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.

Construction of carrier state viruses with partial genomes of the segmented dsRNA bacteriophages

International Nuclear Information System (INIS)

Sun Yang; Qiao Xueying; Mindich, Leonard

2004-01-01

The cystoviridae are bacteriophages with genomes of three segments of dsRNA enclosed within a polyhedral capsid. Two members of this family, PHI6 and PHI8, have been shown to form carrier states in which the virus replicates as a stable episome in the host bacterium while expressing reporter genes such as kanamycin resistance or lacα. The carrier state does not require the activity of all the genes necessary for phage production. It is possible to generate carrier states by infecting cells with virus or by electroporating nonreplicating plasmids containing cDNA copies of the viral genomes into the host cells. We have found that carrier states in both PHI6 and PHI8 can be formed at high frequency with all three genomic segments or with only the large and small segments. The large genomic segment codes for the proteins that constitute the inner core of the virus, which is the structure responsible for the packaging and replication of the genome. In PHI6, a carrier state can be formed with the large and middle segment if mutations occur in the gene for the major structural protein of the inner core. In PHI8, carrier state formation requires the activity of genes 8 and 12 of segment S

Fast and accurate semi-automated segmentation method of spinal cord MR images at 3T applied to the construction of a cervical spinal cord template.

Directory of Open Access Journals (Sweden)

Mohamed-Mounir El Mendili

Full Text Available To design a fast and accurate semi-automated segmentation method for spinal cord 3T MR images and to construct a template of the cervical spinal cord.A semi-automated double threshold-based method (DTbM was proposed enabling both cross-sectional and volumetric measures from 3D T2-weighted turbo spin echo MR scans of the spinal cord at 3T. Eighty-two healthy subjects, 10 patients with amyotrophic lateral sclerosis, 10 with spinal muscular atrophy and 10 with spinal cord injuries were studied. DTbM was compared with active surface method (ASM, threshold-based method (TbM and manual outlining (ground truth. Accuracy of segmentations was scored visually by a radiologist in cervical and thoracic cord regions. Accuracy was also quantified at the cervical and thoracic levels as well as at C2 vertebral level. To construct a cervical template from healthy subjects' images (n=59, a standardization pipeline was designed leading to well-centered straight spinal cord images and accurate probability tissue map.Visual scoring showed better performance for DTbM than for ASM. Mean Dice similarity coefficient (DSC was 95.71% for DTbM and 90.78% for ASM at the cervical level and 94.27% for DTbM and 89.93% for ASM at the thoracic level. Finally, at C2 vertebral level, mean DSC was 97.98% for DTbM compared with 98.02% for TbM and 96.76% for ASM. DTbM showed similar accuracy compared with TbM, but with the advantage of limited manual interaction.A semi-automated segmentation method with limited manual intervention was introduced and validated on 3T images, enabling the construction of a cervical spinal cord template.

Fast and accurate semi-automated segmentation method of spinal cord MR images at 3T applied to the construction of a cervical spinal cord template.

Science.gov (United States)

El Mendili, Mohamed-Mounir; Chen, Raphaël; Tiret, Brice; Villard, Noémie; Trunet, Stéphanie; Pélégrini-Issac, Mélanie; Lehéricy, Stéphane; Pradat, Pierre-François; Benali, Habib

2015-01-01

To design a fast and accurate semi-automated segmentation method for spinal cord 3T MR images and to construct a template of the cervical spinal cord. A semi-automated double threshold-based method (DTbM) was proposed enabling both cross-sectional and volumetric measures from 3D T2-weighted turbo spin echo MR scans of the spinal cord at 3T. Eighty-two healthy subjects, 10 patients with amyotrophic lateral sclerosis, 10 with spinal muscular atrophy and 10 with spinal cord injuries were studied. DTbM was compared with active surface method (ASM), threshold-based method (TbM) and manual outlining (ground truth). Accuracy of segmentations was scored visually by a radiologist in cervical and thoracic cord regions. Accuracy was also quantified at the cervical and thoracic levels as well as at C2 vertebral level. To construct a cervical template from healthy subjects' images (n=59), a standardization pipeline was designed leading to well-centered straight spinal cord images and accurate probability tissue map. Visual scoring showed better performance for DTbM than for ASM. Mean Dice similarity coefficient (DSC) was 95.71% for DTbM and 90.78% for ASM at the cervical level and 94.27% for DTbM and 89.93% for ASM at the thoracic level. Finally, at C2 vertebral level, mean DSC was 97.98% for DTbM compared with 98.02% for TbM and 96.76% for ASM. DTbM showed similar accuracy compared with TbM, but with the advantage of limited manual interaction. A semi-automated segmentation method with limited manual intervention was introduced and validated on 3T images, enabling the construction of a cervical spinal cord template.

Méthodes de graphe pour la segmentation d'images et le suivi d'objets dynamiques

OpenAIRE

Wang , Xiaofang

2015-01-01

Image segmentation is a fundamental problem in computer vision. In particular, unsupervised image segmentation is an important component in many high-level algorithms and practical vision systems. In this dissertation, we propose three methods that approach image segmentation from different angles of graph based methods and are proved powerful to address these problems. Our first method develops an original graph construction method. We also analyze different types of graph construction metho...

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.)

