostate cancer takes place by implantation of radioactive seeds inside the gland. The standard of care for this treatment procedure is to acquire transrectal ultrasound images of the prostate which are segmented in order to plan the appropriate seed placement. The segmentation process is usually performed either manually or semi-automatically and is associated with subjective errors because the prostate visibility is limited in ultrasound images. The current segmentation process also limits the possibility of intra-operative delineation of the prostate to perform real-time dosimetry. In this paper, we propose a computationally inexpensive and fully automatic segmentation approach that takes advantage of previously segmented images to form a joint space of images and their segmentations. We utilize joint Independent Component Analysis method to generate a model which is further employed to produce a probability map of the target segmentation. We evaluate this approach on the transrectal ultrasound volume images of 60 patients using a leave-one-out cross-validation approach. The results are compared with the manually segmented prostate contours that were used by clinicians to plan brachytherapy procedures. We show that the proposed approach is fast with comparable accuracy and precision to those found in previous studies on TRUS segmentation.

  9. Atlas-based segmentation technique incorporating inter-observer delineation uncertainty for whole breast

    International Nuclear Information System (INIS)

    Bell, L R; Pogson, E M; Metcalfe, P; Holloway, L; Dowling, J A

    2017-01-01

    Accurate, efficient auto-segmentation methods are essential for the clinical efficacy of adaptive radiotherapy delivered with highly conformal techniques. Current atlas based auto-segmentation techniques are adequate in this respect, however fail to account for inter-observer variation. An atlas-based segmentation method that incorporates inter-observer variation is proposed. This method is validated for a whole breast radiotherapy cohort containing 28 CT datasets with CTVs delineated by eight observers. To optimise atlas accuracy, the cohort was divided into categories by mean body mass index and laterality, with atlas’ generated for each in a leave-one-out approach. Observer CTVs were merged and thresholded to generate an auto-segmentation model representing both inter-observer and inter-patient differences. For each category, the atlas was registered to the left-out dataset to enable propagation of the auto-segmentation from atlas space. Auto-segmentation time was recorded. The segmentation was compared to the gold-standard contour using the dice similarity coefficient (DSC) and mean absolute surface distance (MASD). Comparison with the smallest and largest CTV was also made. This atlas-based auto-segmentation method incorporating inter-observer variation was shown to be efficient (<4min) and accurate for whole breast radiotherapy, with good agreement (DSC>0.7, MASD <9.3mm) between the auto-segmented contours and CTV volumes. (paper)

  10. Dictionary Based Segmentation in Volumes

    DEFF Research Database (Denmark)

    Emerson, Monica Jane; Jespersen, Kristine Munk; Jørgensen, Peter Stanley

    2015-01-01

    We present a method for supervised volumetric segmentation based on a dictionary of small cubes composed of pairs of intensity and label cubes. Intensity cubes are small image volumes where each voxel contains an image intensity. Label cubes are volumes with voxelwise probabilities for a given...... label. The segmentation process is done by matching a cube from the volume, of the same size as the dictionary intensity cubes, to the most similar intensity dictionary cube, and from the associated label cube we get voxel-wise label probabilities. Probabilities from overlapping cubes are averaged...... and hereby we obtain a robust label probability encoding. The dictionary is computed from labeled volumetric image data based on weighted clustering. We experimentally demonstrate our method using two data sets from material science – a phantom data set of a solid oxide fuel cell simulation for detecting...

  11. Segmentation in local hospital markets.

    Science.gov (United States)

    Dranove, D; White, W D; Wu, L

    1993-01-01

    This study examines evidence of market segmentation on the basis of patients' insurance status, demographic characteristics, and medical condition in selected local markets in California in the years 1983 and 1989. Substantial differences exist in the probability patients may be admitted to particular hospitals based on insurance coverage, particularly Medicaid, and race. Segmentation based on insurance and race is related to hospital characteristics, but not the characteristics of the hospital's community. Medicaid patients are more likely to go to hospitals with lower costs and fewer service offerings. Privately insured patients go to hospitals offering more services, although cost concerns are increasing. Hispanic patients also go to low-cost hospitals, ceteris paribus. Results indicate little evidence of segmentation based on medical condition in either 1983 or 1989, suggesting that "centers of excellence" have yet to play an important role in patient choice of hospital. The authors found that distance matters, and that patients prefer nearby hospitals, moreso for some medical conditions than others, in ways consistent with economic theories of consumer choice.

  12. 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...

  13. Gold-standard and improved framework for sperm head segmentation.

    Science.gov (United States)

    Chang, Violeta; Saavedra, Jose M; Castañeda, Victor; Sarabia, Luis; Hitschfeld, Nancy; Härtel, Steffen

    2014-11-01

    Semen analysis is the first step in the evaluation of an infertile couple. Within this process, an accurate and objective morphological analysis becomes more critical as it is based on the correct detection and segmentation of human sperm components. In this paper, we present an improved two-stage framework for detection and segmentation of human sperm head characteristics (including acrosome and nucleus) that uses three different color spaces. The first stage detects regions of interest that define sperm heads, using k-means, then candidate heads are refined using mathematical morphology. In the second stage, we work on each region of interest to segment accurately the sperm head as well as nucleus and acrosome, using clustering and histogram statistical analysis techniques. Our proposal is also characterized by being fully automatic, where a user intervention is not required. Our experimental evaluation shows that our proposed method outperforms the state-of-the-art. This is supported by the results of different evaluation metrics. In addition, we propose a gold-standard built with the cooperation of a referent expert in the field, aiming to compare methods for detecting and segmenting sperm cells. Our results achieve notable improvement getting above 98% in the sperm head detection process at the expense of having significantly fewer false positives obtained by the state-of-the-art method. Our results also show an accurate head, acrosome and nucleus segmentation achieving over 80% overlapping against hand-segmented gold-standard. Our method achieves higher Dice coefficient, lower Hausdorff distance and less dispersion with respect to the results achieved by the state-of-the-art method. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  14. Automatic segmentation of diatom images for classification

    NARCIS (Netherlands)

    Jalba, Andrei C.; Wilkinson, Michael H.F.; Roerdink, Jos B.T.M.

    A general framework for automatic segmentation of diatom images is presented. This segmentation is a critical first step in contour-based methods for automatic identification of diatoms by computerized image analysis. We review existing results, adapt popular segmentation methods to this difficult

  15. The Process of Marketing Segmentation Strategy Selection

    OpenAIRE

    Ionel Dumitru

    2007-01-01

    The process of marketing segmentation strategy selection represents the essence of strategical marketing. We present hereinafter the main forms of the marketing statategy segmentation: undifferentiated marketing, differentiated marketing, concentrated marketing and personalized marketing. In practice, the companies use a mix of these marketing segmentation methods in order to maximize the proffit and to satisfy the consumers’ needs.

  16. Handwriting segmentation of unconstrained Oriya text

    Indian Academy of Sciences (India)

    characters of the word that touch are then segmented. From experiments we have observed that the proposed “touching character” segmentation module has 96·7% accuracy for two-character touching strings. Keywords. Indian language; Oriya script; character segmentation; handwriting recognition. 1. Introduction.

  17. 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

  18. Quick Dissection of the Segmental Bronchi

    Science.gov (United States)

    Nakajima, Yuji

    2010-01-01

    Knowledge of the three-dimensional anatomy of the bronchopulmonary segments is essential for respiratory medicine. This report describes a quick guide for dissecting the segmental bronchi in formaldehyde-fixed human material. All segmental bronchi are easy to dissect, and thus, this exercise will help medical students to better understand the…

  19. Multi-strategy Segmentation of Melodies

    NARCIS (Netherlands)

    Rodríguez López, M.E.; Volk, Anja; Bountouridis, D.

    2014-01-01

    Melodic segmentation is a fundamental yet unsolved problem in automatic music processing. At present most melody segmentation models rely on a ‘single strategy’ (i.e. they model a single perceptual segmentation cue). However, cognitive studies suggest that multiple cues need to be considered. In

  20. 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…

  1. Parallel fuzzy connected image segmentation on GPU

    OpenAIRE

    Zhuge, Ying; Cao, Yong; Udupa, Jayaram K.; Miller, Robert W.

    2011-01-01

    Purpose: Image segmentation techniques using fuzzy connectedness (FC) principles have shown their effectiveness in segmenting a variety of objects in several large applications. However, one challenge in these algorithms has been their excessive computational requirements when processing large image datasets. Nowadays, commodity graphics hardware provides a highly parallel computing environment. In this paper, the authors present a parallel fuzzy connected image segmentation algorithm impleme...

  2. Segmental fracture of the lumbar spine.

    Science.gov (United States)

    O'hEireamhoin, Sven; Devitt, Brian; Baker, Joseph; Kiely, Paul; Synnott, Keith

    2010-10-01

    A case report is presented. To describe a rare, previously undescribed pattern of spinal injury. This seems to be a unique injury with no previously described injuries matching the fracture pattern observed. This is a case report based on the experience of the authors. The discussion includes a short literature review based on pubmed searches. We report the case of a 26-year-old female cyclist involved in a road traffic accident with a truck resulting in complete disruption of the lumbar spine. The cyclist was caught on the inside of a truck turning left and seems to have passed under the rear wheels. She was brought to the local emergency department where, after appropriate resuscitation, trauma survey revealed spinal deformity with complete neurologic deficit below T12 and fractured pubic rami, soft tissue injuries to the perineum and multiple abrasions. Plain radiology showed a segmental fracture dislocation of her lumbar vertebrae, extending from the L1 superior endplate through to L4-L5 disc space. The entire segment was displaced in both anteroposterior and lateral planes. Computed tomography confirmed these injuries and ruled out significant visceral injury. She was transferred to the national spinal unit (author unit), where she underwent reduction and fixation with rods and screws from T9-S1, using one cross-link. After her immediate postoperative recovery, she was referred to the national rehabilitation unit. Although so-called "en bloc" lumbar fractures have been previously described, the authors were unable to find any injury of this degree in the literature. This rare injury seems to show a pattern of spinal injury previously undescribed.

  3. Automated image segmentation using information theory

    International Nuclear Information System (INIS)

    Hibbard, L.S.

    2001-01-01

    Full text: Our development of automated contouring of CT images for RT planning is based on maximum a posteriori (MAP) analyses of region textures, edges, and prior shapes, and assumes stationary Gaussian distributions for voxel textures and contour shapes. Since models may not accurately represent image data, it would be advantageous to compute inferences without relying on models. The relative entropy (RE) from information theory can generate inferences based solely on the similarity of probability distributions. The entropy of a distribution of a random variable X is defined as -Σ x p(x)log 2 p(x) for all the values x which X may assume. The RE (Kullback-Liebler divergence) of two distributions p(X), q(X), over X is Σ x p(x)log 2 {p(x)/q(x)}. The RE is a kind of 'distance' between p,q, equaling zero when p=q and increasing as p,q are more different. Minimum-error MAP and likelihood ratio decision rules have RE equivalents: minimum error decisions obtain with functions of the differences between REs of compared distributions. One applied result is the contour ideally separating two regions is that which maximizes the relative entropy of the two regions' intensities. A program was developed that automatically contours the outlines of patients in stereotactic headframes, a situation most often requiring manual drawing. The relative entropy of intensities inside the contour (patient) versus outside (background) was maximized by conjugate gradient descent over the space of parameters of a deformable contour. shows the computed segmentation of a patient from headframe backgrounds. This program is particularly useful for preparing images for multimodal image fusion. Relative entropy and allied measures of distribution similarity provide automated contouring criteria that do not depend on statistical models of image data. This approach should have wide utility in medical image segmentation applications. Copyright (2001) Australasian College of Physical Scientists and

  4. A shape-optimized framework for kidney segmentation in ultrasound images using NLTV denoising and DRLSE

    Directory of Open Access Journals (Sweden)

    Yang Fan

    2012-10-01

    Full Text Available Abstract Background Computer-assisted surgical navigation aims to provide surgeons with anatomical target localization and critical structure observation, where medical image processing methods such as segmentation, registration and visualization play a critical role. Percutaneous renal intervention plays an important role in several minimally-invasive surgeries of kidney, such as Percutaneous Nephrolithotomy (PCNL and Radio-Frequency Ablation (RFA of kidney tumors, which refers to a surgical procedure where access to a target inside the kidney by a needle puncture of the skin. Thus, kidney segmentation is a key step in developing any ultrasound-based computer-aided diagnosis systems for percutaneous renal intervention. Methods In this paper, we proposed a novel framework for kidney segmentation of ultrasound (US images combined with nonlocal total variation (NLTV image denoising, distance regularized level set evolution (DRLSE and shape prior. Firstly, a denoised US image was obtained by NLTV image denoising. Secondly, DRLSE was applied in the kidney segmentation to get binary image. In this case, black and white region represented the kidney and the background respectively. The last stage is that the shape prior was applied to get a shape with the smooth boundary from the kidney shape space, which was used to optimize the segmentation result of the second step. The alignment model was used occasionally to enlarge the shape space in order to increase segmentation accuracy. Experimental results on both synthetic images and US data are given to demonstrate the effectiveness and accuracy of the proposed algorithm. Results We applied our segmentation framework on synthetic and real US images to demonstrate the better segmentation results of our method. From the qualitative results, the experiment results show that the segmentation results are much closer to the manual segmentations. The sensitivity (SN, specificity (SP and positive predictive value

  5. Semi-supervised subspace learning for Mumford-Shah model based texture segmentation.

    Science.gov (United States)

    Law, Yan Nei; Lee, Hwee Kuan; Yip, Andy M

    2010-03-01

    We propose a novel image segmentation model which incorporates subspace clustering techniques into a Mumford-Shah model to solve texture segmentation problems. While the natural unsupervised approach to learn a feature subspace can easily be trapped in a local solution, we propose a novel semi-supervised optimization algorithm that makes use of information derived from both the intermediate segmentation results and the regions-of-interest (ROI) selected by the user to determine the optimal subspaces of the target regions. Meanwhile, these subspaces are embedded into a Mumford-Shah objective function so that each segment of the optimal partition is homogeneous in its own subspace. The method outperforms standard Mumford-Shah models since it can separate textures which are less separated in the full feature space. Experimental results are presented to confirm the usefulness of subspace clustering in texture segmentation.

  6. An automatic system for segmentation, matching, anatomical labeling and measurement of airways from CT images

    DEFF Research Database (Denmark)

    Petersen, Jens; Feragen, Aasa; Owen, Megan

    Purpose: Assessing airway dimensions and attenuation from CT images is useful in the study of diseases affecting the airways such as Chronic Obstructive Pulmonary Disease (COPD). Measurements can be compared between patients and over time if specific airway segments can be identified. However......, manually finding these segments and performing such measurements is very time consuming. The purpose of the developed and validated system is to enable such measurements using automatic segmentations of the airway interior and exterior wall surfaces in three dimensions, anatomical branch labeling of all...... is used to match specific airway segments in multiple images of the same subject. The anatomical names of all segmental branches are assigned based on distances to a training set of expert labeled trees. Distances are measured in a geometric tree-space, incorporating both topology and centerline shape...

  7. Robust x-ray image segmentation by spectral clustering and active shape model.

    Science.gov (United States)

    Wu, Jing; Mahfouz, Mohamed R

    2016-07-01

    Extraction of bone contours from x-ray radiographs plays an important role in joint space width assessment, preoperative planning, and kinematics analysis. We present a robust segmentation method to accurately extract the distal femur and proximal tibia in knee radiographs of varying image quality. A spectral clustering method based on the eigensolution of an affinity matrix is utilized for x-ray image denoising. An active shape model-based segmentation method is employed for robust and accurate segmentation of the denoised x-ray images. The performance of the proposed method is evaluated with x-ray images from the public-use dataset(s), the osteoarthritis initiative, achieving a root mean square error of [Formula: see text] for femur and [Formula: see text] for tibia. The results demonstrate that this method outperforms previous segmentation methods in capturing anatomical shape variations, accounting for image quality differences and guiding accurate segmentation.

  8. Joint statistics and conditional mean strain rates of streamline segments

    International Nuclear Information System (INIS)

    Schaefer, P; Gampert, M; Peters, N

    2013-01-01

    Based on four different direct numerical simulations of turbulent flows with Taylor-based Reynolds numbers ranging from Re λ = 50 to 300 among which are two homogeneous isotropic decaying, one forced and one homogeneous shear flow, streamlines are identified and the obtained space curves are parameterized with the pseudo-time as well as the arclength. Based on local extrema of the absolute value of the velocity along the streamlines, the latter are partitioned into segments following Wang (2010 J. Fluid Mech. 648 183–203). Streamline segments are then statistically analyzed based on both parameterizations using the joint probability density function of the pseudo-time lag τ (arclength l, respectively) between and the velocity difference Δu at the extrema: P(τ,Δu), (P(l,Δu)). We distinguish positive and negative streamline segments depending on the sign of the velocity difference Δu. Differences as well as similarities in the statistical description for both parameterizations are discussed. In particular, it turns out that the normalized probability distribution functions (pdfs) (of both parameterizations) of the length of positive, negative and all segments assume a universal shape for all Reynolds numbers and flow types and are well described by a model derived in Schaefer P et al (2012 Phys. Fluids 24 045104). Particular attention is given to the conditional mean velocity difference at the ending points of the segments, which can be understood as a first-order structure function in the context of streamline segment analysis. It determines to a large extent the stretching (compression) of positive (negative) streamline segments and corresponds to the convective velocity in phase space in the transport model equation for the pdf. While based on the random sweeping hypothesis a scaling ∝ (u rms ετ) 1/3 is found for the parameterization based on the pseudo-time, the parameterization with the arclength l yields a much larger than expected l 1/3 scaling. A

  9. Unfolding Implementation in Industrial Market Segmentation

    DEFF Research Database (Denmark)

    Bøjgaard, John; Ellegaard, Chris

    2011-01-01

    Market segmentation is an important method of strategic marketing and constitutes a cornerstone of the marketing literature. It has undergone extensive scientific inquiry during the past 50 years. Reporting on an extensive review of the market segmentation literature, the challenging task...... of implementing industrial market segmentation is discussed and unfolded in this article. Extant literature has identified segmentation implementation as a core challenge for marketers, but also one, which has received limited empirical attention. Future research opportunities are formulated in this article...... for marketing management. Three key elements and challenges connected to execution of market segmentation are identified — organization, motivation, and adaptation....

  10. Central nervous system involvement in a case of segmental nevus depigmentosus

    Directory of Open Access Journals (Sweden)

    Ishita Majumdar

    2016-01-01

    Full Text Available Central nervous system involvement in segmental nevus depigmentosus (SND is rare. A 7-month-old boy having convulsion and segmental hypopigmented patch in the right inguinal region. Magnetic resonance imaging of brain showed bilateral periventricular white matter hypoplasia with prominent subarachnoid spaces and mild dilation of ventricles with mild left cerebral hemispheric atrophy. Association of SND with seizure and white matter lesion has been rarely reported.

  11. Image Segmentation Using Disjunctive Normal Bayesian Shape and Appearance Models.

    Science.gov (United States)

    Mesadi, Fitsum; Erdil, Ertunc; Cetin, Mujdat; Tasdizen, Tolga

    2018-01-01

    The use of appearance and shape priors in image segmentation is known to improve accuracy; however, existing techniques have several drawbacks. For instance, most active shape and appearance models require landmark points and assume unimodal shape and appearance distributions, and the level set representation does not support construction of local priors. In this paper, we present novel appearance and shape models for image segmentation based on a differentiable implicit parametric shape representation called a disjunctive normal shape model (DNSM). The DNSM is formed by the disjunction of polytopes, which themselves are formed by the conjunctions of half-spaces. The DNSM's parametric nature allows the use of powerful local prior statistics, and its implicit nature removes the need to use landmarks and easily handles topological changes. In a Bayesian inference framework, we model arbitrary shape and appearance distributions using nonparametric density estimations, at any local scale. The proposed local shape prior results in accurate segmentation even when very few training shapes are available, because the method generates a rich set of shape variations by locally combining training samples. We demonstrate the performance of the framework by applying it to both 2-D and 3-D data sets with emphasis on biomedical image segmentation applications.

  12. A Parametric Finite-Element Model for Evaluating Segmented Mirrors with Discrete, Edgewise Connectivity

    Science.gov (United States)

    Gersh-Range, Jessica A.; Arnold, William R.; Peck, Mason A.; Stahl, H. Philip

    2011-01-01

    Since future astrophysics missions require space telescopes with apertures of at least 10 meters, there is a need for on-orbit assembly methods that decouple the size of the primary mirror from the choice of launch vehicle. One option is to connect the segments edgewise using mechanisms analogous to damped springs. To evaluate the feasibility of this approach, a parametric ANSYS model that calculates the mode shapes, natural frequencies, and disturbance response of such a mirror, as well as of the equivalent monolithic mirror, has been developed. This model constructs a mirror using rings of hexagonal segments that are either connected continuously along the edges (to form a monolith) or at discrete locations corresponding to the mechanism locations (to form a segmented mirror). As an example, this paper presents the case of a mirror whose segments are connected edgewise by mechanisms analogous to a set of four collocated single-degree-of-freedom damped springs. The results of a set of parameter studies suggest that such mechanisms can be used to create a 15-m segmented mirror that behaves similarly to a monolith, although fully predicting the segmented mirror performance would require incorporating measured mechanism properties into the model. Keywords: segmented mirror, edgewise connectivity, space telescope

  13. Upper airway segmentation and dimensions estimation from cone-beam CT image datasets

    Energy Technology Data Exchange (ETDEWEB)

    Shi, Hongjian; Scarfe, W.C. [Louisville Univ., KY (United States). School of Dentistry; Farman, A.G. [Louisville Univ., KY (United States). School of Dentistry; Louisville Univ., KY (United States). Div. of Radiology and Imaging Science

    2006-11-15

    Objective: To segment and measure the upper airway using cone-beam computed tomography (CBCT). This information may be useful as an imaging biomarker in the diagnostic assessment of patients with obstructive sleep apnea and in the planning of any necessary therapy. Methods: With Institutional Review Board Approval, anonymous CBCT datasets from subjects who had been imaged for a variety of conditions unrelated to the airway were evaluated. DICOM images were available. A segmentation algorithm was developed to separate the bounded upper airway and measurements were performed manually to determine the smallest cross-sectional area and the anteriorposterior distance of the retropalatal space (RP-SCA and RP-AP, respectively) and retroglossal space (RG-SCA and RG-AP, respectively). A segmentation algorithm was developed to separate the bounded upper airway and it was applied to determine RP-AP, RG-AP, the smallest transaxial-sectional area (TSCA) and largest sagittal view airway area (LCSA). A second algorithm was created to evaluate the airway volume within this bounded upper airway. Results: Measurements of the airway segmented automatically by the developed algorithm agreed with those obtained using manual segmentation. The corresponding volumes showed only very small differences considered clinically insignificant. Conclusion: Automatic segmentation of the airway imaged using CBCT is feasible and this method can be used to evaluate airway cross-section and volume comparable to measurements extracted using manual segmentation. (orig.)

  14. 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.

  15. 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.

  16. An efficient iris segmentation approach

    Science.gov (United States)

    Gomai, Abdu; El-Zaart, A.; Mathkour, H.

    2011-10-01

    Iris recognition system became a reliable system for authentication and verification tasks. It consists of five stages: image acquisition, iris segmentation, iris normalization, feature encoding, and feature matching. Iris segmentation stage is one of the most important stages. It plays an essential role to locate the iris efficiently and accurately. In this paper, we present a new approach for iris segmentation using image processing technique. This approach is composed of four main parts. (1) Eliminating reflections of light on the eye image based on inverting the color of the grayscale image, filling holes in the intensity image, and inverting the color of the intensity image to get the original grayscale image without any reflections. (2) Pupil boundary detection based on dividing an eye image to nine sub-images and finding the minimum value of the mean intensity for each sub-image to get a suitable threshold value of pupil. (3) Enhancing the contrast of outer iris boundary using exponential operator to have sharp variation. (4) Outer iris boundary localization based on applying a gray threshold and morphological operations on the rectangular part of an eye image including the pupil and the outer boundaries of iris to find the small radius of outer iris boundary from the center of pupil. The proposed approach has been tested on CASIA v1.0 iris image database and other collected iris image database. The experimental results show that the approach is able to detect pupil and outer iris boundary with high accuracy results approximately 100% and reduce time consuming.

  17. 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.

  18. Interferon Induced Focal Segmental Glomerulosclerosis

    Directory of Open Access Journals (Sweden)

    Yusuf Kayar

    2016-01-01

    Full Text Available Behçet’s disease is an inflammatory disease of unknown etiology which involves recurring oral and genital aphthous ulcers and ocular lesions as well as articular, vascular, and nervous system involvement. Focal segmental glomerulosclerosis (FSGS is usually seen in viral infections, immune deficiency syndrome, sickle cell anemia, and hyperfiltration and secondary to interferon therapy. Here, we present a case of FSGS identified with kidney biopsy in a patient who had been diagnosed with Behçet’s disease and received interferon-alpha treatment for uveitis and presented with acute renal failure and nephrotic syndrome associated with interferon.

  19. A contrario line segment detection

    CERN Document Server

    von Gioi, Rafael Grompone

    2014-01-01

    The reliable detection of low-level image structures is an old and still challenging problem in computer vision. This?book leads a detailed tour through the LSD algorithm, a line segment detector designed to be fully automatic. Based on the a contrario framework, the algorithm works efficiently without the need of any parameter tuning. The design criteria are thoroughly explained and the algorithm's good and bad results are illustrated on real and synthetic images. The issues involved, as well as the strategies used, are common to many geometrical structure detection problems and some possible

  20. Multiphase Image Segmentation Using the Deformable Simplicial Complex Method

    DEFF Research Database (Denmark)

    Dahl, Vedrana Andersen; Christiansen, Asger Nyman; Bærentzen, Jakob Andreas

    2014-01-01

    in image segmentation based on deformable models. We show the benefits of using the deformable simplicial complex method for image segmentation by segmenting an image into a known number of segments characterized by distinct mean pixel intensities....

  1. Adjustable Two-Tier Cache for IPTV Based on Segmented Streaming

    Directory of Open Access Journals (Sweden)

    Kai-Chun Liang

    2012-01-01

    Full Text Available Internet protocol TV (IPTV is a promising Internet killer application, which integrates video, voice, and data onto a single IP network, and offers viewers an innovative set of choices and control over their TV content. To provide high-quality IPTV services, an effective strategy is based on caching. This work proposes a segment-based two-tier caching approach, which divides each video into multiple segments to be cached. This approach also partitions the cache space into two layers, where the first layer mainly caches to-be-played segments and the second layer saves possibly played segments. As the segment access becomes frequent, the proposed approach enlarges the first layer and reduces the second layer, and vice versa. Because requested segments may not be accessed frequently, this work further designs an admission control mechanism to determine whether an incoming segment should be cached or not. The cache architecture takes forward/stop playback into account and may replace the unused segments under the interrupted playback. Finally, we conduct comprehensive simulation experiments to evaluate the performance of the proposed approach. The results show that our approach can yield higher hit ratio than previous work under various environmental parameters.

  2. Automatic segmentation of clinical texts.

    Science.gov (United States)

    Apostolova, Emilia; Channin, David S; Demner-Fushman, Dina; Furst, Jacob; Lytinen, Steven; Raicu, Daniela

    2009-01-01

    Clinical narratives, such as radiology and pathology reports, are commonly available in electronic form. However, they are also commonly entered and stored as free text. Knowledge of the structure of clinical narratives is necessary for enhancing the productivity of healthcare departments and facilitating research. This study attempts to automatically segment medical reports into semantic sections. Our goal is to develop a robust and scalable medical report segmentation system requiring minimum user input for efficient retrieval and extraction of information from free-text clinical narratives. Hand-crafted rules were used to automatically identify a high-confidence training set. This automatically created training dataset was later used to develop metrics and an algorithm that determines the semantic structure of the medical reports. A word-vector cosine similarity metric combined with several heuristics was used to classify each report sentence into one of several pre-defined semantic sections. This baseline algorithm achieved 79% accuracy. A Support Vector Machine (SVM) classifier trained on additional formatting and contextual features was able to achieve 90% accuracy. Plans for future work include developing a configurable system that could accommodate various medical report formatting and content standards.

  3. WCE video segmentation using textons

    Science.gov (United States)

    Gallo, Giovanni; Granata, Eliana

    2010-03-01

    Wireless Capsule Endoscopy (WCE) integrates wireless transmission with image and video technology. It has been used to examine the small intestine non invasively. Medical specialists look for signicative events in the WCE video by direct visual inspection manually labelling, in tiring and up to one hour long sessions, clinical relevant frames. This limits the WCE usage. To automatically discriminate digestive organs such as esophagus, stomach, small intestine and colon is of great advantage. In this paper we propose to use textons for the automatic discrimination of abrupt changes within a video. In particular, we consider, as features, for each frame hue, saturation, value, high-frequency energy content and the responses to a bank of Gabor filters. The experiments have been conducted on ten video segments extracted from WCE videos, in which the signicative events have been previously labelled by experts. Results have shown that the proposed method may eliminate up to 70% of the frames from further investigations. The direct analysis of the doctors may hence be concentrated only on eventful frames. A graphical tool showing sudden changes in the textons frequencies for each frame is also proposed as a visual aid to find clinically relevant segments of the video.

  4. Segmented MEMS Mirror Arrays Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective of this proposal is to demonstrate the feasibility of manufacturing large-throw, low cross-talk, high resolution and fast responding-speed wavefront...

  5. 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)

  6. Segmented Domain Decomposition Multigrid For 3-D Turbomachinery Flows

    Science.gov (United States)

    Celestina, M. L.; Adamczyk, J. J.; Rubin, S. G.

    2001-01-01

    A Segmented Domain Decomposition Multigrid (SDDMG) procedure was developed for three-dimensional viscous flow problems as they apply to turbomachinery flows. The procedure divides the computational domain into a coarse mesh comprised of uniformly spaced cells. To resolve smaller length scales such as the viscous layer near a surface, segments of the coarse mesh are subdivided into a finer mesh. This is repeated until adequate resolution of the smallest relevant length scale is obtained. Multigrid is used to communicate information between the different grid levels. To test the procedure, simulation results will be presented for a compressor and turbine cascade. These simulations are intended to show the ability of the present method to generate grid independent solutions. Comparisons with data will also be presented. These comparisons will further demonstrate the usefulness of the present work for they allow an estimate of the accuracy of the flow modeling equations independent of error attributed to numerical discretization.

  7. Unsupervised color image segmentation using a lattice algebra clustering technique

    Science.gov (United States)

    Urcid, Gonzalo; Ritter, Gerhard X.

    2011-08-01

    In this paper we introduce a lattice algebra clustering technique for segmenting digital images in the Red-Green- Blue (RGB) color space. The proposed technique is a two step procedure. Given an input color image, the first step determines the finite set of its extreme pixel vectors within the color cube by means of the scaled min-W and max-M lattice auto-associative memory matrices, including the minimum and maximum vector bounds. In the second step, maximal rectangular boxes enclosing each extreme color pixel are found using the Chebychev distance between color pixels; afterwards, clustering is performed by assigning each image pixel to its corresponding maximal box. The two steps in our proposed method are completely unsupervised or autonomous. Illustrative examples are provided to demonstrate the color segmentation results including a brief numerical comparison with two other non-maximal variations of the same clustering technique.

  8. Point based interactive image segmentation using multiquadrics splines

    Science.gov (United States)

    Meena, Sachin; Duraisamy, Prakash; Palniappan, Kannappan; Seetharaman, Guna

    2017-05-01

    Multiquadrics (MQ) are radial basis spline function that can provide an efficient interpolation of data points located in a high dimensional space. MQ were developed by Hardy to approximate geographical surfaces and terrain modelling. In this paper we frame the task of interactive image segmentation as a semi-supervised interpolation where an interpolating function learned from the user provided seed points is used to predict the labels of unlabeled pixel and the spline function used in the semi-supervised interpolation is MQ. This semi-supervised interpolation framework has a nice closed form solution which along with the fact that MQ is a radial basis spline function lead to a very fast interactive image segmentation process. Quantitative and qualitative results on the standard datasets show that MQ outperforms other regression based methods, GEBS, Ridge Regression and Logistic Regression, and popular methods like Graph Cut,4 Random Walk and Random Forest.6

  9. Endplates Changes Related to Age and Vertebral Segment

    Directory of Open Access Journals (Sweden)

    Carlos Fernando P. S. Herrero

    2014-01-01

    Full Text Available Endplate separations are defined as the presence of a space between the hyaline cartilage and the cortical bone of the adjacent vertebral body. This study evaluates endplate separations from the vertebral body and intervertebral discs and verifies if endplate separation is related to age and the spinal level. Groups were formed based on age (20–40 and 41–85 years old and the vertebral segment (T7-T8 and L4-L5 segments. Histological analysis included assessment of the length of the vertebral endplates, the number and dimensions of the separations, and orientation of the collagen fibers, in the mid-sagittal slice. Two indexes were created: the separation index (number of separations/vertebral length and separation extension index (sum of all separations/vertebral length. The results of the study demonstrated a direct relationship between the density of separations in the endplate and two variables: age and spinal level.

  10. Space Warfighting Construct: Prototyping

    Science.gov (United States)

    Teehan, R. F.; Anttonen, J. S.; Stein, J. M.; Stearns, J. A.

    Space is undergoing a period of great change, as the barriers to entry are lowering in every arena. Launch to any orbit is becoming more routine and feasible thanks to industry innovation, the rise of small- and cubesats, and the use of ESPA rings enabling “freight trains to GEO.” With more regular rides to space, there is a concomitant rise in the capability for space qualification, technology validation and verification, and all types of experimentation in both the space and ground segments. The types of architectures that commercial and government agencies develop is being influenced because space is becoming more accessible. Whereas current architectures are designed to have four to six satellites perform a mission, in the future that same mission may be distributed among dozens, hundreds, or even thousands of satellites. This changing landscape is something of a double-edged sword for Space Situational Awareness (SSA): safety of flight becomes a heightened concern, but the opportunities for the entire community to innovate, prototype, and ultimately provide novel, robust solutions have never been greater.

  11. Temporal segmentation of animal trajectories informed by habitat use

    Science.gov (United States)

    van Toor, Marielle L.; Newman, Scott H.; Takekawa, John Y.; Wegmann, Martin; Safi, Kamran

    2016-01-01

    Most animals live in seasonal environments and experience very different conditions throughout the year. Behavioral strategies like migration, hibernation, and a life cycle adapted to the local seasonality help to cope with fluctuations in environmental conditions. Thus, how an individual utilizes the environment depends both on the current availability of habitat and the behavioral prerequisites of the individual at that time. While the increasing availability and richness of animal movement data has facilitated the development of algorithms that classify behavior by movement geometry, changes in the environmental correlates of animal movement have so far not been exploited for a behavioral annotation. Here, we suggest a method that uses these changes in individual–environment associations to divide animal location data into segments of higher ecological coherence, which we term niche segmentation. We use time series of random forest models to evaluate the transferability of habitat use over time to cluster observational data accordingly. We show that our method is able to identify relevant changes in habitat use corresponding to both changes in the availability of habitat and how it was used using simulated data, and apply our method to a tracking data set of common teal (Anas crecca). The niche segmentation proved to be robust, and segmented habitat suitability outperformed models neglecting the temporal dynamics of habitat use. Overall, we show that it is possible to classify animal trajectories based on changes of habitat use similar to geometric segmentation algorithms. We conclude that such an environmentally informed classification of animal trajectories can provide new insights into an individuals' behavior and enables us to make sensible predictions of how suitable areas might be connected by movement in space and time.

  12. SEGMENTATION OF UAV-BASED IMAGES INCORPORATING 3D POINT CLOUD INFORMATION

    Directory of Open Access Journals (Sweden)

    A. Vetrivel

    2015-03-01

    Full Text Available Numerous applications related to urban scene analysis demand automatic recognition of buildings and distinct sub-elements. For example, if LiDAR data is available, only 3D information could be leveraged for the segmentation. However, this poses several risks, for instance, the in-plane objects cannot be distinguished from their surroundings. On the other hand, if only image based segmentation is performed, the geometric features (e.g., normal orientation, planarity are not readily available. This renders the task of detecting the distinct sub-elements of the building with similar radiometric characteristic infeasible. In this paper the individual sub-elements of buildings are recognized through sub-segmentation of the building using geometric and radiometric characteristics jointly. 3D points generated from Unmanned Aerial Vehicle (UAV images are used for inferring the geometric characteristics of roofs and facades of the building. However, the image-based 3D points are noisy, error prone and often contain gaps. Hence the segmentation in 3D space is not appropriate. Therefore, we propose to perform segmentation in image space using geometric features from the 3D point cloud along with the radiometric features. The initial detection of buildings in 3D point cloud is followed by the segmentation in image space using the region growing approach by utilizing various radiometric and 3D point cloud features. The developed method was tested using two data sets obtained with UAV images with a ground resolution of around 1-2 cm. The developed method accurately segmented most of the building elements when compared to the plane-based segmentation using 3D point cloud alone.

  13. Three-dimensional rendering of segmented object using matlab - biomed 2010.

    Science.gov (United States)

    Anderson, Jeffrey R; Barrett, Steven F

    2010-01-01

    The three-dimensional rendering of microscopic objects is a difficult and challenging task that often requires specialized image processing techniques. Previous work has been described of a semi-automatic segmentation process of fluorescently stained neurons collected as a sequence of slice images with a confocal laser scanning microscope. Once properly segmented, each individual object can be rendered and studied as a three-dimensional virtual object. This paper describes the work associated with the design and development of Matlab files to create three-dimensional images from the segmented object data previously mentioned. Part of the motivation for this work is to integrate both the segmentation and rendering processes into one software application, providing a seamless transition from the segmentation tasks to the rendering and visualization tasks. Previously these tasks were accomplished on two different computer systems, windows and Linux. This transition basically limits the usefulness of the segmentation and rendering applications to those who have both computer systems readily available. The focus of this work is to create custom Matlab image processing algorithms for object rendering and visualization, and merge these capabilities to the Matlab files that were developed especially for the image segmentation task. The completed Matlab application will contain both the segmentation and rendering processes in a single graphical user interface, or GUI. This process for rendering three-dimensional images in Matlab requires that a sequence of two-dimensional binary images, representing a cross-sectional slice of the object, be reassembled in a 3D space, and covered with a surface. Additional segmented objects can be rendered in the same 3D space. The surface properties of each object can be varied by the user to aid in the study and analysis of the objects. This inter-active process becomes a powerful visual tool to study and understand microscopic objects.

  14. Intelligent multi-spectral IR image segmentation

    Science.gov (United States)

    Lu, Thomas; Luong, Andrew; Heim, Stephen; Patel, Maharshi; Chen, Kang; Chao, Tien-Hsin; Chow, Edward; Torres, Gilbert

    2017-05-01

    This article presents a neural network based multi-spectral image segmentation method. A neural network is trained on the selected features of both the objects and background in the longwave (LW) Infrared (IR) images. Multiple iterations of training are performed until the accuracy of the segmentation reaches satisfactory level. The segmentation boundary of the LW image is used to segment the midwave (MW) and shortwave (SW) IR images. A second neural network detects the local discontinuities and refines the accuracy of the local boundaries. This article compares the neural network based segmentation method to the Wavelet-threshold and Grab-Cut methods. Test results have shown increased accuracy and robustness of this segmentation scheme for multi-spectral IR images.

  15. POST-HOC SEGMENTATION USING MARKETING RESEARCH

    Directory of Open Access Journals (Sweden)

    CRISTINEL CONSTANTIN

    2012-10-01

    Full Text Available This paper is about an instrumental research conducted in order to compare the information given by two multivariate data analysis used fordividing a population in clusters. These methods are K-means cluster and TwoStep cluster, which are available in SPSS system. Such methods could be used in post-hoc market segmentations, which allow companies to find segments with specific behaviours or attitudes. The research scope is to find which of the two methods is better for market segmentation practice. The outcomes reveal that every method has strong points and weaknesses. These ones are related to the relevance of segments description and the statistic significance of the difference between segments. In this respect, the researchers should compare the results of the named analyses and choose the method which better discriminate between the market segments.

  16. Media segmentation using self-similarity decomposition

    Science.gov (United States)

    Foote, Jonathan T.; Cooper, Matthew L.

    2003-01-01

    We present a framework for analyzing the structure of digital media streams. Though our methods work for video, text, and audio, we concentrate on detecting the structure of digital music files. In the first step, spectral data is used to construct a similarity matrix calculated from inter-frame spectral similarity.The digital audio can be robustly segmented by correlating a kernel along the diagonal of the similarity matrix. Once segmented, spectral statistics of each segment are computed. In the second step,segments are clustered based on the self-similarity of their statistics. This reveals the structure of the digital music in a set of segment boundaries and labels. Finally, the music is summarized by selecting clusters with repeated segments throughout the piece. The summaries can be customized for various applications based on the structure of the original music.

  17. 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.

  18. CDIS: Circle Density Based Iris Segmentation

    Science.gov (United States)

    Gupta, Anand; Kumari, Anita; Kundu, Boris; Agarwal, Isha

    Biometrics is an automated approach of measuring and analysing physical and behavioural characteristics for identity verification. The stability of the Iris texture makes it a robust biometric tool for security and authentication purposes. Reliable Segmentation of Iris is a necessary precondition as an error at this stage will propagate into later stages and requires proper segmentation of non-ideal images having noises like eyelashes, etc. Iris Segmentation work has been done earlier but we feel it lacks in detecting iris in low contrast images, removal of specular reflections, eyelids and eyelashes. Hence, it motivates us to enhance the said parameters. Thus, we advocate a new approach CDIS for Iris segmentation along with new algorithms for removal of eyelashes, eyelids and specular reflections and pupil segmentation. The results obtained have been presented using GAR vs. FAR graphs at the end and have been compared with prior works related to segmentation of iris.

  19. Segmentation of Lung Structures in CT

    DEFF Research Database (Denmark)

    Lo, Pechin Chien Pau

    This thesis proposes and evaluates new algorithms for segmenting various lung structures in computed tomography (CT) images, namely the lungs, airway trees and vessel trees. The main objective of these algorithms is to facilitate a better platform for studying Chronic Obstructive Pulmonary Diseas....... Two approaches for extracting the airway tree using the voxel classification appearance model are proposed: a vessel guided approach and a locally optimal paths approach. The vessel guided approach exploits the fact that all airways are accompanied by arteries of similar orientation....... Segmented airway trees from the algorithms that participate in the study were used to construct the reference standard needed, circumventing the need for labour intensive manual segmentations. Each segmented trees is subdivided into its individual branch segments, where the branch segments are subjected...

  20. Introduction to Space Systems Design and Synthesis

    CERN Document Server

    Aguirre, Miguel A

    2013-01-01

    The definition of all space systems starts with the establishment of its fundamental parameters: requirements to be fulfilled, overall system and satellite design, analysis and design of the critical elements, developmental approach, cost, and schedule. There are only a few texts covering early design of space systems and none of them has been specifically dedicated to it. Furthermore all existing space engineering books concentrate on analysis. None of them deal with space system synthesis – with the interrelations between all the elements of the space system. Introduction to Space Systems concentrates on understanding the interaction between all the forces, both technical and non-technical, which influence the definition of a space system. This book refers to the entire system: space and ground segments, mission objectives as well as to cost, risk, and mission success probabilities. Introduction to Space Systems is divided into two parts. The first part analyzes the process of space system design in an ab...

  1. IFRS 8 Operating Segments - A Closer Look

    OpenAIRE

    Muthupandian, K S

    2008-01-01

    The International Accounting Standards Board issued the International Financial Reporting Standard 8 Operating Segments. Segment information is one of the most vital aspects of financial reporting for investors and other users. The IFRS 8 requires an entity to adopt the ‘management approach’ to reporting on the financial performance of its operating segments. This article presents a closer look of the standard (objective, scope, and disclosures).

  2. Communication with market segments - travel agencies' perspective

    OpenAIRE

    Lorena Bašan; Jasmina Dlačić; Željko Trezner

    2013-01-01

    Purpose – The purpose of this paper is to research the travel agencies’ communication with market segments. Communication with market segments takes into account marketing communication means as well as the implementation of different business orientations. Design – Special emphasis is placed on the use of different marketing communication means and their efficiency. Research also explores business orientation adaptation when approaching different market segments. Methodology – In explo...

  3. ANALYSIS OF BUYING HABITS - WINE SEGMENT

    OpenAIRE

    Samardzija, Luka; Soukup, Domagoj; Kuzmanovic, Sinisa

    2017-01-01

    On a market with high supply offer segmentation cares extremely high importance. Wine is characterized as highly complex product and possibility of segmentation is extremely large. To insure detailed analysis it is essential to take in count all starting points of segmentation. Demographic factor can help with the analysis but wine as a product demands as specific approach as possible to ensure relevant conclusion. Wine promotion and market communication without detailed analysis based on ...

  4. Hierarchical morphological segmentation for image sequence coding

    OpenAIRE

    Salembier Clairon, Philippe Jean; Pardàs Feliu, Montse

    1994-01-01

    This paper deals with a hierarchical morphological segmentation algorithm for image sequence coding. Mathematical morphology is very attractive for this purpose because it efficiently deals with geometrical features such as size, shape, contrast, or connectivity that can be considered as segmentation-oriented features. The algorithm follows a top-down procedure. It first takes into account the global information and produces a coarse segmentation, that is, with a small number of regions. Then...

  5. Segmentation in the brazilian labor market

    OpenAIRE

    Botelho, Fernando; Ponczek, Vladimir Pinheiro

    2007-01-01

    This paper measures the degree of segmentation in the brazilian labor market. Controlling for observable and unobservable characteristics, workers earn more in the formal sector, which supports the segmentation hypothesis. We break down the degree of segmentation by socio-economic attributes to identify the groups where this phenomenon is more prevalent. We investigate the robustness of our findings to the inclusion of self-employed individuals, and apply a two-stage panel probit model using ...

  6. 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

  7. Lifestyle market segmentation - efficiency and ethical issues

    OpenAIRE

    Pilstl, Michaela

    2010-01-01

    Lifestyle market segmentation can be very supportive for a successful marketing strategy of a company. However it is not clear whether lifestyle market segmentation is efficient and ethical or not. Several market segmentation concepts such as Cross-Cultural Consumer Characterization, VALS, PRIZM NE, Mosaic, ConneXions NE and GfK Roper Consumer Styles are analyzed in order to give an extensive overview of the offered concepts. The observation of efficiency issues in regards to market segmentat...

  8. Osmotic and Heat Stress Effects on Segmentation

    OpenAIRE

    Weiss, Julian; Devoto, Stephen H.

    2016-01-01

    During vertebrate embryonic development, early skin, muscle, and bone progenitor populations organize into segments known as somites. Defects in this conserved process of segmentation lead to skeletal and muscular deformities, such as congenital scoliosis, a curvature of the spine caused by vertebral defects. Environmental stresses such as hypoxia or heat shock produce segmentation defects, and significantly increase the penetrance and severity of vertebral defects in genetically susceptible ...