Applications of magnetic resonance image segmentation in neurology

Science.gov (United States)

Heinonen, Tomi; Lahtinen, Antti J.; Dastidar, Prasun; Ryymin, Pertti; Laarne, Paeivi; Malmivuo, Jaakko; Laasonen, Erkki; Frey, Harry; Eskola, Hannu

1999-05-01

After the introduction of digital imagin devices in medicine computerized tissue recognition and classification have become important in research and clinical applications. Segmented data can be applied among numerous research fields including volumetric analysis of particular tissues and structures, construction of anatomical modes, 3D visualization, and multimodal visualization, hence making segmentation essential in modern image analysis. In this research project several PC based software were developed in order to segment medical images, to visualize raw and segmented images in 3D, and to produce EEG brain maps in which MR images and EEG signals were integrated. The software package was tested and validated in numerous clinical research projects in hospital environment.

Weakly supervised semantic segmentation using fore-background priors

Science.gov (United States)

Han, Zheng; Xiao, Zhitao; Yu, Mingjun

2017-07-01

Weakly-supervised semantic segmentation is a challenge in the field of computer vision. Most previous works utilize the labels of the whole training set and thereby need the construction of a relationship graph about image labels, thus result in expensive computation. In this study, we tackle this problem from a different perspective. We proposed a novel semantic segmentation algorithm based on background priors, which avoids the construction of a huge graph in whole training dataset. Specifically, a random forest classifier is obtained using weakly supervised training data .Then semantic texton forest (STF) feature is extracted from image superpixels. Finally, a CRF based optimization algorithm is proposed. The unary potential of CRF derived from the outputting probability of random forest classifier and the robust saliency map as background prior. Experiments on the MSRC21 dataset show that the new algorithm outperforms some previous influential weakly-supervised segmentation algorithms. Furthermore, the use of efficient decision forests classifier and parallel computing of saliency map significantly accelerates the implementation.

Construction of a cDNA library from human retinal pigment epithelial cells challenged with rod outer segments.

Science.gov (United States)

Cavaney, D M; Rakoczy, P E; Constable, I J

1995-05-01

To study genes expressed by retinal pigment epithelial (RPE) cells during phagocytosis and digestion of rod outer segments (ROS), a complementary (c)DNA library was produced using an in-vitro model. The cDNA library can be used to study molecular changes which contribute to the development of diseases due to a failure in outer segment phagocytosis and digestion by RPE cells. Here we demonstrate a way to study genes and their functions using a molecular biological approach and describing the first step involved in this process, the construction of a cDNA library. Human RPE cells obtained from the eyes of a seven-year-old donor were cultured and challenged with bovine ROS. The culture was harvested and total RNA was extracted. Complementary DNA was transcribed from the messenger (m)RNA and was directionally cloned into the LambdaGEM-4 bacteriophage vector successfully. Some clones were picked and the DNA extracted, to determine the size of the inserts as a measure of the quality of the library. Molecular biology and cell culture are important tools to be used in eye research, especially in areas where tissue is limiting and animal models are not available. We now have a ROS challenged RPE cDNA library which will be used to identify genes responsible for degrading phagocytosed debris within the retinal pigment epithelium.

Attributed relational graphs for cell nucleus segmentation in fluorescence microscopy images.

Science.gov (United States)

Arslan, Salim; Ersahin, Tulin; Cetin-Atalay, Rengul; Gunduz-Demir, Cigdem

2013-06-01

More rapid and accurate high-throughput screening in molecular cellular biology research has become possible with the development of automated microscopy imaging, for which cell nucleus segmentation commonly constitutes the core step. Although several promising methods exist for segmenting the nuclei of monolayer isolated and less-confluent cells, it still remains an open problem to segment the nuclei of more-confluent cells, which tend to grow in overlayers. To address this problem, we propose a new model-based nucleus segmentation algorithm. This algorithm models how a human locates a nucleus by identifying the nucleus boundaries and piecing them together. In this algorithm, we define four types of primitives to represent nucleus boundaries at different orientations and construct an attributed relational graph on the primitives to represent their spatial relations. Then, we reduce the nucleus identification problem to finding predefined structural patterns in the constructed graph and also use the primitives in region growing to delineate the nucleus borders. Working with fluorescence microscopy images, our experiments demonstrate that the proposed algorithm identifies nuclei better than previous nucleus segmentation algorithms.

AISLE: an automatic volumetric segmentation method for the study of lung allometry.

Science.gov (United States)

Ren, Hongliang; Kazanzides, Peter

2011-01-01

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

CT image segmentation methods for bone used in medical additive manufacturing.