  9. Compliance with Segment Disclosure Initiatives

    DEFF Research Database (Denmark)

    Arya, Anil; Frimor, Hans; Mittendorf, Brian

    2013-01-01

    Regulatory oversight of capital markets has intensified in recent years, with a particular emphasis on expanding financial transparency. A notable instance is efforts by the Financial Accounting Standards Board that push firms to identify and report performance of individual business units...... compliance or mandates strict compliance from firms. Under voluntary compliance, a firm is able to credibly withhold individual segment information from its competitors by disclosing data only at the aggregate firm level. Consistent with regulatory hopes, we show that mandatory compliance enhances welfare...... by increasing transparency and leveling the playing field. However, our analysis also demonstrates that in the long run, if firms are unable to use discretion in reporting to maintain their competitive edge, they may seek more destructive alternatives. Accounting for such concerns, in the long run, voluntary...

  10. Core Recursive Hierarchical Image Segmentation

    Science.gov (United States)

    Tilton, James

    2011-01-01

    The Recursive Hierarchical Image Segmentation (RHSEG) software has been repackaged to provide a version of the RHSEG software that is not subject to patent restrictions and that can be released to the general public through NASA GSFC's Open Source release process. Like the Core HSEG Software Package, this Core RHSEG Software Package also includes a visualization program called HSEGViewer along with a utility program HSEGReader. It also includes an additional utility program called HSEGExtract. The unique feature of the Core RHSEG package is that it is a repackaging of the RHSEG technology designed to specifically avoid the inclusion of the certain software technology. Unlike the Core HSEG package, it includes the recursive portions of the technology, but does not include processing window artifact elimination technology.

  11. 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.

  12. 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.

  13. Polarimetric Segmentation Using Wishart Test Statistic

    DEFF Research Database (Denmark)

    Skriver, Henning; Schou, Jesper; Nielsen, Allan Aasbjerg

    2002-01-01

    ) approach, which is a merging algorithm for single channel SAR images. The polarimetric version described in this paper uses the above-mentioned test statistic for merging. The segmentation algorithm has been applied to polarimetric SAR data from the Danish dual-frequency, airborne polarimetric SAR, EMISAR......A newly developed test statistic for equality of two complex covariance matrices following the complex Wishart distribution and an associated asymptotic probability for the test statistic has been used in a segmentation algorithm. The segmentation algorithm is based on the MUM (merge using moments....... The results show clearly an improved segmentation performance for the full polarimetric algorithm compared to single channel approaches....

  14. VIDEO SEGMENTATION USING A NOVEL LBP DESCRIPTOR

    Directory of Open Access Journals (Sweden)

    Zhongkun He

    2014-08-01

    Full Text Available Video segmentation is the basis for content-based video retrieval, object recognition, object tracking, and video compression. This paper proposes a kind of novel and easy spatial-temporal LBP coding method, using the spatial-temporal 2 × 2 × 2 neighborhood clique to encode the changes in a video. Based on the coding method, a scheme of video segmentation is developed. Compared to the traditional segmentation method, its distinguished advantage is that it does not need to construct the background model and is simple in computation. Experimental results indicate that this new algorithm can give satisfying segmentation results.

  15. Image segmentation using fuzzy LVQ clustering networks

    Science.gov (United States)

    Tsao, Eric Chen-Kuo; Bezdek, James C.; Pal, Nikhil R.

    1992-01-01

    In this note we formulate image segmentation as a clustering problem. Feature vectors extracted from a raw image are clustered into subregions, thereby segmenting the image. A fuzzy generalization of a Kohonen learning vector quantization (LVQ) which integrates the Fuzzy c-Means (FCM) model with the learning rate and updating strategies of the LVQ is used for this task. This network, which segments images in an unsupervised manner, is thus related to the FCM optimization problem. Numerical examples on photographic and magnetic resonance images are given to illustrate this approach to image segmentation.

  16. The ICSI+ Multilingual Sentence Segmentation System

    National Research Council Canada - National Science Library

    Zimmerman, M; Hakkani-Tuer, D; Fung, J; Mirghafori, N; Gottlieb, L; Shriberg, E; Liu, Y

    2006-01-01

    The ICSI+ multilingual sentence segmentation with results for English and Mandarin broadcast news automatic speech recognizer transcriptions represents a joint effort involving ICSI, SRI, and UT Dallas...

  17. 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

  18. 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.

  19. Text segmentation for MRC document compression.

    Science.gov (United States)

    Haneda, Eri; Bouman, Charles A

    2011-06-01

    The mixed raster content (MRC) standard (ITU-T T.44) specifies a framework for document compression which can dramatically improve the compression/quality tradeoff as compared to traditional lossy image compression algorithms. The key to MRC compression is the separation of the document into foreground and background layers, represented as a binary mask. Therefore, the resulting quality and compression ratio of a MRC document encoder is highly dependent upon the segmentation algorithm used to compute the binary mask. In this paper, we propose a novel multiscale segmentation scheme for MRC document encoding based upon the sequential application of two algorithms. The first algorithm, cost optimized segmentation (COS), is a blockwise segmentation algorithm formulated in a global cost optimization framework. The second algorithm, connected component classification (CCC), refines the initial segmentation by classifying feature vectors of connected components using an Markov random field (MRF) model. The combined COS/CCC segmentation algorithms are then incorporated into a multiscale framework in order to improve the segmentation accuracy of text with varying size. In comparisons to state-of-the-art commercial MRC products and selected segmentation algorithms in the literature, we show that the new algorithm achieves greater accuracy of text detection but with a lower false detection rate of nontext features. We also demonstrate that the proposed segmentation algorithm can improve the quality of decoded documents while simultaneously lowering the bit rate.

  20. 3D variational brain tumor segmentation using Dirichlet priors on a clustered feature set.

    Science.gov (United States)

    Popuri, Karteek; Cobzas, Dana; Murtha, Albert; Jägersand, Martin

    2012-07-01

    Brain tumor segmentation is a required step before any radiation treatment or surgery. When performed manually, segmentation is time consuming and prone to human errors. Therefore, there have been significant efforts to automate the process. But, automatic tumor segmentation from MRI data is a particularly challenging task. Tumors have a large diversity in shape and appearance with intensities overlapping the normal brain tissues. In addition, an expanding tumor can also deflect and deform nearby tissue. In our work, we propose an automatic brain tumor segmentation method that addresses these last two difficult problems. We use the available MRI modalities (T1, T1c, T2) and their texture characteristics to construct a multidimensional feature set. Then, we extract clusters which provide a compact representation of the essential information in these features. The main idea in this work is to incorporate these clustered features into the 3D variational segmentation framework. In contrast to previous variational approaches, we propose a segmentation method that evolves the contour in a supervised fashion. The segmentation boundary is driven by the learned region statistics in the cluster space. We incorporate prior knowledge about the normal brain tissue appearance during the estimation of these region statistics. In particular, we use a Dirichlet prior that discourages the clusters from the normal brain region to be in the tumor region. This leads to a better disambiguation of the tumor from brain tissue. We evaluated the performance of our automatic segmentation method on 15 real MRI scans of brain tumor patients, with tumors that are inhomogeneous in appearance, small in size and in proximity to the major structures in the brain. Validation with the expert segmentation labels yielded encouraging results: Jaccard (58%), Precision (81%), Recall (67%), Hausdorff distance (24 mm). Using priors on the brain/tumor appearance, our proposed automatic 3D variational

  1. ACM-based automatic liver segmentation from 3-D CT images by combining multiple atlases and improved mean-shift techniques.

    Science.gov (United States)

    Ji, Hongwei; He, Jiangping; Yang, Xin; Deklerck, Rudi; Cornelis, Jan

    2013-05-01

    In this paper, we present an autocontext model(ACM)-based automatic liver segmentation algorithm, which combines ACM, multiatlases, and mean-shift techniques to segment liver from 3-D CT images. Our algorithm is a learning-based method and can be divided into two stages. At the first stage, i.e., the training stage, ACM is performed to learn a sequence of classifiers in each atlas space (based on each atlas and other aligned atlases). With the use of multiple atlases, multiple sequences of ACM-based classifiers are obtained. At the second stage, i.e., the segmentation stage, the test image will be segmented in each atlas space by applying each sequence of ACM-based classifiers. The final segmentation result will be obtained by fusing segmentation results from all atlas spaces via a multiclassifier fusion technique. Specially, in order to speed up segmentation, given a test image, we first use an improved mean-shift algorithm to perform over-segmentation and then implement the region-based image labeling instead of the original inefficient pixel-based image labeling. The proposed method is evaluated on the datasets of MICCAI 2007 liver segmentation challenge. The experimental results show that the average volume overlap error and the average surface distance achieved by our method are 8.3% and 1.5 m, respectively, which are comparable to the results reported in the existing state-of-the-art work on liver segmentation.

  2. Comparison of the properties of segmented copolyetheresteramids with commercial segmented copolymers

    NARCIS (Netherlands)

    Niesten, M.C.E.J.; Gaymans, R.J.

    2001-01-01

    The thermal (using differential scanning calorimetry), dynamic mechanical (using a dynamic mechanical analyzer), and mechanical properties of segmented copolyetheresteramides with aramid units of uniform length (TT) and poly(tetramethylene oxide) (PTMO) segments were compared to those of commercial

  3. White blood cell counting analysis of blood smear images using various segmentation strategies

    Science.gov (United States)

    Safuan, Syadia Nabilah Mohd; Tomari, Razali; Zakaria, Wan Nurshazwani Wan; Othman, Nurmiza

    2017-09-01

    In white blood cell (WBC) diagnosis, the most crucial measurement parameter is the WBC counting. Such information is widely used to evaluate the effectiveness of cancer therapy and to diagnose several hidden infection within human body. The current practice of manual WBC counting is laborious and a very subjective assessment which leads to the invention of computer aided system (CAS) with rigorous image processing solution. In the CAS counting work, segmentation is the crucial step to ensure the accuracy of the counted cell. The optimal segmentation strategy that can work under various blood smeared image acquisition conditions is remain a great challenge. In this paper, a comparison between different segmentation methods based on color space analysis to get the best counting outcome is elaborated. Initially, color space correction is applied to the original blood smeared image to standardize the image color intensity level. Next, white blood cell segmentation is performed by using combination of several color analysis subtraction which are RGB, CMYK and HSV, and Otsu thresholding. Noises and unwanted regions that present after the segmentation process is eliminated by applying a combination of morphological and Connected Component Labelling (CCL) filter. Eventually, Circle Hough Transform (CHT) method is applied to the segmented image to estimate the number of WBC including the one under the clump region. From the experiment, it is found that G-S yields the best performance.

  4. Design of a highly segmented Endcap at a CLIC detector

    CERN Document Server

    Gerwig, H; Siegrist, N

    2010-01-01

    This technical note describes a possible design for a highly segmented end-cap at a CLIC detector with a strong magnetic field up to 5 Tesla. Reinforcement is horizontal in order to allow an insertion of the muon chambers from the side. Construction issues, assembly questions as well as muon chamber access and support questions have been studied. A FEA analysis to optimize dead space for physics and checking the weakening effect of alignment channels through the end-cap have been performed.

  5. Performance of a highly segmented scintillating fibres electromagnetic calorimeter

    International Nuclear Information System (INIS)

    Asmone, A.; Bertino, M.; Bini, C.; De Zorzi, G.; Diambrini Palazzi, G.; Di Cosimo, G.; Di Domenico, A.; Garufi, F.; Gauzzi, P.; Zanello, D.

    1993-01-01

    A prototype of scintillating fibres electromagnetic calorimeter has been constructed and tested with 2, 4 and 8 GeV electron beams at the CERN PS. The calorimeter modules consist of a Bi-Pb-Sn alloy and scintillating fibres. The fibres are parallel to the modules longer axis, and nearly parallel to the incident electrons direction. The calorimeter has two different segmentation regions of 24x24 mm 2 and 8x24 mm 2 cross area respectively. Results on energy and impact point space resolution are obtained and compared for the two different granularities. (orig.)

  6. Space autonomy as migration of functionality: the mars case

    NARCIS (Netherlands)

    Grant, T.; Bos, A.; Neerincx, M.; Soler, A.O.; Brauer, U.; Wolff, M.

    2006-01-01

    This paper develops Grandjean and Lecouat's insight that spacecraft autonomy can be seen as the migration of functionality from the ground segment to the space segment. Their insight is extended to manned planetary exploration missions and applied to an IT-based crew assistant for supporting manned

  7. A Unique 10 Segment Display for Bengali Numerals

    OpenAIRE

    Azad, Md. Abul Kalam; Sharmeen, Rezwana; Ahmad, Shabbir; Kamruzzaman, S. M.

    2010-01-01

    Segmented display is widely used for efficient display of alphanumeric characters. English numerals are displayed by 7 segment and 16 segment display. The segment size is uniform in this two display architecture. Display architecture using 8, 10, 11, 18 segments have been proposed for Bengali numerals 0...9 yet no display architecture is designed using segments of uniform size and uniform power consumption. In this paper we have proposed a uniform 10 segment architecture for Bengali numerals....

  8. 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.

  9. A Multiatlas Segmentation Using Graph Cuts with Applications to Liver Segmentation in CT Scans

    Science.gov (United States)

    2014-01-01

    An atlas-based segmentation approach is presented that combines low-level operations, an affine probabilistic atlas, and a multiatlas-based segmentation. The proposed combination provides highly accurate segmentation due to registrations and atlas selections based on the regions of interest (ROIs) and coarse segmentations. Our approach shares the following common elements between the probabilistic atlas and multiatlas segmentation: (a) the spatial normalisation and (b) the segmentation method, which is based on minimising a discrete energy function using graph cuts. The method is evaluated for the segmentation of the liver in computed tomography (CT) images. Low-level operations define a ROI around the liver from an abdominal CT. We generate a probabilistic atlas using an affine registration based on geometry moments from manually labelled data. Next, a coarse segmentation of the liver is obtained from the probabilistic atlas with low computational effort. Then, a multiatlas segmentation approach improves the accuracy of the segmentation. Both the atlas selections and the nonrigid registrations of the multiatlas approach use a binary mask defined by coarse segmentation. We experimentally demonstrate that this approach performs better than atlas selections and nonrigid registrations in the entire ROI. The segmentation results are comparable to those obtained by human experts and to other recently published results. PMID:25276219

  10. 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...

  11. Crystalline morphologies in segmented copolymers with hard segments of uniform length

    NARCIS (Netherlands)

    Sauer, Bryan B.; McLean, R. Scott; Gaymans, R.J.; Niesten, M.C.E.J.

    2004-01-01

    The crystal morphological properties of segmented poly(ether ester aramide) elastomers with aromatic hard-segment amide units of uniform length were studied. Four samples with hard-segment fractions ranging from 3.4 to 9 wt % were studied by tapping atomic force microscopy (AFM). For one sample,

  12. Weighting training images by maximizing distribution similarity for supervised segmentation across scanners.

    Science.gov (United States)

    Opbroek, Annegreet van; Vernooij, Meike W; Ikram, M Arfan; Bruijne, Marleen de

    2015-08-01

    Many automatic segmentation methods are based on supervised machine learning. Such methods have proven to perform well, on the condition that they are trained on a sufficiently large manually labeled training set that is representative of the images to segment. However, due to differences between scanners, scanning parameters, and patients such a training set may be difficult to obtain. We present a transfer-learning approach to segmentation by multi-feature voxelwise classification. The presented method can be trained using a heterogeneous set of training images that may be obtained with different scanners than the target image. In our approach each training image is given a weight based on the distribution of its voxels in the feature space. These image weights are chosen as to minimize the difference between the weighted probability density function (PDF) of the voxels of the training images and the PDF of the voxels of the target image. The voxels and weights of the training images are then used to train a weighted classifier. We tested our method on three segmentation tasks: brain-tissue segmentation, skull stripping, and white-matter-lesion segmentation. For all three applications, the proposed weighted classifier significantly outperformed an unweighted classifier on all training images, reducing classification errors by up to 42%. For brain-tissue segmentation and skull stripping our method even significantly outperformed the traditional approach of training on representative training images from the same study as the target image. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Visual Sensor Based Image Segmentation by Fuzzy Classification and Subregion Merge

    Directory of Open Access Journals (Sweden)

    Huidong He

    2017-01-01

    Full Text Available The extraction and tracking of targets in an image shot by visual sensors have been studied extensively. The technology of image segmentation plays an important role in such tracking systems. This paper presents a new approach to color image segmentation based on fuzzy color extractor (FCE. Different from many existing methods, the proposed approach provides a new classification of pixels in a source color image which usually classifies an individual pixel into several subimages by fuzzy sets. This approach shows two unique features: the spatial proximity and color similarity, and it mainly consists of two algorithms: CreateSubImage and MergeSubImage. We apply the FCE to segment colors of the test images from the database at UC Berkeley in the RGB, HSV, and YUV, the three different color spaces. The comparative studies show that the FCE applied in the RGB space is superior to the HSV and YUV spaces. Finally, we compare the segmentation effect with Canny edge detection and Log edge detection algorithms. The results show that the FCE-based approach performs best in the color image segmentation.

  14. AN ADAPTIVE APPROACH FOR SEGMENTATION OF 3D LASER POINT CLOUD

    Directory of Open Access Journals (Sweden)

    Z. Lari

    2012-09-01

    Full Text Available Automatic processing and object extraction from 3D laser point cloud is one of the major research topics in the field of photogrammetry. Segmentation is an essential step in the processing of laser point cloud, and the quality of extracted objects from laser data is highly dependent on the validity of the segmentation results. This paper presents a new approach for reliable and efficient segmentation of planar patches from a 3D laser point cloud. In this method, the neighbourhood of each point is firstly established using an adaptive cylinder while considering the local point density and surface trend. This neighbourhood definition has a major effect on the computational accuracy of the segmentation attributes. In order to efficiently cluster planar surfaces and prevent introducing ambiguities, the coordinates of the origin's projection on each point's best fitted plane are used as the clustering attributes. Then, an octree space partitioning method is utilized to detect and extract peaks from the attribute space. Each detected peak represents a specific cluster of points which are located on a distinct planar surface in the object space. Experimental results show the potential and feasibility of applying this method for segmentation of both airborne and terrestrial laser data.

  15. Fingerprint segmentation based on hidden Markov models

    NARCIS (Netherlands)

    Klein, S.; Bazen, A.M.; Veldhuis, Raymond N.J.

    An important step in fingerprint recognition is segmentation. During segmentation the fingerprint image is decomposed into foreground, background and low-quality regions. The foreground is used in the recognition process, the background is ignored. The low-quality regions may or may not be used,

  16. Storing tooth segments for optimal esthetics

    NARCIS (Netherlands)

    Tuzuner, T.; Turgut, S.; Özen, B.; Kılınç, H.; Bagis, B.

    2016-01-01

    Objective: A fractured whole crown segment can be reattached to its remnant; crowns from extracted teeth may be used as pontics in splinting techniques. We aimed to evaluate the effect of different storage solutions on tooth segment optical properties after different durations. Study design: Sixty

  17. Monosomic analysis reveals duplicated chromosomal segments in ...

    Indian Academy of Sciences (India)

    Monosomic analysis reveals duplicated chromosomal segments in maize genome. MAHESH C. YADAV1,2∗, J. K. S. ... cated chromosomal segments in maize genome. Materials and methods. Development and .... each in chromosomes 2 and 7, while 10 other pairs of du- plicate loci had one copy in chromosome 3 and the ...

  18. Handwriting segmentation of unconstrained Oriya text

    Indian Academy of Sciences (India)

    Based on vertical projection profiles and structural features of Oriya characters, text lines are segmented into words. For character segmentation, at first, the isolated and connected (touching) characters in a word are detected. Using structural, topological and water reservoir concept-based features, characters of the word ...

  19. 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.

  20. Speech Segmentation Using Bayesian Autoregressive Changepoint Detector

    Directory of Open Access Journals (Sweden)

    P. Sovka

    1998-12-01

    Full Text Available This submission is devoted to the study of the Bayesian autoregressive changepoint detector (BCD and its use for speech segmentation. Results of the detector application to autoregressive signals as well as to real speech are given. BCD basic properties are described and discussed. The novel two-step algorithm consisting of cepstral analysis and BCD for automatic speech segmentation is suggested.

  1. Handwriting segmentation of unconstrained Oriya text

    Indian Academy of Sciences (India)

    Segmentation of handwritten text into lines, words and characters is one of the important steps in the handwritten text recognition process. In this paper we propose a water reservoir concept-based scheme for segmentation of unconstrained Oriya handwritten text into individual characters. Here, at first, the text image is ...

  2. Benefit segmentation of the fitness market.

    Science.gov (United States)

    Brown, J D

    1992-01-01

    While considerate attention is being paid to the fitness and wellness needs of people by healthcare and related marketing organizations, little research attention has been directed to identifying the market segments for fitness based upon consumers' perceived benefits of fitness. This article describes three distinct segments of fitness consumers comprising an estimated 50 percent of households. Implications for marketing strategies are also presented.

  3. Congenital segmental dilatation of the colon

    African Journals Online (AJOL)

    Congenital segmental dilatation of the colon is a rare cause of intestinal obstruction in neonates. We report a case of congenital segmental dilatation of the colon and highlight the clinical, radiological, and histopathological features of this entity. Proper surgical treatment was initiated on the basis of preoperative radiological ...

  4. Translocations used to generate chromosome segment duplications ...

    Indian Academy of Sciences (India)

    Supplementary figure 1. (a–i) Putative novel genes created by the breakpoints. Translocation chromosomes are shown with the translocated segment indicated in red and the untranslocated segments in black or blue. Purple arrows indicate whether the chromosome is a donor (arrow pointing up) or a recipient (arrow ...

  5. Image segmentation with a finite element method

    DEFF Research Database (Denmark)

    Bourdin, Blaise

    1999-01-01

    The Mumford-Shah functional for image segmentation is an original approach of the image segmentation problem, based on a minimal energy criterion. Its minimization can be seen as a free discontinuity problem and is based on \\Gamma-convergence and bounded variation functions theories.Some new...... numerical results, computed from both artificial and real images are presented and discussed....

  6. Market Segmentation Using Bayesian Model Based Clustering

    NARCIS (Netherlands)

    Van Hattum, P.

    2009-01-01

    This dissertation deals with two basic problems in marketing, that are market segmentation, which is the grouping of persons who share common aspects, and market targeting, which is focusing your marketing efforts on one or more attractive market segments. For the grouping of persons who share

  7. Segmental blood pressure after total hip replacement

    DEFF Research Database (Denmark)

    Gebuhr, Peter Henrik; Soelberg, M; Henriksen, Jens Henrik

    1992-01-01

    Twenty-nine patients due to have a total hip replacement had their systemic systolic and segmental blood pressures measured prior to operation and 1 and 6 weeks postoperatively. No patients had signs of ischemia. The segmental blood pressure was measured at the ankle and at the toes. A significan...

  8. Unsupervised Retinal Vessel Segmentation Using Combined Filters

    Science.gov (United States)

    Oliveira, Wendeson S.; Teixeira, Joyce Vitor; Ren, Tsang Ing; Cavalcanti, George D. C.; Sijbers, Jan

    2016-01-01

    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. PMID:26919587

  9. 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.

  10. Image segmentation with a finite element method

    DEFF Research Database (Denmark)

    Bourdin, Blaise

    1999-01-01

    The Mumford-Shah functional for image segmentation is an original approach of the image segmentation problem, based on a minimal energy criterion. Its minimization can be seen as a free discontinuity problem and is based on \\Gamma-convergence and bounded variation functions theories.Some new...

  11. 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.

  12. 47 CFR 101.1505 - Segmentation plan.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 5 2010-10-01 2010-10-01 false Segmentation plan. 101.1505 Section 101.1505 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) SAFETY AND SPECIAL RADIO SERVICES FIXED MICROWAVE SERVICES Service and Technical Rules for the 70/80/90 GHz Bands § 101.1505 Segmentation plan. (a) An entity...