Science.gov (United States)

van Eijnatten, Maureen; van Dijk, Roelof; Dobbe, Johannes; Streekstra, Geert; Koivisto, Juha; Wolff, Jan

2018-01-01

The accuracy of additive manufactured medical constructs is limited by errors introduced during image segmentation. The aim of this study was to review the existing literature on different image segmentation methods used in medical additive manufacturing. Thirty-two publications that reported on the accuracy of bone segmentation based on computed tomography images were identified using PubMed, ScienceDirect, Scopus, and Google Scholar. The advantages and disadvantages of the different segmentation methods used in these studies were evaluated and reported accuracies were compared. The spread between the reported accuracies was large (0.04 mm - 1.9 mm). Global thresholding was the most commonly used segmentation method with accuracies under 0.6 mm. The disadvantage of this method is the extensive manual post-processing required. Advanced thresholding methods could improve the accuracy to under 0.38 mm. However, such methods are currently not included in commercial software packages. Statistical shape model methods resulted in accuracies from 0.25 mm to 1.9 mm but are only suitable for anatomical structures with moderate anatomical variations. Thresholding remains the most widely used segmentation method in medical additive manufacturing. To improve the accuracy and reduce the costs of patient-specific additive manufactured constructs, more advanced segmentation methods are required. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Segmentation in reading and film comprehension.

Science.gov (United States)

Zacks, Jeffrey M; Speer, Nicole K; Reynolds, Jeremy R

2009-05-01

When reading a story or watching a film, comprehenders construct a series of representations in order to understand the events depicted. Discourse comprehension theories and a recent theory of perceptual event segmentation both suggest that comprehenders monitor situational features such as characters' goals, to update these representations at natural boundaries in activity. However, the converging predictions of these theories had previously not been tested directly. Two studies provided evidence that changes in situational features such as characters, their locations, their interactions with objects, and their goals are related to the segmentation of events in both narrative texts and films. A 3rd study indicated that clauses with event boundaries are read more slowly than are other clauses and that changes in situational features partially mediate this relation. A final study suggested that the predictability of incoming information influences reading rate and possibly event segmentation. Taken together, these results suggest that processing situational changes during comprehension is an important determinant of how one segments ongoing activity into events and that this segmentation is related to the control of processing during reading. (c) 2009 APA, all rights reserved.

Segmentation of human skull in MRI using statistical shape information from CT data.

Science.gov (United States)

Wang, Defeng; Shi, Lin; Chu, Winnie C W; Cheng, Jack C Y; Heng, Pheng Ann

2009-09-01

To automatically segment the skull from the MRI data using a model-based three-dimensional segmentation scheme. This study exploited the statistical anatomy extracted from the CT data of a group of subjects by means of constructing an active shape model of the skull surfaces. To construct a reliable shape model, a novel approach was proposed to optimize the automatic landmarking on the coupled surfaces (i.e., the skull vault) by minimizing the description length that incorporated local thickness information. This model was then used to locate the skull shape in MRI of a different group of patients. Compared with performing landmarking separately on the coupled surfaces, the proposed landmarking method constructed models that had better generalization ability and specificity. The segmentation accuracies were measured by the Dice coefficient and the set difference, and compared with the method based on mathematical morphology operations. The proposed approach using the active shape model based on the statistical skull anatomy presented in the head CT data contributes to more reliable segmentation of the skull from MRI data.

Creation of voxel-based models for paediatric dosimetry from automatic segmentation methods

International Nuclear Information System (INIS)

Acosta, O.; Li, R.; Ourselin, S.; Caon, M.

2006-01-01

Full text: The first computational models representing human anatomy were mathematical phantoms, but still far from accurate representations of human body. These models have been used with radiation transport codes (Monte Carlo) to estimate organ doses from radiological procedures. Although new medical imaging techniques have recently allowed the construction of voxel-based models based on the real anatomy, few children models from individual CT or MRI data have been reported [1,3]. For pediatric dosimetry purposes, a large range of voxel models by ages is required since scaling the anatomy from existing models is not sufficiently accurate. The small number of models available arises from the small number of CT or MRI data sets of children available and the long amount of time required to segment the data sets. The existing models have been constructed by manual segmentation slice by slice and using simple thresholding techniques. In medical image segmentation, considerable difficulties appear when applying classical techniques like thresholding or simple edge detection. Until now, any evidence of more accurate or near-automatic methods used in construction of child voxel models exists. We aim to construct a range of pediatric voxel models, integrating automatic or semi-automatic 3D segmentation techniques. In this paper we present the first stage of this work using pediatric CT data.

The relevance of segments reports – measurement methodology

Directory of Open Access Journals (Sweden)

Tomasz Zimnicki

2017-09-01

Full Text Available The segment report is one of the areas of financial statements, and it obliges a company to provide infor-mation about the economic situation in each of its activity areas. The article evaluates the change of segment reporting standards from IAS14R to IFRS8 in the context of feature relevance. It presents the construction of a measure which allows the relevance of segment disclosures to be determined. The created measure was used to study periodical reports published by companies listed on the main market of the Warsaw Stock Exchange from three reporting periods – 2008, 2009 and 2013. Based on the re-search results, it was found that the change of segment reporting standards from IAS14R to IFRS8 in the context of relevance was legitimate.

Tissues segmentation based on multi spectral medical images

Science.gov (United States)

Li, Ya; Wang, Ying

2017-11-01

Each band image contains the most obvious tissue feature according to the optical characteristics of different tissues in different specific bands for multispectral medical images. In this paper, the tissues were segmented by their spectral information at each multispectral medical images. Four Local Binary Patter descriptors were constructed to extract blood vessels based on the gray difference between the blood vessels and their neighbors. The segmented tissue in each band image was merged to a clear image.

Continuously live image processor for drift chamber track segment triggering

International Nuclear Information System (INIS)

Berenyi, A.; Chen, H.K.; Dao, K.

1999-01-01

The first portion of the BaBar experiment Level 1 Drift Chamber Trigger pipeline is the Track Segment Finder (TSF). Using a novel method incorporating both occupancy and drift-time information, the TSF system continually searches for segments in the supercells of the full 7104-wire Drift Chamber hit image at 3.7 MHz. The TSF was constructed to operate in a potentially high beam-background environment while achieving high segment-finding efficiency, deadtime-free operation, a spatial resolution of 5 simulated physics events

The semiotics of medical image Segmentation.

Science.gov (United States)

Baxter, John S H; Gibson, Eli; Eagleson, Roy; Peters, Terry M

2018-02-01

As the interaction between clinicians and computational processes increases in complexity, more nuanced mechanisms are required to describe how their communication is mediated. Medical image segmentation in particular affords a large number of distinct loci for interaction which can act on a deep, knowledge-driven level which complicates the naive interpretation of the computer as a symbol processing machine. Using the perspective of the computer as dialogue partner, we can motivate the semiotic understanding of medical image segmentation. Taking advantage of Peircean semiotic traditions and new philosophical inquiry into the structure and quality of metaphors, we can construct a unified framework for the interpretation of medical image segmentation as a sign exchange in which each sign acts as an interface metaphor. This allows for a notion of finite semiosis, described through a schematic medium, that can rigorously describe how clinicians and computers interpret the signs mediating their interaction. Altogether, this framework provides a unified approach to the understanding and development of medical image segmentation interfaces. Copyright © 2017 Elsevier B.V. All rights reserved.

Graph run-length matrices for histopathological image segmentation.

Science.gov (United States)

Tosun, Akif Burak; Gunduz-Demir, Cigdem

2011-03-01

The histopathological examination of tissue specimens is essential for cancer diagnosis and grading. However, this examination is subject to a considerable amount of observer variability as it mainly relies on visual interpretation of pathologists. To alleviate this problem, it is very important to develop computational quantitative tools, for which image segmentation constitutes the core step. In this paper, we introduce an effective and robust algorithm for the segmentation of histopathological tissue images. This algorithm incorporates the background knowledge of the tissue organization into segmentation. For this purpose, it quantifies spatial relations of cytological tissue components by constructing a graph and uses this graph to define new texture features for image segmentation. This new texture definition makes use of the idea of gray-level run-length matrices. However, it considers the runs of cytological components on a graph to form a matrix, instead of considering the runs of pixel intensities. Working with colon tissue images, our experiments demonstrate that the texture features extracted from "graph run-length matrices" lead to high segmentation accuracies, also providing a reasonable number of segmented regions. Compared with four other segmentation algorithms, the results show that the proposed algorithm is more effective in histopathological image segmentation.

Construction of calibration curve for accountancy tank

International Nuclear Information System (INIS)

Kato, Takayuki; Goto, Yoshiki; Nidaira, Kazuo

2009-01-01

Tanks are equipped in a reprocessing plant for accounting solution of nuclear material. The careful measurement of volume in tanks is very important to implement rigorous accounting of nuclear material. The calibration curve relating the volume and level of solution needs to be constructed, where the level is determined by differential pressure of dip tubes. Several calibration curves are usually employed, but it's not explicitly decided how many segment are used, where to select segment, or what should be the degree of polynomial curve. These parameters, i.e., segment and degree of polynomial curve are mutually interrelated to give the better performance of calibration curve. Here we present the construction technique of giving optimum calibration curves and their characteristics. (author)

Segmentation hyperspectrale de forets tropicales par arbres de partition binaires

OpenAIRE

Tochon, Guillaume; Feret, J.B.; Valero, Silvia; Martin, R.E.; Tupayachi, R.; Chanussot, Jocelyn; Salembier Clairon, Philippe Jean; Asner, G.P.

2013-01-01

La segmentation d’images de forêts tropicales est un outil important pour faciliter le travail des écologues. Dans ce papier, nous proposons une nouvelle méthode de segmentation pour les images hyperspectrales, basée sur la construction d’un arbre de partition binaire (APB). Nous introduisons tout d’abord une étape de prétraitement combinant une analyse en composantes principales et la définition de cartes de pré-segmentation, afin de réduire spatialement et spectralement le volume de données...

An Algorithm for Morphological Segmentation of Esperanto Words

Directory of Open Access Journals (Sweden)

Guinard Theresa

2016-04-01

Full Text Available Morphological analysis (finding the component morphemes of a word and tagging morphemes with part-of-speech information is a useful preprocessing step in many natural language processing applications, especially for synthetic languages. Compound words from the constructed language Esperanto are formed by straightforward agglutination, but for many words, there is more than one possible sequence of component morphemes. However, one segmentation is usually more semantically probable than the others. This paper presents a modified n-gram Markov model that finds the most probable segmentation of any Esperanto word, where the model’s states represent morpheme part-of-speech and semantic classes. The overall segmentation accuracy was over 98% for a set of presegmented dictionary words.