  13. Feature-driven model-based segmentation

    Science.gov (United States)

    Qazi, Arish A.; Kim, John; Jaffray, David A.; Pekar, Vladimir

    2011-03-01

    The accurate delineation of anatomical structures is required in many medical image analysis applications. One example is radiation therapy planning (RTP), where traditional manual delineation is tedious, labor intensive, and can require hours of clinician's valuable time. Majority of automated segmentation methods in RTP belong to either model-based or atlas-based approaches. One substantial limitation of model-based segmentation is that its accuracy may be restricted by the uncertainties in image content, specifically when segmenting low-contrast anatomical structures, e.g. soft tissue organs in computed tomography images. In this paper, we introduce a non-parametric feature enhancement filter which replaces raw intensity image data by a high level probabilistic map which guides the deformable model to reliably segment low-contrast regions. The method is evaluated by segmenting the submandibular and parotid glands in the head and neck region and comparing the results to manual segmentations in terms of the volume overlap. Quantitative results show that we are in overall good agreement with expert segmentations, achieving volume overlap of up to 80%. Qualitatively, we demonstrate that we are able to segment low-contrast regions, which otherwise are difficult to delineate with deformable models relying on distinct object boundaries from the original image data.

  14. Segmental neurofibromatosis (NF type-V)

    International Nuclear Information System (INIS)

    Arfan-ur-Bari; Simeen, R.

    2003-01-01

    Segmental neurofibromatosis is a variant of neurofibromatosis in which skin lesions are confined to a circumscribed body segment. A case of a 39-year old man with this condition is presented, who was having multiple soft skin tumours over a localized area of back with no associated cafe au lait spots, auxiliary freckles or lish nodules. Histology confirmed the diagnosis of neurofibroma. (author)

  15. Segmentation of sows in farrowing pens

    DEFF Research Database (Denmark)

    Tu, Gang Jun; Karstoft, Henrik; Pedersen, Lene Juul

    2014-01-01

    The correct segmentation of a foreground object in video recordings is an important task for many surveillance systems. The development of an effective and practical algorithm to segment sows in grayscale video recordings captured under commercial production conditions is described. The segmentat...... to detect and classify the sow behaviours in farrowing pens....

  16. Limb-segment selection in drawing behaviour

    NARCIS (Netherlands)

    Meulenbroek, R G; Rosenbaum, D A; Thomassen, A.J.W.M.; Schomaker, L R

    How do we select combinations of limb segments to carry out physical tasks? Three possible determinants of limb-segment selection are hypothesized here: (1) optimal amplitudes and frequencies of motion for the effectors; (2) preferred movement axes for the effectors; and (3) a tendency to continue

  17. LIMB-SEGMENT SELECTION IN DRAWING BEHAVIOR

    NARCIS (Netherlands)

    MEULENBROEK, RGJ; ROSENBAUM, DA; THOMASSEN, AJWM; SCHOMAKER, LRB; Schomaker, Lambertus

    How do we select combinations of limb segments to carry out physical tasks? Three possible determinants of limb-segment selection are hypothesized here: (1) optimal amplitudes and frequencies of motion for the effectors; (2) preferred movement axes for the effectors; and (3) a tendency to continue

  18. Creating Web Area Segments with Google Analytics

    Science.gov (United States)

    Segments allow you to quickly access data for a predefined set of Sessions or Users, such as government or education users, or sessions in a particular state. You can then apply this segment to any report within the Google Analytics (GA) interface.

  19. FISICO: Fast Image SegmentatIon COrrection.

    Directory of Open Access Journals (Sweden)

    Waldo Valenzuela

    Full Text Available In clinical diagnosis, medical image segmentation plays a key role in the analysis of pathological regions. Despite advances in automatic and semi-automatic segmentation techniques, time-effective correction tools are commonly needed to improve segmentation results. Therefore, these tools must provide faster corrections with a lower number of interactions, and a user-independent solution to reduce the time frame between image acquisition and diagnosis.We present a new interactive method for correcting image segmentations. Our method provides 3D shape corrections through 2D interactions. This approach enables an intuitive and natural corrections of 3D segmentation results. The developed method has been implemented into a software tool and has been evaluated for the task of lumbar muscle and knee joint segmentations from MR images.Experimental results show that full segmentation corrections could be performed within an average correction time of 5.5±3.3 minutes and an average of 56.5±33.1 user interactions, while maintaining the quality of the final segmentation result within an average Dice coefficient of 0.92±0.02 for both anatomies. In addition, for users with different levels of expertise, our method yields a correction time and number of interaction decrease from 38±19.2 minutes to 6.4±4.3 minutes, and 339±157.1 to 67.7±39.6 interactions, respectively.

  20. FISICO: Fast Image SegmentatIon COrrection.

    Science.gov (United States)

    Valenzuela, Waldo; Ferguson, Stephen J; Ignasiak, Dominika; Diserens, Gaëlle; Häni, Levin; Wiest, Roland; Vermathen, Peter; Boesch, Chris; Reyes, Mauricio

    2016-01-01

    In clinical diagnosis, medical image segmentation plays a key role in the analysis of pathological regions. Despite advances in automatic and semi-automatic segmentation techniques, time-effective correction tools are commonly needed to improve segmentation results. Therefore, these tools must provide faster corrections with a lower number of interactions, and a user-independent solution to reduce the time frame between image acquisition and diagnosis. We present a new interactive method for correcting image segmentations. Our method provides 3D shape corrections through 2D interactions. This approach enables an intuitive and natural corrections of 3D segmentation results. The developed method has been implemented into a software tool and has been evaluated for the task of lumbar muscle and knee joint segmentations from MR images. Experimental results show that full segmentation corrections could be performed within an average correction time of 5.5±3.3 minutes and an average of 56.5±33.1 user interactions, while maintaining the quality of the final segmentation result within an average Dice coefficient of 0.92±0.02 for both anatomies. In addition, for users with different levels of expertise, our method yields a correction time and number of interaction decrease from 38±19.2 minutes to 6.4±4.3 minutes, and 339±157.1 to 67.7±39.6 interactions, respectively.

  1. Convolutional Neural Networks for SAR Image Segmentation

    DEFF Research Database (Denmark)

    Malmgren-Hansen, David; Nobel-Jørgensen, Morten

    2015-01-01

    Segmentation of Synthetic Aperture Radar (SAR) images has several uses, but it is a difficult task due to a number of properties related to SAR images. In this article we show how Convolutional Neural Networks (CNNs) can easily be trained for SAR image segmentation with good results. Besides...

  2. Gene expression suggests double-segmental and single-segmental patterning mechanisms during posterior segment addition in the beetle Tribolium castaneum.

    Science.gov (United States)

    Janssen, Ralf

    2014-01-01

    In the model arthropod Drosophila, all segments are patterned simultaneously in the blastoderm. In most other arthropods, however, posterior segments are added sequentially from a posterior segment addition zone. Posterior addition of single segments likely represents the ancestral mode of arthropod segmentation, although in Drosophila, segments are patterned in pairs by the pair-rule genes. It has been shown that in the new model insect, the beetle Tribolium, a segmentation clock operates that apparently patterns all segments in pairs as well. Here, I report on the expression of the segment polarity gene H15/midline in Tribolium. In the anterior embryo, segmental stripes of H15 appear in pairs, but in the posterior of the embryo stripes appear in a single-segmental periodicity. This implies that either two completely different segmentation-mechanisms may act in the germ band of Tribolium, that the segmentation clock changes its periodicity during development, or that the speed in which posterior segments are patterned changes. In any case, the data suggest the presence of another (or modified), yet undiscovered, mechanism of posterior segment addition in one of the best-understood arthropod models. The finding of a hitherto unrecognized segmentation mechanism in Tribolium may have major implications for the understanding of the origin of segmentation mechanisms, including the origin of pair rule patterning. It also calls for (re)-investigation of posterior segment addition in Tribolium and other previously studied arthropod models.

  3. A holistic image segmentation framework for cloud detection and extraction

    Science.gov (United States)

    Shen, Dan; Xu, Haotian; Blasch, Erik; Horvath, Gregory; Pham, Khanh; Zheng, Yufeng; Ling, Haibin; Chen, Genshe

    2013-05-01

    Atmospheric clouds are commonly encountered phenomena affecting visual tracking from air-borne or space-borne sensors. Generally clouds are difficult to detect and extract because they are complex in shape and interact with sunlight in a complex fashion. In this paper, we propose a clustering game theoretic image segmentation based approach to identify, extract, and patch clouds. In our framework, the first step is to decompose a given image containing clouds. The problem of image segmentation is considered as a "clustering game". Within this context, the notion of a cluster is equivalent to a classical equilibrium concept from game theory, as the game equilibrium reflects both the internal and external (e.g., two-player) cluster conditions. To obtain the evolutionary stable strategies, we explore three evolutionary dynamics: fictitious play, replicator dynamics, and infection and immunization dynamics (InImDyn). Secondly, we use the boundary and shape features to refine the cloud segments. This step can lower the false alarm rate. In the third step, we remove the detected clouds and patch the empty spots by performing background recovery. We demonstrate our cloud detection framework on a video clip provides supportive results.

  4. MR PROSTATE SEGMENTATION VIA DISTRIBUTED DISCRIMINATIVE DICTIONARY (DDD) LEARNING.

    Science.gov (United States)

    Guo, Yanrong; Zhan, Yiqiang; Gao, Yaozong; Jiang, Jianguo; Shen, Dinggang

    2013-01-01

    Segmenting prostate from MR images is important yet challenging. Due to non-Gaussian distribution of prostate appearances in MR images, the popular active appearance model (AAM) has its limited performance. Although the newly developed sparse dictionary learning method[1, 2] can model the image appearance in a non-parametric fashion, the learned dictionaries still lack the discriminative power between prostate and non-prostate tissues, which is critical for accurate prostate segmentation. In this paper, we propose to integrate deformable model with a novel learning scheme, namely the Distributed Discriminative Dictionary ( DDD ) learning, which can capture image appearance in a non-parametric and discriminative fashion. In particular, three strategies are designed to boost the tissue discriminative power of DDD. First , minimum Redundancy Maximum Relevance (mRMR) feature selection is performed to constrain the dictionary learning in a discriminative feature space. Second , linear discriminant analysis (LDA) is employed to assemble residuals from different dictionaries for optimal separation between prostate and non-prostate tissues. Third , instead of learning the global dictionaries, we learn a set of local dictionaries for the local regions (each with small appearance variations) along prostate boundary, thus achieving better tissue differentiation locally. In the application stage, DDDs will provide the appearance cues to robustly drive the deformable model onto the prostate boundary. Experiments on 50 MR prostate images show that our method can yield a Dice Ratio of 88% compared to the manual segmentations, and have 7% improvement over the conventional AAM.

  5. A Hybrid Technique for Medical Image Segmentation

    Directory of Open Access Journals (Sweden)

    Alamgir Nyma

    2012-01-01

    Full Text Available Medical image segmentation is an essential and challenging aspect in computer-aided diagnosis and also in pattern recognition research. This paper proposes a hybrid method for magnetic resonance (MR image segmentation. We first remove impulsive noise inherent in MR images by utilizing a vector median filter. Subsequently, Otsu thresholding is used as an initial coarse segmentation method that finds the homogeneous regions of the input image. Finally, an enhanced suppressed fuzzy c-means is used to partition brain MR images into multiple segments, which employs an optimal suppression factor for the perfect clustering in the given data set. To evaluate the robustness of the proposed approach in noisy environment, we add different types of noise and different amount of noise to T1-weighted brain MR images. Experimental results show that the proposed algorithm outperforms other FCM based algorithms in terms of segmentation accuracy for both noise-free and noise-inserted MR images.

  6. 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...... manner. In a first phase, a coarse estimate of the overall spine alignment and the vertebra locations is computed using a shape model sampling scheme. These samples are used to initialize a second phase of active shape model search, under a nonlinear model of vertebra appearance. The search...... 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...

  7. A benchmark study of automated intra-retinal cyst segmentation algorithms using optical coherence tomography B-scans.

    Science.gov (United States)

    Girish, G N; Anima, V A; Kothari, Abhishek R; Sudeep, P V; Roychowdhury, Sohini; Rajan, Jeny

    2018-01-01

    Retinal cysts are formed by accumulation of fluid in the retina caused by leakages from inflammation or vitreous fractures. Analysis of the retinal cystic spaces holds significance in detection and treatment of several ocular diseases like age-related macular degeneration, diabetic macular edema etc. Thus, segmentation of intra-retinal cysts and quantification of cystic spaces are vital for retinal pathology and severity detection. In the recent years, automated segmentation of intra-retinal cysts using optical coherence tomography B-scans has gained significant importance in the field of retinal image analysis. The objective of this paper is to compare different intra-retinal cyst segmentation algorithms for comparative analysis and benchmarking purposes. In this work, we employ a modular approach for standardizing the different segmentation algorithms. Further, we analyze the variations in automated cyst segmentation performances and method scalability across image acquisition systems by using the publicly available cyst segmentation challenge dataset (OPTIMA cyst segmentation challenge). Several key automated methods are comparatively analyzed using quantitative and qualitative experiments. Our analysis demonstrates the significance of variations in signal-to-noise ratio (SNR), retinal layer morphology and post-processing steps on the automated cyst segmentation processes. This benchmarking study provides insights towards the scalability of automated processes across vendor-specific imaging modalities to provide guidance for retinal pathology diagnostics and treatment processes. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Implementation and assessment of diffusion-weighted partial Fourier readout-segmented echo-planar imaging.

    Science.gov (United States)

    Frost, Robert; Porter, David A; Miller, Karla L; Jezzard, Peter

    2012-08-01

    Single-shot echo-planar imaging has been used widely in diffusion magnetic resonance imaging due to the difficulties in correcting motion-induced phase corruption in multishot data. Readout-segmented EPI has addressed the multishot problem by introducing a two-dimensional nonlinear navigator correction with online reacquisition of uncorrectable data to enable acquisition of high-resolution diffusion data with reduced susceptibility artifact and T*(2) blurring. The primary shortcoming of readout-segmented EPI in its current form is its long acquisition time (longer than similar resolution single-shot echo-planar imaging protocols by approximately the number of readout segments), which limits the number of diffusion directions. By omitting readout segments at one side of k-space and using partial Fourier reconstruction, readout-segmented EPI imaging times could be reduced. In this study, the effects of homodyne and projection onto convex sets reconstructions on estimates of the fractional anisotropy, mean diffusivity, and diffusion orientation in fiber tracts and raw T(2)- and trace-weighted signal are compared, along with signal-to-noise ratio results. It is found that projections onto convex sets reconstruction with 3/5 segments in a 2 mm isotropic diffusion tensor image acquisition and 9/13 segments in a 0.9 × 0.9 × 4.0 mm(3) diffusion-weighted image acquisition provide good fidelity relative to the full k-space parameters. This allows application of readout-segmented EPI to tractography studies, and clinical stroke and oncology protocols. Copyright © 2011 Wiley-Liss, Inc.

  9. Vessel segmentation in screening mammograms

    Science.gov (United States)

    Mordang, J. J.; Karssemeijer, N.

    2015-03-01

    Blood vessels are a major cause of false positives in computer aided detection systems for the detection of breast cancer. Therefore, the purpose of this study is to construct a framework for the segmentation of blood vessels in screening mammograms. The proposed framework is based on supervised learning using a cascade classifier. This cascade classifier consists of several stages where in each stage a GentleBoost classifier is trained on Haar-like features. A total of 30 cases were included in this study. In each image, vessel pixels were annotated by selecting pixels on the centerline of the vessel, control samples were taken by annotating a region without any visible vascular structures. This resulted in a total of 31,000 pixels marked as vascular and over 4 million control pixels. After training, the classifier assigns a vesselness likelihood to the pixels. The proposed framework was compared to three other vessel enhancing methods, i) a vesselness filter, ii) a gaussian derivative filter, and iii) a tubeness filter. The methods were compared in terms of area under the receiver operating characteristics curves, the Az values. The Az value of the cascade approach is 0:85. This is superior to the vesselness, Gaussian, and tubeness methods, with Az values of 0:77, 0:81, and 0:78, respectively. From these results, it can be concluded that our proposed framework is a promising method for the detection of vessels in screening mammograms.

  10. SEGMENTATION OF SME PORTFOLIO IN BANKING SYSTEM

    Directory of Open Access Journals (Sweden)

    Namolosu Simona Mihaela

    2013-07-01

    Full Text Available The Small and Medium Enterprises (SMEs represent an important target market for commercial Banks. In this respect, finding the best methods for designing and implementing the optimal marketing strategies (for this target are a continuous concern for the marketing specialists and researchers from the banking system; the purpose is to find the most suitable service model for these companies. SME portfolio of a bank is not homogeneous, different characteristics and behaviours being identified. The current paper reveals empirical evidence about SME portfolio characteristics and segmentation methods used in banking system. Its purpose is to identify if segmentation has an impact in finding the optimal marketing strategies and service model and if this hypothesis might be applicable for any commercial bank, irrespective of country/ region. Some banks are segmenting the SME portfolio by a single criterion: the annual company (official turnover; others are considering also profitability and other financial indicators of the company. In some cases, even the banking behaviour becomes a criterion. For all cases, creating scenarios with different thresholds and estimating the impact in profitability and volumes are two mandatory steps in establishing the final segmentation (criteria matrix. Details about each of these segmentation methods may be found in the paper. Testing the final matrix of criteria is also detailed, with the purpose of making realistic estimations. Example for lending products is provided; the product offer is presented as responding to needs of targeted sub segment and therefore being correlated with the sub segment characteristics. Identifying key issues and trends leads to further action plan proposal. Depending on overall strategy and commercial target of the bank, the focus may shift, one or more sub segments becoming high priority (for acquisition/ activation/ retention/ cross sell/ up sell/ increase profitability etc., while

  11. Order and chaos in the rotation and revolution of two massive line segments.

    Science.gov (United States)

    Blaikie, Andrew; Saines, Alex D; Schmitthenner, Matthew; Lankford, Maggie; Pasteur, R Drew; Lindner, John F

    2014-04-01

    As a generalization of Newton's two body problem, we explore the dynamics of two massive line segments interacting gravitationally. The extension of each line segment or slash (/) provides extra degrees of freedom that enable the interplay between rotation and revolution in an especially simple example. This slash-slash (//) body problem can thereby elucidate the dynamics of nonspherical space structures, from asteroids to space stations. Fortunately, as we show, Newton's laws imply exact algebraic expressions for the force and torque between the slashes, and this greatly facilitates analysis. The diverse dynamics include a stable synchronous orbit, families of unstable periodic orbits, generic chaotic orbits, and spin-orbit coupling that can unbind the slashes. In particular, retrograde orbits where the slashes spin opposite to their orbits are stable, with regular dynamics and smooth parameter spaces, while prograde orbits are unstable, with chaotic dynamics and fractal parameter spaces.

  12. Cerebrospinal fluid space alterations in melancholic depression.

    Directory of Open Access Journals (Sweden)

    Esther Via

    Full Text Available Melancholic depression is a biologically homogeneous clinical entity in which structural brain alterations have been described. Interestingly, reports of structural alterations in melancholia include volume increases in Cerebro-Spinal Fluid (CSF spaces. However, there are no previous reports of CSF volume alterations using automated whole-brain voxel-wise approaches, as tissue classification algorithms have been traditionally regarded as less reliable for CSF segmentation. Here we aimed to assess CSF volumetric alterations in melancholic depression and their clinical correlates by means of a novel segmentation algorithm ('new segment', as implemented in the software Statistical Parametric Mapping-SPM8, incorporating specific features that may improve CSF segmentation. A three-dimensional Magnetic Resonance Image (MRI was obtained from seventy patients with melancholic depression and forty healthy control subjects. Although imaging data were pre-processed with the 'new segment' algorithm, in order to obtain a comparison with previous segmentation approaches, tissue segmentation was also performed with the 'unified segmentation' approach. Melancholic patients showed a CSF volume increase in the region of the left Sylvian fissure, and a CSF volume decrease in the subarachnoid spaces surrounding medial and lateral parietal cortices. Furthermore, CSF increases in the left Sylvian fissure were negatively correlated with the reduction percentage of depressive symptoms at discharge. None of these results were replicated with the 'unified segmentation' approach. By contrast, between-group differences in the left Sylvian fissure were replicated with a non-automated quantification of the CSF content of this region. Left Sylvian fissure alterations reported here are in agreement with previous findings from non-automated CSF assessments, and also with other reports of gray and white matter insular alterations in depressive samples using automated approaches

  13. MIN-CUT BASED SEGMENTATION OF AIRBORNE LIDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    S. Ural

    2012-07-01

    Full Text Available Introducing an organization to the unstructured point cloud before extracting information from airborne lidar data is common in many applications. Aggregating the points with similar features into segments in 3-D which comply with the nature of actual objects is affected by the neighborhood, scale, features and noise among other aspects. In this study, we present a min-cut based method for segmenting the point cloud. We first assess the neighborhood of each point in 3-D by investigating the local geometric and statistical properties of the candidates. Neighborhood selection is essential since point features are calculated within their local neighborhood. Following neighborhood determination, we calculate point features and determine the clusters in the feature space. We adapt a graph representation from image processing which is especially used in pixel labeling problems and establish it for the unstructured 3-D point clouds. The edges of the graph that are connecting the points with each other and nodes representing feature clusters hold the smoothness costs in the spatial domain and data costs in the feature domain. Smoothness costs ensure spatial coherence, while data costs control the consistency with the representative feature clusters. This graph representation formalizes the segmentation task as an energy minimization problem. It allows the implementation of an approximate solution by min-cuts for a global minimum of this NP hard minimization problem in low order polynomial time. We test our method with airborne lidar point cloud acquired with maximum planned post spacing of 1.4 m and a vertical accuracy 10.5 cm as RMSE. We present the effects of neighborhood and feature determination in the segmentation results and assess the accuracy and efficiency of the implemented min-cut algorithm as well as its sensitivity to the parameters of the smoothness and data cost functions. We find that smoothness cost that only considers simple distance

  14. Automatic Traffic Sign Detection and Recognition Using Colour Segmentation and Shape Identification

    Directory of Open Access Journals (Sweden)

    Horak Karel

    2016-01-01

    Full Text Available The paper describes a colour-based segmentation method of European traffic signs for detection in an image and a feature-based recognition method for categorizing them into given classes. At first, we have performed analysis of several well-known colour spaces as the RGB, HSV and YCbCr often used for segmentation purposes. The HSV colour space has been chosen as the most convenient for segmentation step and colour-based models of traffic signs representatives were created. Next, the fast radial symmetry (FRS detection method and the Harris corner detector were used to recognize circles, triangles and squares as main geometrical shapes of the traffic signs. For these purposes a new gallery of real-life images containing traffic signs has been created and analysed. Overall efficiency of our recognition method is approx. 93 % on our gallery and is usable for real-time implementations.

  15. Cavity contour segmentation in chest radiographs using supervised learning and dynamic programming.

    Science.gov (United States)

    Maduskar, Pragnya; Hogeweg, Laurens; de Jong, Pim A; Peters-Bax, Liesbeth; Dawson, Rodney; Ayles, Helen; Sánchez, Clara I; van Ginneken, Bram

    2014-07-01

    Efficacy of tuberculosis (TB) treatment is often monitored using chest radiography. Monitoring size of cavities in pulmonary tuberculosis is important as the size predicts severity of the disease and its persistence under therapy predicts relapse. The authors present a method for automatic cavity segmentation in chest radiographs. A two stage method is proposed to segment the cavity borders, given a user defined seed point close to the center of the cavity. First, a supervised learning approach is employed to train a pixel classifier using texture and radial features to identify the border pixels of the cavity. A likelihood value of belonging to the cavity border is assigned to each pixel by the classifier. The authors experimented with four different classifiers:k-nearest neighbor (kNN), linear discriminant analysis (LDA), GentleBoost (GB), and random forest (RF). Next, the constructed likelihood map was used as an input cost image in the polar transformed image space for dynamic programming to trace the optimal maximum cost path. This constructed path corresponds to the segmented cavity contour in image space. The method was evaluated on 100 chest radiographs (CXRs) containing 126 cavities. The reference segmentation was manually delineated by an experienced chest radiologist. An independent observer (a chest radiologist) also delineated all cavities to estimate interobserver variability. Jaccard overlap measure Ω was computed between the reference segmentation and the automatic segmentation; and between the reference segmentation and the independent observer's segmentation for all cavities. A median overlap Ω of 0.81 (0.76 ± 0.16), and 0.85 (0.82 ± 0.11) was achieved between the reference segmentation and the automatic segmentation, and between the segmentations by the two radiologists, respectively. The best reported mean contour distance and Hausdorff distance between the reference and the automatic segmentation were, respectively, 2.48 ± 2.19 and 8.32

  16. Cavity contour segmentation in chest radiographs using supervised learning and dynamic programming

    International Nuclear Information System (INIS)

    Maduskar, Pragnya; Hogeweg, Laurens; Sánchez, Clara I.; Ginneken, Bram van; Jong, Pim A. de; Peters-Bax, Liesbeth; Dawson, Rodney; Ayles, Helen

    2014-01-01

    Purpose: Efficacy of tuberculosis (TB) treatment is often monitored using chest radiography. Monitoring size of cavities in pulmonary tuberculosis is important as the size predicts severity of the disease and its persistence under therapy predicts relapse. The authors present a method for automatic cavity segmentation in chest radiographs. Methods: A two stage method is proposed to segment the cavity borders, given a user defined seed point close to the center of the cavity. First, a supervised learning approach is employed to train a pixel classifier using texture and radial features to identify the border pixels of the cavity. A likelihood value of belonging to the cavity border is assigned to each pixel by the classifier. The authors experimented with four different classifiers:k-nearest neighbor (kNN), linear discriminant analysis (LDA), GentleBoost (GB), and random forest (RF). Next, the constructed likelihood map was used as an input cost image in the polar transformed image space for dynamic programming to trace the optimal maximum cost path. This constructed path corresponds to the segmented cavity contour in image space. Results: The method was evaluated on 100 chest radiographs (CXRs) containing 126 cavities. The reference segmentation was manually delineated by an experienced chest radiologist. An independent observer (a chest radiologist) also delineated all cavities to estimate interobserver variability. Jaccard overlap measure Ω was computed between the reference segmentation and the automatic segmentation; and between the reference segmentation and the independent observer's segmentation for all cavities. A median overlap Ω of 0.81 (0.76 ± 0.16), and 0.85 (0.82 ± 0.11) was achieved between the reference segmentation and the automatic segmentation, and between the segmentations by the two radiologists, respectively. The best reported mean contour distance and Hausdorff distance between the reference and the automatic segmentation were

  17. 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)

  18. 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.

  19. Bringing Gravity to Space

    Science.gov (United States)

    Norsk, P.; Shelhamer, M.

    2016-01-01

    This panel will present NASA's plans for ongoing and future research to define the requirements for Artificial Gravity (AG) as a countermeasure against the negative health effects of long-duration weightlessness. AG could mitigate the gravity-sensitive effects of spaceflight across a host of physiological systems. Bringing gravity to space could mitigate the sensorimotor and neuro-vestibular disturbances induced by G-transitions upon reaching a planetary body, and the cardiovascular deconditioning and musculoskeletal weakness induced by weightlessness. Of particular interest for AG during deep-space missions is mitigation of the Visual Impairment Intracranial Pressure (VIIP) syndrome that the majority of astronauts exhibit in space to varying degrees, and which presumably is associated with weightlessness-induced fluid shift from lower to upper body segments. AG could be very effective for reversing the fluid shift and thus help prevent VIIP. The first presentation by Dr. Charles will summarize some of the ground-based and (very little) space-based research that has been conducted on AG by the various space programs. Dr. Paloski will address the use of AG during deep-space exploration-class missions and describe the different AG scenarios such as intra-vehicular, part-of-vehicle, or whole-vehicle centrifugations. Dr. Clement will discuss currently planned NASA research as well as how to coordinate future activities among NASA's international partners. Dr. Barr will describe some possible future plans for using space- and ground-based partial-G analogs to define the relationship between physiological responses and G levels between 0 and 1. Finally, Dr. Stenger will summarize how the human cardiovascular system could benefit from intermittent short-radius centrifugations during long-duration missions.

  20. Sobolev spaces

    CERN Document Server

    Adams, Robert A

    2003-01-01

    Sobolev Spaces presents an introduction to the theory of Sobolev Spaces and other related spaces of function, also to the imbedding characteristics of these spaces. This theory is widely used in pure and Applied Mathematics and in the Physical Sciences.This second edition of Adam''s ''classic'' reference text contains many additions and much modernizing and refining of material. The basic premise of the book remains unchanged: Sobolev Spaces is intended to provide a solid foundation in these spaces for graduate students and researchers alike.* Self-contained and accessible for readers in other disciplines.* Written at elementary level making it accessible to graduate students.

  1. Sacred Space.

    Science.gov (United States)

    Adelstein, Pamela

    2018-01-01

    A space can be sacred, providing those who inhabit a particular space with sense of transcendence-being connected to something greater than oneself. The sacredness may be inherent in the space, as for a religious institution or a serene place outdoors. Alternatively, a space may be made sacred by the people within it and events that occur there. As medical providers, we have the opportunity to create sacred space in our examination rooms and with our patient interactions. This sacred space can be healing to our patients and can bring us providers opportunities for increased connection, joy, and gratitude in our daily work.

  2. Transcriptional control in the segmentation gene network of Drosophila.

    Science.gov (United States)

    Schroeder, Mark D; Pearce, Michael; Fak, John; Fan, HongQing; Unnerstall, Ulrich; Emberly, Eldon; Rajewsky, Nikolaus; Siggia, Eric D; Gaul, Ulrike

    2004-09-01

    The segmentation gene network of Drosophila consists of maternal and zygotic factors that generate, by transcriptional (cross-) regulation, expression patterns of increasing complexity along the anterior-posterior axis of the embryo. Using known binding site information for maternal and zygotic gap transcription factors, the computer algorithm Ahab recovers known segmentation control elements (modules) with excellent success and predicts many novel modules within the network and genome-wide. We show that novel module predictions are highly enriched in the network and typically clustered proximal to the promoter, not only upstream, but also in intronic space and downstream. When placed upstream of a reporter gene, they consistently drive patterned blastoderm expression, in most cases faithfully producing one or more pattern elements of the endogenous gene. Moreover, we demonstrate for the entire set of known and newly validated modules that Ahab's prediction of binding sites correlates well with the expression patterns produced by the modules, revealing basic rules governing their composition. Specifically, we show that maternal factors consistently act as activators and that gap factors act as repressors, except for the bimodal factor Hunchback. Our data suggest a simple context-dependent rule for its switch from repressive to activating function. Overall, the composition of modules appears well fitted to the spatiotemporal distribution of their positive and negative input factors. Finally, by comparing Ahab predictions with different categories of transcription factor input, we confirm the global regulatory structure of the segmentation gene network, but find odd skipped behaving like a primary pair-rule gene. The study expands our knowledge of the segmentation gene network by increasing the number of experimentally tested modules by 50%. For the first time, the entire set of validated modules is analyzed for binding site composition under a uniform set of

  3. Transcriptional control in the segmentation gene network of Drosophila.

    Directory of Open Access Journals (Sweden)

    Mark D Schroeder

    2004-09-01

    Full Text Available The segmentation gene network of Drosophila consists of maternal and zygotic factors that generate, by transcriptional (cross- regulation, expression patterns of increasing complexity along the anterior-posterior axis of the embryo. Using known binding site information for maternal and zygotic gap transcription factors, the computer algorithm Ahab recovers known segmentation control elements (modules with excellent success and predicts many novel modules within the network and genome-wide. We show that novel module predictions are highly enriched in the network and typically clustered proximal to the promoter, not only upstream, but also in intronic space and downstream. When placed upstream of a reporter gene, they consistently drive patterned blastoderm expression, in most cases faithfully producing one or more pattern elements of the endogenous gene. Moreover, we demonstrate for the entire set of known and newly validated modules that Ahab's prediction of binding sites correlates well with the expression patterns produced by the modules, revealing basic rules governing their composition. Specifically, we show that maternal factors consistently act as activators and that gap factors act as repressors, except for the bimodal factor Hunchback. Our data suggest a simple context-dependent rule for its switch from repressive to activating function. Overall, the composition of modules appears well fitted to the spatiotemporal distribution of their positive and negative input factors. Finally, by comparing Ahab predictions with different categories of transcription factor input, we confirm the global regulatory structure of the segmentation gene network, but find odd skipped behaving like a primary pair-rule gene. The study expands our knowledge of the segmentation gene network by increasing the number of experimentally tested modules by 50%. For the first time, the entire set of validated modules is analyzed for binding site composition under a

  4. Performance Analysis of Segmentation of Hyperspectral Images Based on Color Image Segmentation

    Directory of Open Access Journals (Sweden)

    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.

  5. 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

  6. Hydrophilic segmented block copolymers based on poly(ethylene oxide)

    NARCIS (Netherlands)

    Husken, D.

    2006-01-01

    Segmented block copolymers consist of alternating flexible segments and crystallisable rigid segments. The flexible segments have a low glass transition temperature and are used to obtain flexible materials. The rigid segments can crystallise and act as thermal-reversible physical crosslinks, giving

  7. Multi-Scale Singularity Trees: Soft-Linked Scale-Space Hierarchies

    DEFF Research Database (Denmark)

    Somchaipeng, Kerawit; Sporring, Jon; Kreiborg, Sven

    2005-01-01

    We consider images as manifolds embedded in a hybrid of a high dimensional space of coordinates and features. Using the proposed energy functional and mathematical landmarks, images are partitioned into segments. The nesting of image segments occurring at catastrophe points in the scale-space is ...

  8. High-resolution satellite image segmentation using Hölder exponents

    Indian Academy of Sciences (India)

    1Regional Remote Sensing Service Centre, Indian Space Research Organization, IIT Campus,. Kharagpur 721 ... The watershed segmentation methods (Vincent .... it does not require any prior information about the pixel intensity. This work attempts to describe the textures of high-resolution images using Hölder exponent.

  9. Using GOMS and NASA-TLX to Evaluate Human-Computer Interaction Process in Interactive Segmentation

    NARCIS (Netherlands)

    Ramkumar, A.; Stappers, P.J.; Niessen, W.J.; Adebahr, S; Schimek-Jasch, T; Nestle, U; Song, Y.

    2016-01-01

    HCI plays an important role in interactive medical image segmentation. The Goals, Operators, Methods, and Selection rules (GOMS) model and the National Aeronautics and Space Administration Task Load Index (NASA-TLX) questionnaire are different methods that are often used to evaluate the HCI

  10. Optimization of segment weight using simulated dynamics algorithm for beamlet-based IMRT

    International Nuclear Information System (INIS)

    Chen Bingzhou; Hou Qing

    2007-01-01

    With accurate calculation algorithms in inverse planning for beamlet-based intensity modulated radiotherapy (IMRT), it takes time to calculate the dose matrix, which represents the dose distribution of each beamlet element to each voxel for unit fluence. To reduce the calculation time, coarse or approximate algorithms are often a choice, but this results in a final dose distribution that cannot reflect the real value. In addition, it is necessary to test if a coarse algorithm is capable of calculating the dose matrix of beamlets. In this work, simulated dynamics optimization algorithm was applied to optimize the segment weight to minish the dose error from the dose matrix calculation. After calculating the dose matrix by ray-tracing algorithm which takes into account just the primary component of absorbed dose, the original beam profile intensity distribution was optimized by using the simulated dynamics algorithm. Before segmentation, the even-spaced algorithm and genetic algorithm were applied in clustering. The dose distribution of every segment was calculated accurately by using convolution-superposition algorithm, and the weight of any voxel was in inverse proportion to the voxel number of the PTV or OAR it belonged. The segment weight was optimized by using the simulated dynamics algorithm. By comparing the dose distributions before and after optimization of segment weight, one finds that the dose distribution is improved obviously., It was also found that some segments which contained fewer beamlets or lower weight value could be omitted because the decay of dose distribution could be improved by re-optimizing the segment weight, and that some segments could be omitted by re-optimizing the segment weight during the process of beamlet-based IMRT. (authors)

  11. A Kalman Filtering Perspective for Multiatlas Segmentation.

    Science.gov (United States)

    Gao, Yi; Zhu, Liangjia; Cates, Joshua; MacLeod, Rob S; Bouix, Sylvain; Tannenbaum, Allen

    In multiatlas segmentation, one typically registers several atlases to the novel image, and their respective segmented label images are transformed and fused to form the final segmentation. In this work, we provide a new dynamical system perspective for multiatlas segmentation, inspired by the following fact: The transformation that aligns the current atlas to the novel image can be not only computed by direct registration but also inferred from the transformation that aligns the previous atlas to the image together with the transformation between the two atlases. This process is similar to the global positioning system on a vehicle, which gets position by inquiring from the satellite and by employing the previous location and velocity-neither answer in isolation being perfect. To solve this problem, a dynamical system scheme is crucial to combine the two pieces of information; for example, a Kalman filtering scheme is used. Accordingly, in this work, a Kalman multiatlas segmentation is proposed to stabilize the global/affine registration step. The contributions of this work are twofold. First, it provides a new dynamical systematic perspective for standard independent multiatlas registrations, and it is solved by Kalman filtering. Second, with very little extra computation, it can be combined with most existing multiatlas segmentation schemes for better registration/segmentation accuracy.

  12. 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

  13. A Kalman Filtering Perspective for Multiatlas Segmentation*

    Science.gov (United States)

    Gao, Yi; Zhu, Liangjia; Cates, Joshua; MacLeod, Rob S.; Bouix, Sylvain; Tannenbaum, Allen

    2016-01-01

    In multiatlas segmentation, one typically registers several atlases to the novel image, and their respective segmented label images are transformed and fused to form the final segmentation. In this work, we provide a new dynamical system perspective for multiatlas segmentation, inspired by the following fact: The transformation that aligns the current atlas to the novel image can be not only computed by direct registration but also inferred from the transformation that aligns the previous atlas to the image together with the transformation between the two atlases. This process is similar to the global positioning system on a vehicle, which gets position by inquiring from the satellite and by employing the previous location and velocity—neither answer in isolation being perfect. To solve this problem, a dynamical system scheme is crucial to combine the two pieces of information; for example, a Kalman filtering scheme is used. Accordingly, in this work, a Kalman multiatlas segmentation is proposed to stabilize the global/affine registration step. The contributions of this work are twofold. First, it provides a new dynamical systematic perspective for standard independent multiatlas registrations, and it is solved by Kalman filtering. Second, with very little extra computation, it can be combined with most existing multiatlas segmentation schemes for better registration/segmentation accuracy. PMID:26807162

  14. Unsupervised Myocardial Segmentation for Cardiac BOLD.

    Science.gov (United States)

    Oksuz, Ilkay; Mukhopadhyay, Anirban; Dharmakumar, Rohan; Tsaftaris, Sotirios A

    2017-11-01

    A fully automated 2-D+time myocardial segmentation framework is proposed for cardiac magnetic resonance (CMR) blood-oxygen-level-dependent (BOLD) data sets. Ischemia detection with CINE BOLD CMR relies on spatio-temporal patterns in myocardial intensity, but these patterns also trouble supervised segmentation methods, the de facto standard for myocardial segmentation in cine MRI. Segmentation errors severely undermine the accurate extraction of these patterns. In this paper, we build a joint motion and appearance method that relies on dictionary learning to find a suitable subspace. Our method is based on variational pre-processing and spatial regularization using Markov random fields, to further improve performance. The superiority of the proposed segmentation technique is demonstrated on a data set containing cardiac phase-resolved BOLD MR and standard CINE MR image sequences acquired in baseline and ischemic condition across ten canine subjects. Our unsupervised approach outperforms even supervised state-of-the-art segmentation techniques by at least 10% when using Dice to measure accuracy on BOLD data and performs at par for standard CINE MR. Furthermore, a novel segmental analysis method attuned for BOLD time series is utilized to demonstrate the effectiveness of the proposed method in preserving key BOLD patterns.

  15. On the evaluation of segmentation editing tools

    Science.gov (United States)

    Heckel, Frank; Moltz, Jan H.; Meine, Hans; Geisler, Benjamin; Kießling, Andreas; D’Anastasi, Melvin; dos Santos, Daniel Pinto; Theruvath, Ashok Joseph; Hahn, Horst K.

    2014-01-01

    Abstract. Efficient segmentation editing tools are important components in the segmentation process, as no automatic methods exist that always generate sufficient results. Evaluating segmentation editing algorithms is challenging, because their quality depends on the user’s subjective impression. So far, no established methods for an objective, comprehensive evaluation of such tools exist and, particularly, intermediate segmentation results are not taken into account. We discuss the evaluation of editing algorithms in the context of tumor segmentation in computed tomography. We propose a rating scheme to qualitatively measure the accuracy and efficiency of editing tools in user studies. In order to objectively summarize the overall quality, we propose two scores based on the subjective rating and the quantified segmentation quality over time. Finally, a simulation-based evaluation approach is discussed, which allows a more reproducible evaluation without the need for human input. This automated evaluation complements user studies, allowing a more convincing evaluation, particularly during development, where frequent user studies are not possible. The proposed methods have been used to evaluate two dedicated editing algorithms on 131 representative tumor segmentations. We show how the comparison of editing algorithms benefits from the proposed methods. Our results also show the correlation of the suggested quality score with the qualitative ratings. PMID:26158063

  16. Recent Advancements in Retinal Vessel Segmentation.

    Science.gov (United States)

    L Srinidhi, Chetan; Aparna, P; Rajan, Jeny

    2017-04-01

    Retinal vessel segmentation is a key step towards the accurate visualization, diagnosis, early treatment and surgery planning of ocular diseases. For the last two decades, a tremendous amount of research has been dedicated in developing automated methods for segmentation of blood vessels from retinal fundus images. Despite the fact, segmentation of retinal vessels still remains a challenging task due to the presence of abnormalities, varying size and shape of the vessels, non-uniform illumination and anatomical variability between subjects. In this paper, we carry out a systematic review of the most recent advancements in retinal vessel segmentation methods published in last five years. The objectives of this study are as follows: first, we discuss the most crucial preprocessing steps that are involved in accurate segmentation of vessels. Second, we review most recent state-of-the-art retinal vessel segmentation techniques which are classified into different categories based on their main principle. Third, we quantitatively analyse these methods in terms of its sensitivity, specificity, accuracy, area under the curve and discuss newly introduced performance metrics in current literature. Fourth, we discuss the advantages and limitations of the existing segmentation techniques. Finally, we provide an insight into active problems and possible future directions towards building successful computer-aided diagnostic system.

  17. 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.

  18. 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.

  19. Bayesian automated cortical segmentation for neonatal MRI

    Science.gov (United States)

    Chou, Zane; Paquette, Natacha; Ganesh, Bhavana; Wang, Yalin; Ceschin, Rafael; Nelson, Marvin D.; Macyszyn, Luke; Gaonkar, Bilwaj; Panigrahy, Ashok; Lepore, Natasha

    2017-11-01

    Several attempts have been made in the past few years to develop and implement an automated segmentation of neonatal brain structural MRI. However, accurate automated MRI segmentation remains challenging in this population because of the low signal-to-noise ratio, large partial volume effects and inter-individual anatomical variability of the neonatal brain. In this paper, we propose a learning method for segmenting the whole brain cortical grey matter on neonatal T2-weighted images. We trained our algorithm using a neonatal dataset composed of 3 fullterm and 4 preterm infants scanned at term equivalent age. Our segmentation pipeline combines the FAST algorithm from the FSL library software and a Bayesian segmentation approach to create a threshold matrix that minimizes the error of mislabeling brain tissue types. Our method shows promising results with our pilot training set. In both preterm and full-term neonates, automated Bayesian segmentation generates a smoother and more consistent parcellation compared to FAST, while successfully removing the subcortical structure and cleaning the edges of the cortical grey matter. This method show promising refinement of the FAST segmentation by considerably reducing manual input and editing required from the user, and further improving reliability and processing time of neonatal MR images. Further improvement will include a larger dataset of training images acquired from different manufacturers.

  20. Breast ultrasound image segmentation: a survey.

    Science.gov (United States)

    Huang, Qinghua; Luo, Yaozhong; Zhang, Qiangzhi

    2017-03-01

    Breast cancer is the most common form of cancer among women worldwide. Ultrasound imaging is one of the most frequently used diagnostic tools to detect and classify abnormalities of the breast. Recently, computer-aided diagnosis (CAD) systems using ultrasound images have been developed to help radiologists to increase diagnosis accuracy. However, accurate ultrasound image segmentation remains a challenging problem due to various ultrasound artifacts. In this paper, we investigate approaches developed for breast ultrasound (BUS) image segmentation. In this paper, we reviewed the literature on the segmentation of BUS images according to the techniques adopted, especially over the past 10 years. By dividing into seven classes (i.e., thresholding-based, clustering-based, watershed-based, graph-based, active contour model, Markov random field and neural network), we have introduced corresponding techniques and representative papers accordingly. We have summarized and compared many techniques on BUS image segmentation and found that all these techniques have their own pros and cons. However, BUS image segmentation is still an open and challenging problem due to various ultrasound artifacts introduced in the process of imaging, including high speckle noise, low contrast, blurry boundaries, low signal-to-noise ratio and intensity inhomogeneity CONCLUSIONS: To the best of our knowledge, this is the first comprehensive review of the approaches developed for segmentation of BUS images. With most techniques involved, this paper will be useful and helpful for researchers working on segmentation of ultrasound images, and for BUS CAD system developers.

  1. Semantic Image Segmentation with Contextual Hierarchical Models.

    Science.gov (United States)

    Seyedhosseini, Mojtaba; Tasdizen, Tolga

    2016-05-01

    Semantic segmentation is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. The importance of using contextual information in semantic segmentation frameworks has been widely realized in the field. We propose a contextual framework, called contextual hierarchical model (CHM), which learns contextual information in a hierarchical framework for semantic segmentation. At each level of the hierarchy, a classifier is trained based on downsampled input images and outputs of previous levels. Our model then incorporates the resulting multi-resolution contextual information into a classifier to segment the input image at original resolution. This training strategy allows for optimization of a joint posterior probability at multiple resolutions through the hierarchy. Contextual hierarchical model is purely based on the input image patches and does not make use of any fragments or shape examples. Hence, it is applicable to a variety of problems such as object segmentation and edge detection. We demonstrate that CHM performs at par with state-of-the-art on Stanford background and Weizmann horse datasets. It also outperforms state-of-the-art edge detection methods on NYU depth dataset and achieves state-of-the-art on Berkeley segmentation dataset (BSDS 500).