Indigenous lunar construction materials

Science.gov (United States)

Rogers, Wayne P.; Sture, Stein

1991-01-01

The utilization of local resources for the construction and operation of a lunar base can significantly reduce the cost of transporting materials and supplies from Earth. The feasibility of processing lunar regolith to form construction materials and structural components is investigated. A preliminary review of potential processing methods such as sintering, hot-pressing, liquification, and cast basalt techniques, was completed. The processing method proposed is a variation on the cast basalt technique. It involves liquification of the regolith at 1200-1300 C, casting the liquid into a form, and controlled cooling. While the process temperature is higher than that for sintering or hot-pressing (1000-1100 C), this method is expected to yield a true engineering material with low variability in properties, high strength, and the potential to form large structural components. A scenario for this processing method was integrated with a design for a representative lunar base structure and potential construction techniques. The lunar shelter design is for a modular, segmented, pressurized, hemispherical dome which could serve as habitation and laboratory space. Based on this design, estimates of requirements for power, processing equipment, and construction equipment were made. This proposed combination of material processing method, structural design, and support requirements will help to establish the feasibility of lunar base construction using indigenous materials. Future work will refine the steps of the processing method. Specific areas where more information is needed are: furnace characteristics in vacuum; heat transfer during liquification; viscosity, pouring and forming behavior of molten regolith; design of high temperature forms; heat transfer during cooling; recrystallization of basalt; and refinement of estimates of elastic moduli, compressive and tensile strength, thermal expansion coefficient, thermal conductivity, and heat capacity. The preliminary

The deformation behavior of the cervical spine segment

Science.gov (United States)

Kolmakova, T. V.; Rikun, Yu. A.

2017-09-01

The paper describes the model of the cervical spine segment (C3-C4) and the calculation results of its deformation behavior at flexion. The segment model was built based on the experimental literature data taking into account the presence of the cortical and cancellous bone tissue of vertebral bodies. Degenerative changes of the intervertebral disk (IVD) were simulated through a reduction of the disc height and an increase of Young's modulus. The construction of the geometric model of the cervical spine segment and the calculations of the stress-strain state were carried out in the ANSYS software complex. The calculation results show that the biggest protrusion of the IVD in bending direction of segment is observed when IVD height is reduced. The disc protrusion is reduced with an increase of Young's modulus. The largest protrusion in the direction of flexion of the segment is the intervertebral disk with height of 4.3 mm and elastic modulus of 2.5 MPa. The results of the study can be useful to specialists in the field of biomechanics, medical materials science and prosthetics.

PRINCIPLES AND MODELS OF CONSUMER SEGMENTATION IN THE BANKING PRODUCTS AND SERVICES MARKET

Directory of Open Access Journals (Sweden)

Andrey V. Tsarev

2015-01-01

Full Text Available The process of segmenting consumers ofbanking products and services connects withconducting marketing research. In the processof customer segmentation it is necessary to identify the factors that affect them. Identifi cation of competitive and consumer factors, in particular, is necessary for marketing decision making andthe development of the segment coverage strategy to reach a segment at all stages of planningmarketing activities and evaluating its effectiveness. After determining the basic segments on macro and micro levels the segment coveragestrategies are developed that should be based onthe results of the segmentation map construction.Banking institutions that implement informationtechnology to facilitate collecting and processingcustomer data, such as CRM-systems, receivemore opportunities to identify the client and provide a competitive position in the market.

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.

Innovations in nuclear concrete constructions

International Nuclear Information System (INIS)

Tatum, C.B.

1983-01-01

The technical requirements and scope of concrete work on nuclear projects present significant engineering and construction challenges. These demands represent the extremes in many areas of construction operations. In meeting these challenges, engineering and construction forces have developed several innovations which can be beneficially applied to other types of construction. Innovative approaches in the general categories of engineering scope, construction input to engineering, work planning, special methods and techniques, and satisfaction of quality assurance requirements are given in this paper. The transfer of this technology to other segments of the construction industry will improve overall performance by avoiding the problem areas encountered on nuclear projects

Development of rock segment for reduction of amount of cement use

International Nuclear Information System (INIS)

Tada, Hiroyuki; Kumasaka, Hiroo; Saito, Akira; Nakaya, Atsushi; Ishii, Takashi; Sanada, Masanori; Noguchi, Akira; Kishi, Hirokazu; Nakama, Shigeo; Fujita, Tomoo

2013-01-01

The authors have been developing methods for constructing tunnels using the minimum quantities of cement-type support materials in high-level radioactive waste disposal facilities and advancing research and development about the technical formation of rock segment using low alkali mortar. In this study, the mechanical characteristic values concerning the rock segment and backfill materials were examined. The stability analysis of drift supported by the rock segment and backfilling with gravel were performed. Technical formation and effectiveness of the support planned for further reduction in cement influence was confirmed from the study result. (author)

A Finite Segment Method for Skewed Box Girder Analysis

Directory of Open Access Journals (Sweden)

Xingwei Xue

2018-01-01

Full Text Available A finite segment method is presented to analyze the mechanical behavior of skewed box girders. By modeling the top and bottom plates of the segments with skew plate beam element under an inclined coordinate system and the webs with normal plate beam element, a spatial elastic displacement model for skewed box girder is constructed, which can satisfy the compatibility condition at the corners of the cross section for box girders. The formulation of the finite segment is developed based on the variational principle. The major advantage of the proposed approach, in comparison with the finite element method, is that it can simplify a three-dimensional structure into a one-dimensional structure for structural analysis, which results in significant saving in computational times. At last, the accuracy and efficiency of the proposed finite segment method are verified by a model test.

Mathematical model of mechanical testing of bone-implant (4.5 mm LCP construct

Directory of Open Access Journals (Sweden)

Lucie Urbanová

2012-01-01

Full Text Available The study deals with the possibility of substituting time- and material-demanding mechanical testing of a bone defect fixation by mathematical modelling. Based on the mechanical model, a mathematical model of bone-implant construct stabilizing experimental segmental femoral bone defect (segmental ostectomy in a miniature pig ex vivo model using 4.5 mm titanium LCP was created. It was subsequently computer-loaded by forces acting parallel to the long axis of the construct. By the effect of the acting forces the displacement vector sum of individual construct points occurred. The greatest displacement was noted in the end segments of the bone in close proximity to ostectomy and in the area of the empty central plate hole (without screw at the level of the segmental bone defect. By studying the equivalent von Mises stress σEQV on LCP as part of the tested construct we found that the greatest changes of stress occur in the place of the empty central plate hole. The distribution of this strain was relatively symmetrical along both sides of the hole. The exceeding of the yield stress value and irreversible plastic deformations in this segment of LCP occurred at the acting of the force of 360 N. These findings are in line with the character of damage of the same construct loaded during its mechanic testing. We succeeded in creating a mathematical model of the bone-implant construct which may be further used for computer modelling of real loading of similar constructs chosen for fixation of bone defects in both experimental and clinical practice.

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...

Multi-phase simultaneous segmentation of tumor in lung 4D-CT data with context information.

Directory of Open Access Journals (Sweden)

Zhengwen Shen

Full Text Available Lung 4D computed tomography (4D-CT plays an important role in high-precision radiotherapy because it characterizes respiratory motion, which is crucial for accurate target definition. However, the manual segmentation of a lung tumor is a heavy workload for doctors because of the large number of lung 4D-CT data slices. Meanwhile, tumor segmentation is still a notoriously challenging problem in computer-aided diagnosis. In this paper, we propose a new method based on an improved graph cut algorithm with context information constraint to find a convenient and robust approach of lung 4D-CT tumor segmentation. We combine all phases of the lung 4D-CT into a global graph, and construct a global energy function accordingly. The sub-graph is first constructed for each phase. A context cost term is enforced to achieve segmentation results in every phase by adding a context constraint between neighboring phases. A global energy function is finally constructed by combining all cost terms. The optimization is achieved by solving a max-flow/min-cut problem, which leads to simultaneous and robust segmentation of the tumor in all the lung 4D-CT phases. The effectiveness of our approach is validated through experiments on 10 different lung 4D-CT cases. The comparison with the graph cut without context constraint, the level set method and the graph cut with star shape prior demonstrates that the proposed method obtains more accurate and robust segmentation results.

Automated method for structural segmentation of nasal airways based on cone beam computed tomography

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Tymkovych, Maksym Yu.; Avrunin, Oleg G.; Paliy, Victor G.; Filzow, Maksim; Gryshkov, Oleksandr; Glasmacher, Birgit; Omiotek, Zbigniew; DzierŻak, RóŻa; Smailova, Saule; Kozbekova, Ainur

2017-08-01

The work is dedicated to the segmentation problem of human nasal airways using Cone Beam Computed Tomography. During research, we propose a specialized approach of structured segmentation of nasal airways. That approach use spatial information, symmetrisation of the structures. The proposed stages can be used for construction a virtual three dimensional model of nasal airways and for production full-scale personalized atlases. During research we build the virtual model of nasal airways, which can be used for construction specialized medical atlases and aerodynamics researches.

Market segmentation and analysis of Japan's residential post and beam construction market.

Science.gov (United States)

Joseph A. Roos; Ivan L. Eastin; Hisaaki Matsuguma

2005-01-01

A mail survey of Japanese post and beam builders was conducted to measure their level of ethnocentrism, market orientation, risk aversion, and price consciousness. The data were analyzed utilizing factor and cluster analysis. The results showed that Japanese post and beam builders can be divided into three distinct market segments: open to import...

Multi scales based sparse matrix spectral clustering image segmentation

Science.gov (United States)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

Segmenting Bone Parts for Bone Age Assessment using Point Distribution Model and Contour Modelling

Science.gov (United States)

Kaur, Amandeep; Singh Mann, Kulwinder, Dr.

2018-01-01

Bone age assessment (BAA) is a task performed on radiographs by the pediatricians in hospitals to predict the final adult height, to diagnose growth disorders by monitoring skeletal development. For building an automatic bone age assessment system the step in routine is to do image pre-processing of the bone X-rays so that features row can be constructed. In this research paper, an enhanced point distribution algorithm using contours has been implemented for segmenting bone parts as per well-established procedure of bone age assessment that would be helpful in building feature row and later on; it would be helpful in construction of automatic bone age assessment system. Implementation of the segmentation algorithm shows high degree of accuracy in terms of recall and precision in segmenting bone parts from left hand X-Rays.

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

Indian Academy of Sciences (India)

The retinal blood vessels were segmented through color space conversion and color channel extraction, image pre-processing, Gabor filtering, image postprocessing, feature construction through application of principal component analysis, k-means clustering and first level classification using Naïve–Bayes classification ...