  2. Brain tissue segmentation using fuzzy clustering techniques.

    Science.gov (United States)

    Sucharitha, M; Geetha, K Parimala

    2015-01-01

    Medical image segmentation is an essential step for most consequent image analysis tasks. Medical images can be segmented manually, but the accuracy of image segmentation using the automated segmentation algorithms is more when compared with the manual calculations. In this paper, an automated segmentation and classification of tissues are proposed for MR brain images. To classify MR brain image into three segments such as Grey Matter (GM), White Matter (WM) and Cerebro-Spinal Fluid (CSF). Classification of brain into tissues helps to diagnose several diseases such as tumors, Alzheimer's disease, stroke, multiple sclerosis. An unsupervised clustering technique such as Fuzzy C-Means (FCM) algorithm has been widely used in segmenting the images. The spatial information is not fully utilized by the conventional clustering algorithm and hence it is not applicable for clustering a noisy image. We incorporate a method for image clustering called out as Reformulated Fuzzy Local information C-Means Clustering algorithm [RFLICM] which is a variant of traditional Clustering algorithm by considering both spatial and gray level information. In RFLICM, spatial distance is replaced by local coefficient of variation in a fuzzy manner. Experiments are conducted on brain images to validate the performance of the proposed technique in segmenting the medical images and the efficiency achieved in the presence of salt and pepper noise is 99.86%. Standard FCM, Fuzzy Local information C-means clustering algorithm [FLICM], Reformulated Fuzzy Local information C-means clustering algorithm [RFLICM] are compared to explore the accuracy of our proposed approach. Clustering results show that RFLICM segmentation method is appropriate for classifying tissues in brain MR image.

  3. Unsupervised Segmentation Methods of TV Contents

    Directory of Open Access Journals (Sweden)

    Elie El-Khoury

    2010-01-01

    Full Text Available We present a generic algorithm to address various temporal segmentation topics of audiovisual contents such as speaker diarization, shot, or program segmentation. Based on a GLR approach, involving the ΔBIC criterion, this algorithm requires the value of only a few parameters to produce segmentation results at a desired scale and on most typical low-level features used in the field of content-based indexing. Results obtained on various corpora are of the same quality level than the ones obtained by other dedicated and state-of-the-art methods.

  4. Contractual Incompleteness, Unemployment, and Labour Market Segmentation

    DEFF Research Database (Denmark)

    Altmann, Steffen; Falk, Armin; Grunewald, Andreas

    2014-01-01

    This article provides evidence that involuntary unemployment, and the segmentation of labour markets into firms offering "good" and "bad" jobs, may both arise as a consequence of contractual incompleteness.We provide a simple model that illustrates how unemployment and market segmentation may...... jointly emerge as part of a market equilibrium in environments where work effort is not third-party verifiable. Using experimental labour markets that differ only in the verifiability of effort, we demonstrate empirically that contractual incompleteness can cause unemployment and segmentation. Our data...

  5. Nonsynchronized segmented heterochromia in black scalp hair.

    Science.gov (United States)

    Faulkner, C; Godbolt, A M; Messenger, A G; Jones, S K

    2003-05-01

    Nonsynchronized segmented heterochromia in black scalp hair is a rarely reported entity, the only previous report being described in association with iron deficiency anaemia. A 14-year-old girl presented with a 2-year history of nonsynchronized segmented heterochromia. She was otherwise well and her serum iron, copper, zinc and protein levels were all within the normal range. She had no clinical evidence of vitiligo or alopecia areata. This patient is believed to represent the first reported case of nonsynchronized segmented heterochromia in black scalp hair as a presentation of premature greying of the hair.

  6. Russian space

    Science.gov (United States)

    As well as authorizing NASA's funding for FY 1998 and 1999, the Civilian Space Authorization Act (H.R. 1275) would affect U.S.-Russia interactions in space. Regarding the International Space Station, the bill: prohibits transferring funds to Russia to pay for work on elements that are Russia's responsibility;

  7. Space administration

    OpenAIRE

    Worthington, Scott; Worthington, Scott

    2015-01-01

    My dissertation consists of two parts. The larger portion is an hour-long piece for double bass, electronics, and projected text called Space Administration. The second portion, this essay, discusses my musical background leading up to Space Administration, details of the composition itself, and what new directions I see in my work that in part stem from creating the piece Space Administration

  8. Evaluation of segmentation methods on head and neck CT: Auto-segmentation challenge 2015.

    Science.gov (United States)

    Raudaschl, Patrik F; Zaffino, Paolo; Sharp, Gregory C; Spadea, Maria Francesca; Chen, Antong; Dawant, Benoit M; Albrecht, Thomas; Gass, Tobias; Langguth, Christoph; Lüthi, Marcel; Jung, Florian; Knapp, Oliver; Wesarg, Stefan; Mannion-Haworth, Richard; Bowes, Mike; Ashman, Annaliese; Guillard, Gwenael; Brett, Alan; Vincent, Graham; Orbes-Arteaga, Mauricio; Cárdenas-Peña, David; Castellanos-Dominguez, German; Aghdasi, Nava; Li, Yangming; Berens, Angelique; Moe, Kris; Hannaford, Blake; Schubert, Rainer; Fritscher, Karl D

    2017-05-01

    Automated delineation of structures and organs is a key step in medical imaging. However, due to the large number and diversity of structures and the large variety of segmentation algorithms, a consensus is lacking as to which automated segmentation method works best for certain applications. Segmentation challenges are a good approach for unbiased evaluation and comparison of segmentation algorithms. In this work, we describe and present the results of the Head and Neck Auto-Segmentation Challenge 2015, a satellite event at the Medical Image Computing and Computer Assisted Interventions (MICCAI) 2015 conference. Six teams participated in a challenge to segment nine structures in the head and neck region of CT images: brainstem, mandible, chiasm, bilateral optic nerves, bilateral parotid glands, and bilateral submandibular glands. This paper presents the quantitative results of this challenge using multiple established error metrics and a well-defined ranking system. The strengths and weaknesses of the different auto-segmentation approaches are analyzed and discussed. The Head and Neck Auto-Segmentation Challenge 2015 was a good opportunity to assess the current state-of-the-art in segmentation of organs at risk for radiotherapy treatment. Participating teams had the possibility to compare their approaches to other methods under unbiased and standardized circumstances. The results demonstrate a clear tendency toward more general purpose and fewer structure-specific segmentation algorithms. © 2017 American Association of Physicists in Medicine.

  9. Building Roof Segmentation from Aerial Images Using a Lineand Region-Based Watershed Segmentation Technique

    Directory of Open Access Journals (Sweden)

    Youssef El Merabet

    2015-02-01

    Full Text Available In this paper, we present a novel strategy for roof segmentation from aerial images (orthophotoplans based on the cooperation of edge- and region-based segmentation methods. The proposed strategy is composed of three major steps. The first one, called the pre-processing step, consists of simplifying the acquired image with an appropriate couple of invariant and gradient, optimized for the application, in order to limit illumination changes (shadows, brightness, etc. affecting the images. The second step is composed of two main parallel treatments: on the one hand, the simplified image is segmented by watershed regions. Even if the first segmentation of this step provides good results in general, the image is often over-segmented. To alleviate this problem, an efficient region merging strategy adapted to the orthophotoplan particularities, with a 2D modeling of roof ridges technique, is applied. On the other hand, the simplified image is segmented by watershed lines. The third step consists of integrating both watershed segmentation strategies into a single cooperative segmentation scheme in order to achieve satisfactory segmentation results. Tests have been performed on orthophotoplans containing 100 roofs with varying complexity, and the results are evaluated with the VINETcriterion using ground-truth image segmentation. A comparison with five popular segmentation techniques of the literature demonstrates the effectiveness and the reliability of the proposed approach. Indeed, we obtain a good segmentation rate of 96% with the proposed method compared to 87.5% with statistical region merging (SRM, 84% with mean shift, 82% with color structure code (CSC, 80% with efficient graph-based segmentation algorithm (EGBIS and 71% with JSEG.

  10. Building roof segmentation from aerial images using a lineand region-based watershed segmentation technique.

    Science.gov (United States)

    El Merabet, Youssef; Meurie, Cyril; Ruichek, Yassine; Sbihi, Abderrahmane; Touahni, Raja

    2015-02-02

    In this paper, we present a novel strategy for roof segmentation from aerial images (orthophotoplans) based on the cooperation of edge- and region-based segmentation methods. The proposed strategy is composed of three major steps. The first one, called the pre-processing step, consists of simplifying the acquired image with an appropriate couple of invariant and gradient, optimized for the application, in order to limit illumination changes (shadows, brightness, etc.) affecting the images. The second step is composed of two main parallel treatments: on the one hand, the simplified image is segmented by watershed regions. Even if the first segmentation of this step provides good results in general, the image is often over-segmented. To alleviate this problem, an efficient region merging strategy adapted to the orthophotoplan particularities, with a 2D modeling of roof ridges technique, is applied. On the other hand, the simplified image is segmented by watershed lines. The third step consists of integrating both watershed segmentation strategies into a single cooperative segmentation scheme in order to achieve satisfactory segmentation results. Tests have been performed on orthophotoplans containing 100 roofs with varying complexity, and the results are evaluated with the VINETcriterion using ground-truth image segmentation. A comparison with five popular segmentation techniques of the literature demonstrates the effectiveness and the reliability of the proposed approach. Indeed, we obtain a good segmentation rate of 96% with the proposed method compared to 87.5% with statistical region merging (SRM), 84% with mean shift, 82% with color structure code (CSC), 80% with efficient graph-based segmentation algorithm (EGBIS) and 71% with JSEG.

  11. Value of a probabilistic atlas in medical image segmentation regarding non-rigid registration of abdominal CT scans

    Science.gov (United States)

    Park, Hyunjin; Meyer, Charles R.

    2012-10-01

    A probabilistic atlas provides important information to help segmentation and registration applications in medical image analysis. We construct a probabilistic atlas by picking a target geometry and mapping other training scans onto that target and then summing the results into one probabilistic atlas. By choosing an atlas space close to the desired target, we construct an atlas that represents the population well. Image registration used to map one image geometry onto another is a primary task in atlas building. One of the main parameters of registration is the choice of degrees of freedom (DOFs) of the geometric transform. Herein, we measure the effect of the registration's DOFs on the segmentation performance of the resulting probabilistic atlas. Twenty-three normal abdominal CT scans were used, and four organs (liver, spinal cord, left and right kidneys) were segmented for each scan. A well-known manifold learning method, ISOMAP, was used to find the best target space to build an atlas. In summary, segmentation performance was high for high DOF registrations regardless of the chosen target space, while segmentation performance was lowered for low DOF registrations if a target space was far from the best target space. At the 0.05 level of statistical significance, there were no significant differences at high DOF registrations while there were significant differences at low DOF registrations when choosing different targets.

  12. Segmental mode of neural patterning in sipuncula

    DEFF Research Database (Denmark)

    Kristof, Alen; Wollesen, Tim; Wanninger, Andreas

    2008-01-01

    sipunculan, Phascolosoma agassizii, we found that neurogenesis initially follows a segmental pattern similar to that of annelids. Starting out with paired FMRFamidergic and serotonergic axons, four pairs of associated serotonergic perikarya and interconnecting commissures form one after another...

  13. An efficient algorithm for color image segmentation

    Directory of Open Access Journals (Sweden)

    Shikha Yadav

    2016-09-01

    Full Text Available In field of image processing, image segmentation plays an important role that focus on splitting the whole image into segments. Representation of an image so that it can be more easily analysed and involves more information is an important segmentation goal. The process of partitioning an image can be usually realized by Region based, Boundary based or edge based method. In this work a hybrid approach is followed that combines improved bee colony optimization and Tabu search for color image segmentation. The results produced from this hybrid approach are compared with non-sorted particle swarm optimization, non-sorted genetic algorithm and improved bee colony optimization. Results show that the Hybrid algorithm has better or somewhat similar performance as compared to other algorithms that are based on population. The algorithm is successfully implemented on MATLAB.

  14. Studies in Prestressed and Segmented Brittle Structures

    National Research Council Canada - National Science Library

    Barnett, Ralph L; Hermann, Paul C

    1966-01-01

    .... The applicability of the theory is extended to beam-columns and to I-beams with multiple tendons. The methods of limit analysis are used to predict the ultimate load carrying capacity of prestressed and segmented beams and plates...

  15. Retina image–based optic disc segmentation

    Directory of Open Access Journals (Sweden)

    Ching-Lin Wang

    2016-05-01

    Full Text Available The change of optic disc can be used to diagnose many eye diseases, such as glaucoma, diabetic retinopathy and macular degeneration. Moreover, retinal blood vessel pattern is unique for human beings even for identical twins. It is a highly stable pattern in biometric identification. Since optic disc is the beginning of the optic nerve and main blood vessels in retina, it can be used as a reference point of identification. Therefore, optic disc segmentation is an important technique for developing a human identity recognition system and eye disease diagnostic system. This article hence presents an optic disc segmentation method to extract the optic disc from a retina image. The experimental results show that the optic disc segmentation method can give impressive results in segmenting the optic disc from a retina image.

  16. Probabilistic segmentation of remotely sensed images

    NARCIS (Netherlands)

    Gorte, B.

    1998-01-01

    For information extraction from image data to create or update geographic information systems, objects are identified and labeled using an integration of segmentation and classification. This yields geometric and thematic information, respectively.

    Bayesian image

  17. Measurements on a prototype segmented Clover detector

    CERN Document Server

    Shepherd, S L; Cullen, D M; Appelbe, D E; Simpson, J; Gerl, J; Kaspar, M; Kleinböhl, A; Peter, I; Rejmund, M; Schaffner, H; Schlegel, C; France, G D

    1999-01-01

    The performance of a segmented Clover germanium detector has been measured. The segmented Clover detector is a composite germanium detector, consisting of four individual germanium crystals in the configuration of a four-leaf Clover, housed in a single cryostat. Each crystal is electrically segmented on its outer surface into four quadrants, with separate energy read-outs from nine crystal zones. Signals are also taken from the inner contact of each crystal. This effectively produces a detector with 16 active elements. One of the purposes of this segmentation is to improve the overall spectral resolution when detecting gamma radiation emitted following a nuclear reaction, by minimising Doppler broadening caused by the opening angle subtended by each detector element. Results of the tests with sources and in beam will be presented. The improved granularity of the detector also leads to an improved isolated hit probability compared with an unsegmented Clover detector. (author)

  18. Multi-scale Modelling of Segmentation

    DEFF Research Database (Denmark)

    Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri

    2016-01-01

    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...... of experimental task (i.e., real-time vs. annotated segmentation), nor of musicianship on boundary perception are clear. Our study assesses musicianship effects and differences between segmentation tasks. We conducted a real-time experiment to collect segmentations by musicians and nonmusicians from nine musical...... indication density, although this might be contingent on stimuli and other factors. In line with other studies, no musicianship effects were found: our results showed high agreement between groups and similar inter-subject correlations. Also consistent with previous work, time scales between one and two...

  19. Mixed raster content segmentation, compression, transmission

    CERN Document Server

    Pavlidis, George

    2017-01-01

    This book presents the main concepts in handling digital images of mixed content, traditionally referenced as mixed raster content (MRC), in two main parts. The first includes introductory chapters covering the scientific and technical background aspects, whereas the second presents a set of research and development approaches to tackle key issues in MRC segmentation, compression and transmission. The book starts with a review of color theory and the mechanism of color vision in humans. In turn, the second chapter reviews data coding and compression methods so as to set the background and demonstrate the complexity involved in dealing with MRC. Chapter three addresses the segmentation of images through an extensive literature review, which highlights the various approaches used to tackle MRC segmentation. The second part of the book focuses on the segmentation of color images for optimized compression, including multi-layered decomposition and representation of MRC and the processes that can be employed to op...

  20. Field Sampling from a Segmented Image

    CSIR Research Space (South Africa)

    Debba, Pravesh

    2008-06-01

    Full Text Available This paper presents a statistical method for deriving the optimal prospective field sampling scheme on a remote sensing image to represent different categories in the field. The iterated conditional modes algorithm (ICM) is used for segmentation...

  1. Variational mesh segmentation via quadric surface fitting

    KAUST Repository

    Yan, Dongming

    2012-11-01

    We present a new variational method for mesh segmentation by fitting quadric surfaces. Each component of the resulting segmentation is represented by a general quadric surface (including plane as a special case). A novel energy function is defined to evaluate the quality of the segmentation, which combines both L2 and L2 ,1 metrics from a triangle to a quadric surface. The Lloyd iteration is used to minimize the energy function, which repeatedly interleaves between mesh partition and quadric surface fitting. We also integrate feature-based and simplification-based techniques in the segmentation framework, which greatly improve the performance. The advantages of our algorithm are demonstrated by comparing with the state-of-the-art methods. © 2012 Elsevier Ltd. All rights reserved.

  2. Adjacent segment disease following cervical spine surgery.

    Science.gov (United States)

    Cho, Samuel K; Riew, K Daniel

    2013-01-01

    Cervical spine surgery is broadly divided into fusion and nonfusion procedures. Anterior cervical diskectomy and fusion (ACDF) is a common procedure, although adjacent segment disease following the surgery is an ongoing clinical concern. Adjacent segment cervical disease occurs in approximately 3% of patients per year, with an expected incidence of 25% within the first 10 years following fusion. Nonfusion procedures such as anterior diskectomy and posterior foraminotomy do not decrease the rate of adjacent segment disease compared with ACDF. Recently, enthusiasm has developed for artificial disk replacement as a motion-sparing alternative to fusion. To date, however, multiple clinical trials and subsequent follow-up studies have failed to demonstrate significant reduction of adjacent segment disease when artificial disk replacement is performed instead of fusion.

  3. A segmentation algorithm for noisy images

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Y.; Olman, V.; Uberbacher, E.C.

    1996-12-31

    This paper presents a 2-D image segmentation algorithm and addresses issues related to its performance on noisy images. The algorithm segments an image by first constructing a minimum spanning tree representation of the image and then partitioning the spanning tree into sub-trees representing different homogeneous regions. The spanning tree is partitioned in such a way that the sum of gray-level variations over all partitioned subtrees is minimized under the constraints that each subtree has at least a specified number of pixels and two adjacent subtrees have significantly different ``average`` gray-levels. Two types of noise, transmission errors and Gaussian additive noise. are considered and their effects on the segmentation algorithm are studied. Evaluation results have shown that the segmentation algorithm is robust in the presence of these two types of noise.

  4. Design spaces

    DEFF Research Database (Denmark)

    2005-01-01

    of digital technology with space poses new challenges that call for new approaches. Creative alternatives to traditional systems methodologies are called for when designers use digital media to create new possibilities for action in space. Design Spaces explores how design and media art can provide creative......Digital technologies and media are becoming increasingly embodied and entangled in the spaces and places at work and at home. However, our material environment is more than a geometric abstractions of space: it contains familiar places, social arenas for human action. For designers, the integration...... alternatives for integrating digital technology with space. Connecting practical design work with conceptual development and theorizing, art with technology, and usesr-centered methods with social sciences, Design Spaces provides a useful research paradigm for designing ubiquitous computing. This book...

  5. Design spaces

    DEFF Research Database (Denmark)

    2005-01-01

    Digital technologies and media are becoming increasingly embodied and entangled in the spaces and places at work and at home. However, our material environment is more than a geometric abstractions of space: it contains familiar places, social arenas for human action. For designers, the integration...... of digital technology with space poses new challenges that call for new approaches. Creative alternatives to traditional systems methodologies are called for when designers use digital media to create new possibilities for action in space. Design Spaces explores how design and media art can provide creative...... alternatives for integrating digital technology with space. Connecting practical design work with conceptual development and theorizing, art with technology, and usesr-centered methods with social sciences, Design Spaces provides a useful research paradigm for designing ubiquitous computing. This book...

  6. Accurate and robust line segment extraction using minimum entropy with Hough transform.

    Science.gov (United States)

    Xu, Zezhong; Shin, Bok-Suk; Klette, Reinhard

    2015-03-01

    The Hough transform is a popular technique used in the field of image processing and computer vision. With a Hough transform technique, not only the normal angle and distance of a line but also the line-segment's length and midpoint (centroid) can be extracted by analysing the voting distribution around a peak in the Hough space. In this paper, a method based on minimum-entropy analysis is proposed to extract the set of parameters of a line segment. In each column around a peak in Hough space, the voting values specify probabilistic distributions. The corresponding entropies and statistical means are computed. The line-segment's normal angle and length are simultaneously computed by fitting a quadratic polynomial curve to the voting entropies. The line-segment's midpoint and normal distance are computed by fitting and interpolating a linear curve to the voting means. The proposed method is tested on simulated images for detection accuracy by providing comparative results. Experimental results on real-world images verify the method as well. The proposed method for line-segment detection is both accurate and robust in the presence of quantization error, background noise, or pixel disturbances.

  7. Candidate Smoke Region Segmentation of Fire Video Based on Rough Set Theory

    Directory of Open Access Journals (Sweden)

    Yaqin Zhao

    2015-01-01

    Full Text Available Candidate smoke region segmentation is the key link of smoke video detection; an effective and prompt method of candidate smoke region segmentation plays a significant role in a smoke recognition system. However, the interference of heavy fog and smoke-color moving objects greatly degrades the recognition accuracy. In this paper, a novel method of candidate smoke region segmentation based on rough set theory is presented. First, Kalman filtering is used to update video background in order to exclude the interference of static smoke-color objects, such as blue sky. Second, in RGB color space smoke regions are segmented by defining the upper approximation, lower approximation, and roughness of smoke-color distribution. Finally, in HSV color space small smoke regions are merged by the definition of equivalence relation so as to distinguish smoke images from heavy fog images in terms of V component value variety from center to edge of smoke region. The experimental results on smoke region segmentation demonstrated the effectiveness and usefulness of the proposed scheme.

  8. Older People's Mobility: Segments, Factors, Trends

    DEFF Research Database (Denmark)

    Haustein, Sonja; Siren, Anu

    2015-01-01

    people’s travel behaviour. Based on this, we proposed a theoretical model on how the different determinants work together to form the four mobility patterns related to the identified segments. Finally, based on current trends and expectations, we assessed which segments are likely to increase or decrease...... in future generations of older people and what should be done to support the multi-optional and independent mobility of older people....

  9. Segmental arterial mediolysis with mesangial cell hyperplasia

    DEFF Research Database (Denmark)

    Slavin, Richard E.; Leifsson, Páll Skúli

    2017-01-01

    Background: Segmental arterial mediolysis (SAM) a rare arteriopathy causing massive bleeding or ischemic symptoms, is suspected of representing a vascular disease of the peripheral sympathetic nervous system. It is initiated by the supra physiological release of norepinephrine from the efferent...... by conditions causing the adrenal medulla to release supra physiologic levels of circulating norepinephrine. Supra physiologic release of norepinephrine from the peripheral sympathetic nerves also can cause mesangial hyperplasia that can be accompanied with segmental glomerular loop sclerosis-making it another...

  10. A competition in unsupervised color image segmentation

    Czech Academy of Sciences Publication Activity Database

    Haindl, Michal; Mikeš, Stanislav

    2016-01-01

    Roč. 57, č. 9 (2016), s. 136-151 ISSN 0031-3203 R&D Projects: GA ČR(CZ) GA14-10911S Institutional support: RVO:67985556 Keywords : Unsupervised image segmentation * Segmentation contest * Texture analysis Subject RIV: BD - Theory of Information Impact factor: 4.582, year: 2016 http:// library .utia.cas.cz/separaty/2016/RO/haindl-0459179.pdf

  11. Colour texture segmentation using modelling approach

    Czech Academy of Sciences Publication Activity Database

    Haindl, Michal; Mikeš, Stanislav

    2005-01-01

    Roč. 3687, č. - (2005), s. 484-491 ISSN 0302-9743. [International Conference on Advances in Pattern Recognition /3./. Bath, 22.08.2005-25.08.2005] R&D Projects: GA MŠk 1M0572; GA AV ČR 1ET400750407; GA AV ČR IAA2075302 Institutional research plan: CEZ:AV0Z10750506 Keywords : colour texture segmentation * image models * segmentation benchmark Subject RIV: BD - Theory of Information

  12. Deeply-Supervised CNN for Prostate Segmentation

    OpenAIRE

    Zhu, Qikui; Du, Bo; Turkbey, Baris; Choyke, Peter L .; Yan, Pingkun

    2017-01-01

    Prostate segmentation from Magnetic Resonance (MR) images plays an important role in image guided interven- tion. However, the lack of clear boundary specifically at the apex and base, and huge variation of shape and texture between the images from different patients make the task very challenging. To overcome these problems, in this paper, we propose a deeply supervised convolutional neural network (CNN) utilizing the convolutional information to accurately segment the prostate from MR image...

  13. Adjacent Segment Pathology after Lumbar Spinal Fusion

    OpenAIRE

    Lee, Jae Chul; Choi, Sung-Woo

    2015-01-01

    One of the major clinical issues encountered after lumbar spinal fusion is the development of adjacent segment pathology (ASP) caused by increased mechanical stress at adjacent segments, and resulting in various radiographic changes and clinical symptoms. This condition may require surgical intervention. The incidence of ASP varies with both the definition and methodology adopted in individual studies; various risk factors for this condition have been identified, although a significant contro...

  14. Segmental lichen planus pigmentosus: An unusual presentation

    Directory of Open Access Journals (Sweden)

    Y Hari Kishan Kumar

    2014-01-01

    Full Text Available Lichen planus pigmentosus (LPP is a distinct clinical entity commonly encountered in the Indian population. It is considered a variant of lichen planus (LP. A 40-year-old male presented with asymptomatic hyperpigmented macules in a segmental distribution since 10 years that were clinically and histopathologically suggestive of LPP. We propose the terminology "segmental lichen planus pigmentosus" and report this unusual presentation.

  15. Regulation distance, labour segmentation and gender gaps

    OpenAIRE

    David Peetz

    2015-01-01

    Existing theories on human capital, labour market segmentation and discrimination fail to fully explain gender gaps—for example, the large gender gap in elite occupations where women apparently possess high labour market power. This article seeks to extend our understanding, through the interaction between labour segmentation, regulation content and regulation distance, the last referring to the extent to which employment of particular workers is (un)regulated, including by collective agreeme...

  16. Automated Urban Travel Interpretation: A Bottom-up Approach for Trajectory Segmentation

    Directory of Open Access Journals (Sweden)

    Rahul Deb Das

    2016-11-01

    Full Text Available Understanding travel behavior is critical for an effective urban planning as well as for enabling various context-aware service provisions to support mobility as a service (MaaS. Both applications rely on the sensor traces generated by travellers’ smartphones. These traces can be used to interpret travel modes, both for generating automated travel diaries as well as for real-time travel mode detection. Current approaches segment a trajectory by certain criteria, e.g., drop in speed. However, these criteria are heuristic, and, thus, existing approaches are subjective and involve significant vagueness and uncertainty in activity transitions in space and time. Also, segmentation approaches are not suited for real time interpretation of open-ended segments, and cannot cope with the frequent gaps in the location traces. In order to address all these challenges a novel, state based bottom-up approach is proposed. This approach assumes a fixed atomic segment of a homogeneous state, instead of an event-based segment, and a progressive iteration until a new state is found. The research investigates how an atomic state-based approach can be developed in such a way that can work in real time, near-real time and offline mode and in different environmental conditions with their varying quality of sensor traces. The results show the proposed bottom-up model outperforms the existing event-based segmentation models in terms of adaptivity, flexibility, accuracy and richness in information delivery pertinent to automated travel behavior interpretation.

  17. Automated Urban Travel Interpretation: A Bottom-up Approach for Trajectory Segmentation.

    Science.gov (United States)

    Das, Rahul Deb; Winter, Stephan

    2016-11-23

    Understanding travel behavior is critical for an effective urban planning as well as for enabling various context-aware service provisions to support mobility as a service (MaaS). Both applications rely on the sensor traces generated by travellers' smartphones. These traces can be used to interpret travel modes, both for generating automated travel diaries as well as for real-time travel mode detection. Current approaches segment a trajectory by certain criteria, e.g., drop in speed. However, these criteria are heuristic, and, thus, existing approaches are subjective and involve significant vagueness and uncertainty in activity transitions in space and time. Also, segmentation approaches are not suited for real time interpretation of open-ended segments, and cannot cope with the frequent gaps in the location traces. In order to address all these challenges a novel, state based bottom-up approach is proposed. This approach assumes a fixed atomic segment of a homogeneous state, instead of an event-based segment, and a progressive iteration until a new state is found. The research investigates how an atomic state-based approach can be developed in such a way that can work in real time, near-real time and offline mode and in different environmental conditions with their varying quality of sensor traces. The results show the proposed bottom-up model outperforms the existing event-based segmentation models in terms of adaptivity, flexibility, accuracy and richness in information delivery pertinent to automated travel behavior interpretation.

  18. Automated Bayesian Segmentation of Microvascular White-Matter Lesions in the ACCORD-MIND Study

    International Nuclear Information System (INIS)

    Herskovits, E. H.; Bryan, R. N.; Yang, F.

    2008-01-01

    Purpose: Automatic brain-lesion segmentation has the potential to greatly expand the analysis of the relationships between brain function and lesion locations in large-scale epidemiologic studies, such as the ACCORD-MIND study. In this manuscript we describe the design and evaluation of a Bayesian lesion-segmentation method, with the expectation that our approach would segment white-matter brain lesions in MR images without user intervention. Materials and Methods: Each ACCORD-MIND subject has T1-weighted, T2-weighted, spin-density-weighted, and FLAIR sequences. The training portion of our algorithm first registers training images to a standard coordinate space; then, it collects statistics that capture signal-intensity information, and residual spatial variability of normal structures and lesions. The classification portion of our algorithm then uses these statistics to segment lesions in images from new subjects, without the need for user intervention. We evaluated this algorithm using 42 subjects with primarily white-matter lesions from the ACCORD-MIND project. Results: Our experiments demonstrated high classification accuracy, using an expert neuro radiologist as a standard. Conclusions: A Bayesian lesion-segmentation algorithm that collects multi-channel signal-intensity and spatial information from MR images of the brain shows potential for accurately segmenting brain lesions in images obtained from subjects not used in training. (authors)

  19. Acquisition of earthworm-like movement patterns of many-segmented peristaltic crawling robots

    Directory of Open Access Journals (Sweden)

    Norihiko Saga

    2016-09-01

    Full Text Available In recent years, attention has been increasingly devoted to the development of rescue robots that can protect humans from the inherent risks of rescue work. Particularly, anticipated is the development of a robot that can move deeply through small spaces. We have devoted our attention to peristalsis, the movement mechanism used by earthworms. A reinforcement learning technique used for the derivation of the robot movement pattern, Q-learning, was used to develop a three-segmented peristaltic crawling robot with a motor drive. Characteristically, peristalsis can provide movement capability if at least three segments work, even if a segmented part does not function. Therefore, we had intended to derive the movement pattern of many-segmented peristaltic crawling robots using Q-learning. However, because of the necessary increase in calculations, in the case of many segments, Q-learning cannot be used because of insufficient memory. Therefore, we devoted our attention to a learning method called Actor–Critic, which can be implemented with low memory. Because Actor-Critic methods are TD methods that have a separate memory structure to explicitly represent the policy independent of the value function. Using it, we examined the movement patterns of six-segmented peristaltic crawling robots.

  20. Active contour segmentation in dynamic medical imaging: application to nuclear cardiology

    International Nuclear Information System (INIS)

    Debreuve, Eric

    2000-01-01

    In emission imaging, nuclear medicine provides functional information about the organ of interest. In transmission imaging, it provides anatomical information whose goal may be the correction of physical phenomena that corrupt emission images. With both emission and transmission images, it is useful to know how to extract, either automatically or semi-automatically, the organs of interest and the body outline in the case of a large field of view. This is the aim of segmentation. We developed two active contour segmentation methods. They were implemented using level sets. The key point is the evolution velocity definition. First, we were interested in static transmission imaging of the thorax. The evolution velocity was heuristically defined and depended only on the acquired projections. The segmented transmission map was computed w/o reconstruction and could be advantageously used for attenuation correction. Then, we studied the segmentation of cardiac gated sequences. The developed space-time segmentation method results from the minimization of a variational criterion which takes into account the whole sequence. The computed segmentation could be used for calculating physiological parameters. As an illustration, we computed the ejection fraction. Finally, we exploited some level set properties to develop a non-rigid, non-parametric, and geometric registration method. We applied it for kinetic compensation of cardiac gated sequences. The registered images were then added together providing an image with noise characteristics similar to a cardiac static image but w/o motion-induced blurring. (author)

  1. Rough-Fuzzy Clustering and Unsupervised Feature Selection for Wavelet Based MR Image Segmentation

    Science.gov (United States)

    Maji, Pradipta; Roy, Shaswati

    2015-01-01

    Image segmentation is an indispensable process in the visualization of human tissues, particularly during clinical analysis of brain magnetic resonance (MR) images. For many human experts, manual segmentation is a difficult and time consuming task, which makes an automated brain MR image segmentation method desirable. In this regard, this paper presents a new segmentation method for brain MR images, integrating judiciously the merits of rough-fuzzy computing and multiresolution image analysis technique. The proposed method assumes that the major brain tissues, namely, gray matter, white matter, and cerebrospinal fluid from the MR images are considered to have different textural properties. The dyadic wavelet analysis is used to extract the scale-space feature vector for each pixel, while the rough-fuzzy clustering is used to address the uncertainty problem of brain MR image segmentation. An unsupervised feature selection method is introduced, based on maximum relevance-maximum significance criterion, to select relevant and significant textural features for segmentation problem, while the mathematical morphology based skull stripping preprocessing step is proposed to remove the non-cerebral tissues like skull. The performance of the proposed method, along with a comparison with related approaches, is demonstrated on a set of synthetic and real brain MR images using standard validity indices. PMID:25848961

  2. Rough-fuzzy clustering and unsupervised feature selection for wavelet based MR image segmentation.

    Science.gov (United States)

    Maji, Pradipta; Roy, Shaswati

    2015-01-01

    Image segmentation is an indispensable process in the visualization of human tissues, particularly during clinical analysis of brain magnetic resonance (MR) images. For many human experts, manual segmentation is a difficult and time consuming task, which makes an automated brain MR image segmentation method desirable. In this regard, this paper presents a new segmentation method for brain MR images, integrating judiciously the merits of rough-fuzzy computing and multiresolution image analysis technique. The proposed method assumes that the major brain tissues, namely, gray matter, white matter, and cerebrospinal fluid from the MR images are considered to have different textural properties. The dyadic wavelet analysis is used to extract the scale-space feature vector for each pixel, while the rough-fuzzy clustering is used to address the uncertainty problem of brain MR image segmentation. An unsupervised feature selection method is introduced, based on maximum relevance-maximum significance criterion, to select relevant and significant textural features for segmentation problem, while the mathematical morphology based skull stripping preprocessing step is proposed to remove the non-cerebral tissues like skull. The performance of the proposed method, along with a comparison with related approaches, is demonstrated on a set of synthetic and real brain MR images using standard validity indices.

  3. Multi-atlas segmentation with particle-based group-wise image registration.

    Science.gov (United States)

    Lee, Joohwi; Lyu, Ilwoo; Styner, Martin

    2014-03-21

    We propose a novel multi-atlas segmentation method that employs a group-wise image registration method for the brain segmentation on rodent magnetic resonance (MR) images. The core element of the proposed segmentation is the use of a particle-guided image registration method that extends the concept of particle correspondence into the volumetric image domain. The registration method performs a group-wise image registration that simultaneously registers a set of images toward the space defined by the average of particles. The particle-guided image registration method is robust with low signal-to-noise ratio images as well as differing sizes and shapes observed in the developing rodent brain. Also, the use of an implicit common reference frame can prevent potential bias induced by the use of a single template in the segmentation process. We show that the use of a particle guided-image registration method can be naturally extended to a novel multi-atlas segmentation method and improves the registration method to explicitly use the provided template labels as an additional constraint. In the experiment, we show that our segmentation algorithm provides more accuracy with multi-atlas label fusion and stability against pair-wise image registration. The comparison with previous group-wise registration method is provided as well.

  4. Automatic multi-organ segmentation using learning-based segmentation and level set optimization.

    Science.gov (United States)

    Kohlberger, Timo; Sofka, Michal; Zhang, Jingdan; Birkbeck, Neil; Wetzl, Jens; Kaftan, Jens; Declerck, Jérôme; Zhou, S Kevin

    2011-01-01

    We present a novel generic segmentation system for the fully automatic multi-organ segmentation from CT medical images. Thereby we combine the advantages of learning-based approaches on point cloud-based shape representation, such a speed, robustness, point correspondences, with those of PDE-optimization-based level set approaches, such as high accuracy and the straightforward prevention of segment overlaps. In a benchmark on 10-100 annotated datasets for the liver, the lungs, and the kidneys we show that the proposed system yields segmentation accuracies of 1.17-2.89 mm average surface errors. Thereby the level set segmentation (which is initialized by the learning-based segmentations) contributes with an 20%-40% increase in accuracy.

  5. Segmental bioelectrical impedance analysis: an update.

    Science.gov (United States)

    Ward, Leigh C

    2012-09-01

    Bioelectrical impedance analysis is a popular, noninvasive and practical method for assessment of body composition. The last decade has seen the development of impedance analyzers designed to assess the composition of body segments as well as the whole body. This review outlines the theoretical basis for segmental impedance analysis, validity and use in practice. Segmental impedance analysis tends to underestimate fat-free mass and overestimate fat mass when compared to reference techniques, although the magnitude of these differences can be small. Performance is improved with population-specific prediction equations; algorithms in-built into instrument firmware should not be relied upon. Prediction of whole-body composition from the sum of the individual segments, although theoretically preferable, shows little advantage over whole body wrist to ankle impedance approaches. Prediction of appendicular skeletal muscle mass, although promising, requires further research. The use of measured impedance data directly as indices of composition, rather than for prediction, has not found extensive application in nutritional research despite its success in other fields. Segmental bioimpedance techniques have advanced substantially in recent years due to availability of simple-to-use analyzers and simplified measurement protocols. The method has been well validated and increasingly adopted in nutritional and clinical practice. Segmental impedance, like conventional whole body impedance approaches, provides indirect prediction of body composition whose accuracy is yet to achieve that of reference techniques such as magnetic reference imaging. This lack of accuracy, however, is outweighed by the method's practicality of use in many settings.

  6. Osmotic and Heat Stress Effects on Segmentation.

    Science.gov (United States)

    Weiss, Julian; Devoto, Stephen H

    2016-01-01

    During vertebrate embryonic development, early skin, muscle, and bone progenitor populations organize into segments known as somites. Defects in this conserved process of segmentation lead to skeletal and muscular deformities, such as congenital scoliosis, a curvature of the spine caused by vertebral defects. Environmental stresses such as hypoxia or heat shock produce segmentation defects, and significantly increase the penetrance and severity of vertebral defects in genetically susceptible individuals. Here we show that a brief exposure to a high osmolarity solution causes reproducible segmentation defects in developing zebrafish (Danio rerio) embryos. Both osmotic shock and heat shock produce border defects in a dose-dependent manner, with an increase in both frequency and severity of defects. We also show that osmotic treatment has a delayed effect on somite development, similar to that observed in heat shocked embryos. Our results establish osmotic shock as an alternate experimental model for stress, affecting segmentation in a manner comparable to other known environmental stressors. The similar effects of these two distinct environmental stressors support a model in which a variety of cellular stresses act through a related response pathway that leads to disturbances in the segmentation process.

  7. Osmotic and Heat Stress Effects on Segmentation.

    Directory of Open Access Journals (Sweden)

    Julian Weiss

    Full Text Available During vertebrate embryonic development, early skin, muscle, and bone progenitor populations organize into segments known as somites. Defects in this conserved process of segmentation lead to skeletal and muscular deformities, such as congenital scoliosis, a curvature of the spine caused by vertebral defects. Environmental stresses such as hypoxia or heat shock produce segmentation defects, and significantly increase the penetrance and severity of vertebral defects in genetically susceptible individuals. Here we show that a brief exposure to a high osmolarity solution causes reproducible segmentation defects in developing zebrafish (Danio rerio embryos. Both osmotic shock and heat shock produce border defects in a dose-dependent manner, with an increase in both frequency and severity of defects. We also show that osmotic treatment has a delayed effect on somite development, similar to that observed in heat shocked embryos. Our results establish osmotic shock as an alternate experimental model for stress, affecting segmentation in a manner comparable to other known environmental stressors. The similar effects of these two distinct environmental stressors support a model in which a variety of cellular stresses act through a related response pathway that leads to disturbances in the segmentation process.

  8. 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.

  9. MBIS: multivariate Bayesian image segmentation tool.

    Science.gov (United States)

    Esteban, Oscar; Wollny, Gert; Gorthi, Subrahmanyam; Ledesma-Carbayo, María-J; Thiran, Jean-Philippe; Santos, Andrés; Bach-Cuadra, Meritxell

    2014-07-01

    We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering tool based on the mixture of multivariate normal distributions model. MBIS supports multichannel bias field correction based on a B-spline model. A second methodological novelty is the inclusion of graph-cuts optimization for the stationary anisotropic hidden Markov random field model. Along with MBIS, we release an evaluation framework that contains three different experiments on multi-site data. We first validate the accuracy of segmentation and the estimated bias field for each channel. MBIS outperforms a widely used segmentation tool in a cross-comparison evaluation. The second experiment demonstrates the robustness of results on atlas-free segmentation of two image sets from scan-rescan protocols on 21 healthy subjects. Multivariate segmentation is more replicable than the monospectral counterpart on T1-weighted images. Finally, we provide a third experiment to illustrate how MBIS can be used in a large-scale study of tissue volume change with increasing age in 584 healthy subjects. This last result is meaningful as multivariate segmentation performs robustly without the need for prior knowledge. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  10. Event segmentation ability uniquely predicts event memory.

    Science.gov (United States)

    Sargent, Jesse Q; Zacks, Jeffrey M; Hambrick, David Z; Zacks, Rose T; Kurby, Christopher A; Bailey, Heather R; Eisenberg, Michelle L; Beck, Taylor M

    2013-11-01

    Memory for everyday events plays a central role in tasks of daily living, autobiographical memory, and planning. Event memory depends in part on segmenting ongoing activity into meaningful units. This study examined the relationship between event segmentation and memory in a lifespan sample to answer the following question: Is the ability to segment activity into meaningful events a unique predictor of subsequent memory, or is the relationship between event perception and memory accounted for by general cognitive abilities? Two hundred and eight adults ranging from 20 to 79years old segmented movies of everyday events and attempted to remember the events afterwards. They also completed psychometric ability tests and tests measuring script knowledge for everyday events. Event segmentation and script knowledge both explained unique variance in event memory above and beyond the psychometric measures, and did so as strongly in older as in younger adults. These results suggest that event segmentation is a basic cognitive mechanism, important for memory across the lifespan. Copyright © 2013 Elsevier B.V. All rights reserved.

  11. Event Segmentation Ability Uniquely Predicts Event Memory

    Science.gov (United States)

    Sargent, Jesse Q.; Zacks, Jeffrey M.; Hambrick, David Z.; Zacks, Rose T.; Kurby, Christopher A.; Bailey, Heather R.; Eisenberg, Michelle L.; Beck, Taylor M.

    2013-01-01

    Memory for everyday events plays a central role in tasks of daily living, autobiographical memory, and planning. Event memory depends in part on segmenting ongoing activity into meaningful units. This study examined the relationship between event segmentation and memory in a lifespan sample to answer the following question: Is the ability to segment activity into meaningful events a unique predictor of subsequent memory, or is the relationship between event perception and memory accounted for by general cognitive abilities? Two hundred and eight adults ranging from 20 to 79 years old segmented movies of everyday events and attempted to remember the events afterwards. They also completed psychometric ability tests and tests measuring script knowledge for everyday events. Event segmentation and script knowledge both explained unique variance in event memory above and beyond the psychometric measures, and did so as strongly in older as in younger adults. These results suggest that event segmentation is a basic cognitive mechanism, important for memory across the lifespan. PMID:23942350

  12. The Knipovich Ridge segmentation and the comparison with other ultraslow spreading ridges

    Science.gov (United States)

    Okino, K.; Curewitz, D.; Asada, M.; Tamaki, K.

    2003-04-01

    The ultraslow-spreading Knipovich Ridge is an ~550 km long, transform-free ridge segment linking the Molloy transform fault and the Mohns Ridge in the Arctic Ocean. Discrete volcanic centers marked by large volcanic constructions and accompanying short wavelength mantle Bouguer anomaly (MBA) lows generally resemble those of the Gakkel Ridge and the easternmost Southwest Indian Ridge. These magmatically robust segment centers are regularly spaced about 85-100 km apart along the ridge, and are characterized by accumulated hummocky terrain, high relief, off-axis seamount chains and significant MBA lows. We suggest that these eruptive centers correspond to areas of enhanced magma flux, and that their spacing reflects the geometry of underlying mantle upwelling cells. The large-scale thermal structure of the mantle primarily controls discrete and focused magmatism, and the relatively wide spacing of these segments may reflect cool mantle beneath the ridge. Segment centers along the southern Knipovich Ridge are characterized by lower relief and smaller MBA anomalies than along the northern section of the ridge. This suggests that ridge obliquity is a secondary control on ridge construction on the Knipovich Ridge, as the obliquity changes from 35 to 49 deg. from north to south, respectively, while spreading rate and axial depth remain approximately constant. A comparison of along-axis depths, MBA anomalies and other fundamental parameters of ultraslow spreading ridges based on previous studies shows that the scale of volcanic edifices tends to decrease as obliquity increases. High relief and large MBA characterize the non-oblique segment of the SWIR, while low relief and small MBA characterize the southern Knipovich Ridge (obliquity 49deg.) and the oblique segment of the SWIR (obliquity 45deg.). The increased obliquity may contribute to decreased effective spreading rates, lower upwelling magma velocity and melt formation, and limited horizontal dike propagation near the

  13. Space Commercialization

    Science.gov (United States)

    Martin, Gary L.

    2011-01-01

    A robust and competitive commercial space sector is vital to continued progress in space. The United States is committed to encouraging and facilitating the growth of a U.S. commercial space sector that supports U.S. needs, is globally competitive, and advances U.S. leadership in the generation of new markets and innovation-driven entrepreneurship. Energize competitive domestic industries to participate in global markets and advance the development of: satellite manufacturing; satellite-based services; space launch; terrestrial applications; and increased entrepreneurship. Purchase and use commercial space capabilities and services to the maximum practical extent Actively explore the use of inventive, nontraditional arrangements for acquiring commercial space goods and services to meet United States Government requirements, including measures such as public-private partnerships, . Refrain from conducting United States Government space activities that preclude, discourage, or compete with U.S. commercial space activities. Pursue potential opportunities for transferring routine, operational space functions to the commercial space sector where beneficial and cost-effective.

  14. Space construction system analysis. Part 2: Cost and programmatics

    Science.gov (United States)

    Vonflue, F. W.; Cooper, W.

    1980-01-01

    Cost and programmatic elements of the space construction systems analysis study are discussed. The programmatic aspects of the ETVP program define a comprehensive plan for the development of a space platform, the construction system, and the space shuttle operations/logistics requirements. The cost analysis identified significant items of cost on ETVP development, ground, and flight segments, and detailed the items of space construction equipment and operations.

  15. Pulmonary Lobe Segmentation with Probabilistic Segmentation of the Fissures and a Groupwise Fissure Prior

    Science.gov (United States)

    Bragman, Felix J.S.; McClelland, Jamie R.; Jacob, Joseph; Hurst, John R.; Hawkes, David J.