Image Mosaic Method Based on SIFT Features of Line Segment

Directory of Open Access Journals (Sweden)

Jun Zhu

2014-01-01

Full Text Available This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling.

SEMANTIC SEGMENTATION OF BUILDING ELEMENTS USING POINT CLOUD HASHING

Directory of Open Access Journals (Sweden)

M. Chizhova

2018-05-01

Full Text Available For the interpretation of point clouds, the semantic definition of extracted segments from point clouds or images is a common problem. Usually, the semantic of geometrical pre-segmented point cloud elements are determined using probabilistic networks and scene databases. The proposed semantic segmentation method is based on the psychological human interpretation of geometric objects, especially on fundamental rules of primary comprehension. Starting from these rules the buildings could be quite well and simply classified by a human operator (e.g. architect into different building types and structural elements (dome, nave, transept etc., including particular building parts which are visually detected. The key part of the procedure is a novel method based on hashing where point cloud projections are transformed into binary pixel representations. A segmentation approach released on the example of classical Orthodox churches is suitable for other buildings and objects characterized through a particular typology in its construction (e.g. industrial objects in standardized enviroments with strict component design allowing clear semantic modelling.

Feed-forward segmentation of figure-ground and assignment of border-ownership.

Directory of Open Access Journals (Sweden)

Hans Supèr

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

Feed-forward segmentation of figure-ground and assignment of border-ownership.

Science.gov (United States)

Supèr, Hans; Romeo, August; Keil, Matthias

2010-05-19

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

Segmentation of clustered cells in negative phase contrast images with integrated light intensity and cell shape information.

Science.gov (United States)

Wang, Y; Wang, C; Zhang, Z

2018-05-01

Automated cell segmentation plays a key role in characterisations of cell behaviours for both biology research and clinical practices. Currently, the segmentation of clustered cells still remains as a challenge and is the main reason for false segmentation. In this study, the emphasis was put on the segmentation of clustered cells in negative phase contrast images. A new method was proposed to combine both light intensity and cell shape information through the construction of grey-weighted distance transform (GWDT) within preliminarily segmented areas. With the constructed GWDT, the clustered cells can be detected and then separated with a modified region skeleton-based method. Moreover, a contour expansion operation was applied to get optimised detection of cell boundaries. In this paper, the working principle and detailed procedure of the proposed method are described, followed by the evaluation of the method on clustered cell segmentation. Results show that the proposed method achieves an improved performance in clustered cell segmentation compared with other methods, with 85.8% and 97.16% accuracy rate for clustered cells and all cells, respectively. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Status of the segment interconnect, cable segment ancillary logic, and the cable segment hybrid driver projects

International Nuclear Information System (INIS)

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

1985-01-01

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

Soft segmented inchworm robot with dielectric elastomer muscles

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Conn, Andrew T.; Hinitt, Andrew D.; Wang, Pengchuan

2014-03-01

Robotic devices typically utilize rigid components in order to produce precise and robust operation. Rigidity becomes a significant impediment, however, when navigating confined or constricted environments e.g. search-and-rescue, industrial pipe inspection. In such cases adaptively conformable soft structures become optimal. Dielectric elastomers (DEs) are well suited for developing such soft robots since they are inherently compliant and can produce large musclelike actuation strains. In this paper, a soft segmented inchworm robot is presented that utilizes pneumatically-coupled DE membranes to produce inchworm-like locomotion. The robot is constructed from repeated body segments, each with a simple control architecture, so that the total length can be readily adapted by adding or removing segments. Each segment consists of a soft inflatable shell (internal pressure in range of 1.0-15.9 mBar) and a pair of antagonistic DE membranes (VHB 4905). Experimental testing of a single body segment is presented and the relationship between drive voltage, pneumatic pressure and active displacement is characterized. This demonstrates that pneumatic coupling of DE membranes induces complex non-linear electro-mechanical behaviour as drive voltage and pneumatic pressure are altered. Locomotion of a two-segment inchworm robot prototype with a passive length of 80 mm is presented. Artificial setae are included on the body shell to generate anisotropic friction for locomotion. A maximum locomotion speed of 4.1 mm/s was recorded at a drive frequency of 1.5 Hz, which compares favourably to biological counterparts. Future development of the soft inchworm robot are discussed including reflexive low-level control of individual segments.

A method for robust segmentation of arbitrarily shaped radiopaque structures in cone-beam CT projections

International Nuclear Information System (INIS)

Poulsen, Per Rugaard; Fledelius, Walther; Keall, Paul J.; Weiss, Elisabeth; Lu Jun; Brackbill, Emily; Hugo, Geoffrey D.