    2017-01-01

    A fully automated, unsupervised lobe segmentation algorithm is presented based on a probabilistic segmentation of the fissures and the simultaneous construction of a population model of the fissures. A two-class probabilistic segmentation segments the lung into candidate fissure voxels and the surrounding parenchyma. This was combined with anatomical information and a groupwise fissure prior to drive non-parametric surface fitting to obtain the final segmentation. The performance of our fissure segmentation was validated on 30 patients from the COPDGene cohort, achieving a high median F1-score of 0.90 and showed general insensitivity to filter parameters. We evaluated our lobe segmentation algorithm on the LOLA11 dataset, which contains 55 cases at varying levels of pathology. We achieved the highest score of 0.884 of the automated algorithms. Our method was further tested quantitatively and qualitatively on 80 patients from the COPDGene study at varying levels of functional impairment. Accurate segmentation of the lobes is shown at various degrees of fissure incompleteness for 96% of all cases. We also show the utility of including a groupwise prior in segmenting the lobes in regions of grossly incomplete fissures. PMID:28436850

  16. 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

  17. Real-Time Ultrasound Segmentation, Analysis and Visualisation of Deep Cervical Muscle Structure.

    Science.gov (United States)

    Cunningham, Ryan J; Harding, Peter J; Loram, Ian D

    2017-02-01

    Despite widespread availability of ultrasound and a need for personalised muscle diagnosis (neck/back pain-injury, work related disorder, myopathies, neuropathies), robust, online segmentation of muscles within complex groups remains unsolved by existing methods. For example, Cervical Dystonia (CD) is a prevalent neurological condition causing painful spasticity in one or multiple muscles in the cervical muscle system. Clinicians currently have no method for targeting/monitoring treatment of deep muscles. Automated methods of muscle segmentation would enable clinicians to study, target, and monitor the deep cervical muscles via ultrasound. We have developed a method for segmenting five bilateral cervical muscles and the spine via ultrasound alone, in real-time. Magnetic Resonance Imaging (MRI) and ultrasound data were collected from 22 participants (age: 29.0±6.6, male: 12). To acquire ultrasound muscle segment labels, a novel multimodal registration method was developed, involving MRI image annotation, and shape registration to MRI-matched ultrasound images, via approximation of the tissue deformation. We then applied polynomial regression to transform our annotations and textures into a mean space, before using shape statistics to generate a texture-to-shape dictionary. For segmentation, test images were compared to dictionary textures giving an initial segmentation, and then we used a customized Active Shape Model to refine the fit. Using ultrasound alone, on unseen participants, our technique currently segments a single image in [Formula: see text] to over 86% accuracy (Jaccard index). We propose this approach is applicable generally to segment, extrapolate and visualise deep muscle structure, and analyse statistical features online.

  18. Multi-scale Gaussian representation and outline-learning based cell image segmentation.

    Science.gov (United States)

    Farhan, Muhammad; Ruusuvuori, Pekka; Emmenlauer, Mario; Rämö, Pauli; Dehio, Christoph; Yli-Harja, Olli

    2013-01-01

    High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks.

  19. Multi-scale Gaussian representation and outline-learning based cell image segmentation

    Science.gov (United States)

    2013-01-01

    Background High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. Methods We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. Results and conclusions We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks. PMID:24267488

  20. An Improved Quantum-Inspired Genetic Algorithm for Image Multilevel Thresholding Segmentation

    Directory of Open Access Journals (Sweden)

    Jian Zhang

    2014-01-01

    Full Text Available A multilevel thresholding algorithm for histogram-based image segmentation is presented in this paper. The proposed algorithm introduces an adaptive adjustment strategy of the rotation angle and a cooperative learning strategy into quantum genetic algorithm (called IQGA. An adaptive adjustment strategy of the quantum rotation which is introduced in this study helps improving the convergence speed, search ability, and stability. Cooperative learning enhances the search ability in the high-dimensional solution space by splitting a high-dimensional vector into several one-dimensional vectors. The experimental results demonstrate good performance of the IQGA in solving multilevel thresholding segmentation problem by compared with QGA, GA and PSO.

  1. 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

  2. Automatized spleen segmentation in non-contrast-enhanced MR volume data using subject-specific shape priors

    Science.gov (United States)

    Gloger, Oliver; Tönnies, Klaus; Bülow, Robin; Völzke, Henry

    2017-07-01

    To develop the first fully automated 3D spleen segmentation framework derived from T1-weighted magnetic resonance (MR) imaging data and to verify its performance for spleen delineation and volumetry. This approach considers the issue of low contrast between spleen and adjacent tissue in non-contrast-enhanced MR images. Native T1-weighted MR volume data was performed on a 1.5 T MR system in an epidemiological study. We analyzed random subsamples of MR examinations without pathologies to develop and verify the spleen segmentation framework. The framework is modularized to include different kinds of prior knowledge into the segmentation pipeline. Classification by support vector machines differentiates between five different shape types in computed foreground probability maps and recognizes characteristic spleen regions in axial slices of MR volume data. A spleen-shape space generated by training produces subject-specific prior shape knowledge that is then incorporated into a final 3D level set segmentation method. Individually adapted shape-driven forces as well as image-driven forces resulting from refined foreground probability maps steer the level set successfully to the segment the spleen. The framework achieves promising segmentation results with mean Dice coefficients of nearly 0.91 and low volumetric mean errors of 6.3%. The presented spleen segmentation approach can delineate spleen tissue in native MR volume data. Several kinds of prior shape knowledge including subject-specific 3D prior shape knowledge can be used to guide segmentation processes achieving promising results.

  3. Deriving Motor Primitives through Action Segmentation

    Directory of Open Access Journals (Sweden)

    Paul E. Hemeren

    2011-01-01

    Full Text Available The purpose of the present experiment is to further understand the effect of levels of processing (top-down vs. bottom-up on the perception of movement kinematics and primitives for grasping actions in order to gain insight into possible primitives used by the mirror system. In the present study, we investigated the potential of identifying such primitives using an action segmentation task. Specifically, we investigated whether or not segmentation was driven primarily by the kinematics of the action, as opposed to high-level top-down information about the action and the object used in the action. Participants in the experiment were shown twelve point-light movies of object-centered hand/arm actions that were either presented in their canonical orientation together with the object in question or upside-down (inverted without information about the object. The results show that (1 despite impaired high-level action recognition for the inverted actions participants were able to reliably segment the actions according to lower-level kinematic variables, (2 segmentation behavior in both groups was significantly related to the kinematic variables of change in direction, velocity and acceleration of the wrist (thumb and finger tips for most of the included actions. This indicates that top-down activation of an action representation leads to similar segmentation behavior for hand/arm actions compared to bottom-up, or local, visual processing when performing a fairly unconstrained segmentation task. Motor primitives as parts of more complex actions may therefore be reliably derived through visual segmentation based on movement kinematics.

  4. A summary of image segmentation techniques

    Science.gov (United States)

    Spirkovska, Lilly

    1993-01-01

    Machine vision systems are often considered to be composed of two subsystems: low-level vision and high-level vision. Low level vision consists primarily of image processing operations performed on the input image to produce another image with more favorable characteristics. These operations may yield images with reduced noise or cause certain features of the image to be emphasized (such as edges). High-level vision includes object recognition and, at the highest level, scene interpretation. The bridge between these two subsystems is the segmentation system. Through segmentation, the enhanced input image is mapped into a description involving regions with common features which can be used by the higher level vision tasks. There is no theory on image segmentation. Instead, image segmentation techniques are basically ad hoc and differ mostly in the way they emphasize one or more of the desired properties of an ideal segmenter and in the way they balance and compromise one desired property against another. These techniques can be categorized in a number of different groups including local vs. global, parallel vs. sequential, contextual vs. noncontextual, interactive vs. automatic. In this paper, we categorize the schemes into three main groups: pixel-based, edge-based, and region-based. Pixel-based segmentation schemes classify pixels based solely on their gray levels. Edge-based schemes first detect local discontinuities (edges) and then use that information to separate the image into regions. Finally, region-based schemes start with a seed pixel (or group of pixels) and then grow or split the seed until the original image is composed of only homogeneous regions. Because there are a number of survey papers available, we will not discuss all segmentation schemes. Rather than a survey, we take the approach of a detailed overview. We focus only on the more common approaches in order to give the reader a flavor for the variety of techniques available yet present enough

  5. Tsunamigenic Earthquakes at Along-dip Double Segmentation and Along-strike Single Segmentation near Japan

    Directory of Open Access Journals (Sweden)

    Junji Koyama

    2015-09-01

    Full Text Available A distinct difference of the earthquake activity in megathrust subduction zones is pointed out, concerning seismic segmentations in the vicinity of Japan—that is, the apparent distribution of earthquake hypocenters characterized by Along-dip Double Segmentation (ADDS and Along-strike Single Segmentation (ASSS. ADDS is double aligned seismic-segmentation of trench-ward seismic segments along the Japan Trench and island-ward seismic segments along the Pacific coast of the Japan Islands. The 2011 Tohoku-oki megathrust earthquake of Mw9.0 occurred in ADDS. In the meantime, the subduction zone along the Nankai Trough, the western part of Japan, is the source region of a multiple rupture of seismic segments by the 1707 Houei earthquake, the greatest earthquake in the history of Japan. This subduction zone is narrow under the Japan Islands, which is composed of single aligned seismic-segmentation side by side along the Nankai Trough, which is typical of ASSS. Looking at the world seismicity, the 1960 and 2010 Chile megathrusts, for example, occurred in ASSS, whereas the 1952 Kamchatka and the 1964 Alaska megathrusts occurred in ADDS. These megathrusts in ADDS result from the rupture of strong asperity in the trench-ward seismic segments. Since the asperity of earthquakes in ASSS is concentrated in the shallow part of subduction zones and the asperity of frequent earthquakes in ADDS is in deeper parts of the island-ward seismic segments than those of ASSS, there must be a difference in tsunami excitations due to earthquakes in ADDS and ASSS. An analysis was made in detail of tsunami and seismic excitations of earthquakes in the vicinity of Japan. Tsunami heights of ASSS earthquakes are about two times larger than those of ADDS earthquakes with the same value of seismic moment. The reason for this different tsunami excitation is also considered in relation to the seismic segmentations of ADDS and ASSS.

  6. The Case of the Great Space Exploration: An Educator Guide with Activities in Mathematics, Science, and Technology. The NASA SCI Files. EG-2004-09-12-LARC

    Science.gov (United States)

    Ricles, Shannon; Jaramillo, Becky; Fargo, Michelle

    2004-01-01

    In this companion to the "NASA SCI Files" episode "The Case of the Great Space Exploration," the tree house detectives learn about NASA's new vision for exploring space. In four segments aimed at grades 3-5, students learn about a variety of aspects of space exploration. Each segment of the guide includes an overview, a set of objectives,…

  7. Segmentation and Visualisation of Human Brain Structures

    Energy Technology Data Exchange (ETDEWEB)

    Hult, Roger

    2003-10-01

    In this thesis the focus is mainly on the development of segmentation techniques for human brain structures and of the visualisation of such structures. The images of the brain are both anatomical images (magnet resonance imaging (MRI) and autoradiography) and functional images that show blood flow (functional magnetic imaging (fMRI), positron emission tomography (PET), and single photon emission tomography (SPECT)). When working with anatomical images, the structures segmented are visible as different parts of the brain, e.g. the brain cortex, the hippocampus, or the amygdala. In functional images, the activity or the blood flow that be seen. Grey-level morphology methods are used in the segmentations to make tissue types in the images more homogenous and minimise difficulties with connections to outside tissue. A method for automatic histogram thresholding is also used. Furthermore, there are binary operations such as logic operation between masks and binary morphology operations. The visualisation of the segmented structures uses either surface rendering or volume rendering. For the visualisation of thin structures, surface rendering is the better choice since otherwise some voxels might be missed. It is possible to display activation from a functional image on the surface of a segmented cortex. A new method for autoradiographic images has been developed, which integrates registration, background compensation, and automatic thresholding to get faster and more reliable results than the standard techniques give.

  8. -Means Based Fingerprint Segmentation with Sensor Interoperability

    Directory of Open Access Journals (Sweden)

    Yang Xiukun

    2010-01-01

    Full Text Available A critical step in an automatic fingerprint recognition system is the segmentation of fingerprint images. Existing methods are usually designed to segment fingerprint images originated from a certain sensor. Thus their performances are significantly affected when dealing with fingerprints collected by different sensors. This work studies the sensor interoperability of fingerprint segmentation algorithms, which refers to the algorithm's ability to adapt to the raw fingerprints obtained from different sensors. We empirically analyze the sensor interoperability problem, and effectively address the issue by proposing a -means based segmentation method called SKI. SKI clusters foreground and background blocks of a fingerprint image based on the -means algorithm, where a fingerprint block is represented by a 3-dimensional feature vector consisting of block-wise coherence, mean, and variance (abbreviated as CMV. SKI also employs morphological postprocessing to achieve favorable segmentation results. We perform SKI on each fingerprint to ensure sensor interoperability. The interoperability and robustness of our method are validated by experiments performed on a number of fingerprint databases which are obtained from various sensors.

  9. Extracting Fundamental Periods to Segment Biomedical Signals.

    Science.gov (United States)

    Motrenko, Anastasia; Strijov, Vadim

    2016-11-01

    We address the problem of segmenting nearly periodic time series into period-like segments. We introduce a definition of nearly periodic time series via triplets 〈 basic shape, shape transformation, time scaling 〉 that covers a wide range of time series. To split the time series into periods, we select a pair of principal components of the Hankel matrix. We then cut the trajectory of the selected principal components by its symmetry axis and, thus, obtaining half-periods that are merged into segments. We describe a method of automatic selection of periodic pairs of principal components, corresponding to the fundamental periodicity. We demonstrate the application of the proposed method to the problem of period extraction for accelerometric time series of human gait. We see the automatic segmentation into periods as a problem of major importance for human activity recognition problem, since it allows to obtain interpretable segments: each extracted period can be seen as an ultimate entity of gait. The method we propose is more general compared to the application specific methods and can be used for any nearly periodical time series. We compare its performance to classical mathematical methods of period extraction and find that it is not only comparable to the alternatives, but in some cases performs better.

  10. Experience with mechanical segmentation of reactor internals

    International Nuclear Information System (INIS)

    Carlson, R.; Hedin, G.

    2003-01-01

    Operating experience from BWE:s world-wide has shown that many plants experience initial cracking of the reactor internals after approximately 20 to 25 years of service life. This ''mid-life crisis'', considering a plant design life of 40 years, is now being addressed by many utilities. Successful resolution of these issues should give many more years of trouble-free operation. Replacement of reactor internals could be, in many cases, the most favourable option to achieve this. The proactive strategy of many utilities to replace internals in a planned way is a market-driven effort to minimize the overall costs for power generation, including time spent for handling contingencies and unplanned outages. Based on technical analyses, knowledge about component market prices and in-house costs, a cost-effective, optimized strategy for inspection, mitigation and replacements can be implemented. Also decommissioning of nuclear plants has become a reality for many utilities as numerous plants worldwide are closed due to age and/or other reasons. These facts address a need for safe, fast and cost-effective methods for segmentation of internals. Westinghouse has over the last years developed methods for segmentation of internals and has also carried out successful segmentation projects. Our experience from the segmentation business for Nordic BWR:s is that the most important parameters to consider when choosing a method and equipment for a segmentation project are: - Safety, - Cost-effectiveness, - Cleanliness, - Reliability. (orig.)

  11. Edge Segment-Based Automatic Video Surveillance

    Directory of Open Access Journals (Sweden)

    Oksam Chae

    2007-12-01

    Full Text Available This paper presents a moving-object segmentation algorithm using edge information as segment. The proposed method is developed to address challenges due to variations in ambient lighting and background contents. We investigated the suitability of the proposed algorithm in comparison with the traditional-intensity-based as well as edge-pixel-based detection methods. In our method, edges are extracted from video frames and are represented as segments using an efficiently designed edge class. This representation helps to obtain the geometric information of edge in the case of edge matching and moving-object segmentation; and facilitates incorporating knowledge into edge segment during background modeling and motion tracking. An efficient approach for background initialization and robust method of edge matching is presented, to effectively reduce the risk of false alarm due to illumination change and camera motion while maintaining the high sensitivity to the presence of moving object. Detected moving edges are utilized along with watershed algorithm for extracting video object plane (VOP with more accurate boundary. Experiment results with real image sequence reflect that the proposed method is suitable for automated video surveillance applications in various monitoring systems.

  12. 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.

  13. Bayesian segmentation of brainstem structures in MRI

    DEFF Research Database (Denmark)

    Iglesias, Juan Eugenio; Van Leemput, Koen; Bhatt, Priyanka

    2015-01-01

    In this paper we present a method to segment four brainstem structures (midbrain, pons, medulla oblongata and superior cerebellar peduncle) from 3D brain MRI scans. The segmentation method relies on a probabilistic atlas of the brainstem and its neighboring brain structures. To build the atlas, w...... is able to detect differential effects of AD on the brainstem structures. The method will be implemented as part of the popular neuroimaging package FreeSurfer.......In this paper we present a method to segment four brainstem structures (midbrain, pons, medulla oblongata and superior cerebellar peduncle) from 3D brain MRI scans. The segmentation method relies on a probabilistic atlas of the brainstem and its neighboring brain structures. To build the atlas, we...... combined a dataset of 39 scans with already existing manual delineations of the whole brainstem and a dataset of 10 scans in which the brainstem structures were manually labeled with a protocol that was specifically designed for this study. The resulting atlas can be used in a Bayesian framework to segment...

  14. Infants generalize representations of statistically segmented words

    Directory of Open Access Journals (Sweden)

    Katharine eGraf Estes

    2012-10-01

    Full Text Available The acoustic variation in language presents learners with a substantial challenge. To learn by tracking statistical regularities in speech, infants must recognize words across tokens that differ based on characteristics such as the speaker’s voice, affect, or the sentence context. Previous statistical learning studies have not investigated how these types of surface form variation affect learning. The present experiments used tasks tailored to two distinct developmental levels to investigate the robustness of statistical learning to variation. Experiment 1 examined statistical word segmentation in 11-month-olds and found that infants can recognize statistically segmented words across a change in the speaker’s voice from segmentation to testing. The direction of infants’ preferences suggests that recognizing words across a voice change is more difficult than recognizing them in a consistent voice. Experiment 2 tested whether 17-month-olds can generalize the output of statistical learning across variation to support word learning. The infants were successful in their generalization; they associated referents with statistically defined words despite a change in voice from segmentation to label learning. Infants’ learning patterns also indicate that they formed representations of across-word syllable sequences during segmentation. Thus, low probability sequences can act as object labels in some conditions. The findings of these experiments suggest that the units that emerge during statistical learning are not perceptually constrained, but rather are robust to naturalistic acoustic variation.

  15. Infants generalize representations of statistically segmented words.

    Science.gov (United States)

    Graf Estes, Katharine

    2012-01-01

    The acoustic variation in language presents learners with a substantial challenge. To learn by tracking statistical regularities in speech, infants must recognize words across tokens that differ based on characteristics such as the speaker's voice, affect, or the sentence context. Previous statistical learning studies have not investigated how these types of non-phonemic surface form variation affect learning. The present experiments used tasks tailored to two distinct developmental levels to investigate the robustness of statistical learning to variation. Experiment 1 examined statistical word segmentation in 11-month-olds and found that infants can recognize statistically segmented words across a change in the speaker's voice from segmentation to testing. The direction of infants' preferences suggests that recognizing words across a voice change is more difficult than recognizing them in a consistent voice. Experiment 2 tested whether 17-month-olds can generalize the output of statistical learning across variation to support word learning. The infants were successful in their generalization; they associated referents with statistically defined words despite a change in voice from segmentation to label learning. Infants' learning patterns also indicate that they formed representations of across word syllable sequences during segmentation. Thus, low probability sequences can act as object labels in some conditions. The findings of these experiments suggest that the units that emerge during statistical learning are not perceptually constrained, but rather are robust to naturalistic acoustic variation.

  16. Molecular basis for photoreceptor outer segment architecture.

    Science.gov (United States)

    Goldberg, Andrew F X; Moritz, Orson L; Williams, David S

    2016-11-01

    To serve vision, vertebrate rod and cone photoreceptors must detect photons, convert the light stimuli into cellular signals, and then convey the encoded information to downstream neurons. Rods and cones are sensory neurons that each rely on specialized ciliary organelles to detect light. These organelles, called outer segments, possess elaborate architectures that include many hundreds of light-sensitive membranous disks arrayed one atop another in precise register. These stacked disks capture light and initiate the chain of molecular and cellular events that underlie normal vision. Outer segment organization is challenged by an inherently dynamic nature; these organelles are subject to a renewal process that replaces a significant fraction of their disks (up to ∼10%) on a daily basis. In addition, a broad range of environmental and genetic insults can disrupt outer segment morphology to impair photoreceptor function and viability. In this chapter, we survey the major progress that has been made for understanding the molecular basis of outer segment architecture. We also discuss key aspects of organelle lipid and protein composition, and highlight distributions, interactions, and potential structural functions of key OS-resident molecules, including: kinesin-2, actin, RP1, prominin-1, protocadherin 21, peripherin-2/rds, rom-1, glutamic acid-rich proteins, and rhodopsin. Finally, we identify key knowledge gaps and challenges that remain for understanding how normal outer segment architecture is established and maintained. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Borel Spaces

    CERN Document Server

    Berberian, S K

    2002-01-01

    A detailed exposition of G.W. Mackey's theory of Borel spaces (standard, substandard, analytic), based on results in Chapter 9 of Bourbaki's General Topology. Appended are five informal lectures on the subject (given at the CIMPA/ICPAM Summer School, Nice, 1986), sketching the connection between Borel spaces and representations of operator algebras.

  18. Space psychology

    Science.gov (United States)

    Parin, V. V.; Gorbov, F. D.; Kosmolinskiy, F. P.

    1974-01-01

    Psychological selection of astronauts considers mental responses and adaptation to the following space flight stress factors: (1) confinement in a small space; (2) changes in three dimensional orientation; (3) effects of altered gravity and weightlessness; (4) decrease in afferent nerve pulses; (5) a sensation of novelty and danger; and (6) a sense of separation from earth.

  19. Performative Spaces

    DEFF Research Database (Denmark)

    Svaneklink, Annette

    2009-01-01

    that can be related to traditional architectural concepts in terms of dealing with space, body, time and movement. The paper considers this performativity and dual spatiality as being a processual architecture, constantly reconfiguring new hybrids between space, image and user. This dual spatiality raises...

  20. Space Microbiology

    Science.gov (United States)

    Horneck, Gerda; Klaus, David M.; Mancinelli, Rocco L.

    2010-01-01

    Summary: The responses of microorganisms (viruses, bacterial cells, bacterial and fungal spores, and lichens) to selected factors of space (microgravity, galactic cosmic radiation, solar UV radiation, and space vacuum) were determined in space and laboratory simulation experiments. In general, microorganisms tend to thrive in the space flight environment in terms of enhanced growth parameters and a demonstrated ability to proliferate in the presence of normally inhibitory levels of antibiotics. The mechanisms responsible for the observed biological responses, however, are not yet fully understood. A hypothesized interaction of microgravity with radiation-induced DNA repair processes was experimentally refuted. The survival of microorganisms in outer space was investigated to tackle questions on the upper boundary of the biosphere and on the likelihood of interplanetary transport of microorganisms. It was found that extraterrestrial solar UV radiation was the most deleterious factor of space. Among all organisms tested, only lichens (Rhizocarpon geographicum and Xanthoria elegans) maintained full viability after 2 weeks in outer space, whereas all other test systems were inactivated by orders of magnitude. Using optical filters and spores of Bacillus subtilis as a biological UV dosimeter, it was found that the current ozone layer reduces the biological effectiveness of solar UV by 3 orders of magnitude. If shielded against solar UV, spores of B. subtilis were capable of surviving in space for up to 6 years, especially if embedded in clay or meteorite powder (artificial meteorites). The data support the likelihood of interplanetary transfer of microorganisms within meteorites, the so-called lithopanspermia hypothesis. PMID:20197502