2011-01-01

Purpose: Implanted markers are commonly used in radiotherapy for x-ray based target localization. The projected marker position in a series of cone-beam CT (CBCT) projections can be used to estimate the three dimensional (3D) target trajectory during the CBCT acquisition. This has important applications in tumor motion management such as motion inclusive, gating, and tumor tracking strategies. However, for irregularly shaped markers, reliable segmentation is challenged by large variations in the marker shape with projection angle. The purpose of this study was to develop a semiautomated method for robust and reliable segmentation of arbitrarily shaped radiopaque markers in CBCT projections. Methods: The segmentation method involved the following three steps: (1) Threshold based segmentation of the marker in three to six selected projections with large angular separation, good marker contrast, and uniform background; (2) construction of a 3D marker model by coalignment and backprojection of the threshold-based segmentations; and (3) construction of marker templates at all imaging angles by projection of the 3D model and use of these templates for template-based segmentation. The versatility of the segmentation method was demonstrated by segmentation of the following structures in the projections from two clinical CBCT scans: (1) Three linear fiducial markers (Visicoil) implanted in or near a lung tumor and (2) an artificial cardiac valve in a lung cancer patient. Results: Automatic marker segmentation was obtained in more than 99.9% of the cases. The segmentation failed in a few cases where the marker was either close to a structure of similar appearance or hidden behind a dense structure (data cable). Conclusions: A robust template-based method for segmentation of arbitrarily shaped radiopaque markers in CBCT projections was developed.

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

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

Energy Technology Data Exchange (ETDEWEB)

Maduskar, Pragnya, E-mail: pragnya.maduskar@radboudumc.nl; Hogeweg, Laurens; Sánchez, Clara I.; Ginneken, Bram van [Diagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, 6525 GA (Netherlands); Jong, Pim A. de [Department of Radiology, University Medical Center Utrecht, 3584 CX (Netherlands); Peters-Bax, Liesbeth [Department of Radiology, Radboud University Medical Center, Nijmegen, 6525 GA (Netherlands); Dawson, Rodney [University of Cape Town Lung Institute, Cape Town 7700 (South Africa); Ayles, Helen [Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT (United Kingdom)

2014-07-15

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

Model-Based Learning of Local Image Features for Unsupervised Texture Segmentation

Science.gov (United States)

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

2018-04-01

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

Contextually guided very-high-resolution imagery classification with semantic segments

Science.gov (United States)

Zhao, Wenzhi; Du, Shihong; Wang, Qiao; Emery, William J.

2017-10-01

Contextual information, revealing relationships and dependencies between image objects, is one of the most important information for the successful interpretation of very-high-resolution (VHR) remote sensing imagery. Over the last decade, geographic object-based image analysis (GEOBIA) technique has been widely used to first divide images into homogeneous parts, and then to assign semantic labels according to the properties of image segments. However, due to the complexity and heterogeneity of VHR images, segments without semantic labels (i.e., semantic-free segments) generated with low-level features often fail to represent geographic entities (such as building roofs usually be partitioned into chimney/antenna/shadow parts). As a result, it is hard to capture contextual information across geographic entities when using semantic-free segments. In contrast to low-level features, "deep" features can be used to build robust segments with accurate labels (i.e., semantic segments) in order to represent geographic entities at higher levels. Based on these semantic segments, semantic graphs can be constructed to capture contextual information in VHR images. In this paper, semantic segments were first explored with convolutional neural networks (CNN) and a conditional random field (CRF) model was then applied to model the contextual information between semantic segments. Experimental results on two challenging VHR datasets (i.e., the Vaihingen and Beijing scenes) indicate that the proposed method is an improvement over existing image classification techniques in classification performance (overall accuracy ranges from 82% to 96%).

Interactive-cut: Real-time feedback segmentation for translational research.

Science.gov (United States)

Egger, Jan; Lüddemann, Tobias; Schwarzenberg, Robert; Freisleben, Bernd; Nimsky, Christopher

2014-06-01

In this contribution, a scale-invariant image segmentation algorithm is introduced that "wraps" the algorithm's parameters for the user by its interactive behavior, avoiding the definition of "arbitrary" numbers that the user cannot really understand. Therefore, we designed a specific graph-based segmentation method that only requires a single seed-point inside the target-structure from the user and is thus particularly suitable for immediate processing and interactive, real-time adjustments by the user. In addition, color or gray value information that is needed for the approach can be automatically extracted around the user-defined seed point. Furthermore, the graph is constructed in such a way, so that a polynomial-time mincut computation can provide the segmentation result within a second on an up-to-date computer. The algorithm presented here has been evaluated with fixed seed points on 2D and 3D medical image data, such as brain tumors, cerebral aneurysms and vertebral bodies. Direct comparison of the obtained automatic segmentation results with costlier, manual slice-by-slice segmentations performed by trained physicians, suggest a strong medical relevance of this interactive approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

Segmented block copolymers with monodisperse aramide end-segments

NARCIS (Netherlands)

Araichimani, A.; Gaymans, R.J.

2008-01-01

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

Geomagnetism-Aided Indoor Wi-Fi Radio-Map Construction via Smartphone Crowdsourcing.

Science.gov (United States)

Li, Wen; Wei, Dongyan; Lai, Qifeng; Li, Xianghong; Yuan, Hong

2018-05-08

Wi-Fi radio-map construction is an important phase in indoor fingerprint localization systems. Traditional methods for Wi-Fi radio-map construction have the problems of being time-consuming and labor-intensive. In this paper, an indoor Wi-Fi radio-map construction method is proposed which utilizes crowdsourcing data contributed by smartphone users. We draw indoor pathway map and construct Wi-Fi radio-map without requiring manual site survey, exact floor layout and extra infrastructure support. The key novelty is that it recognizes road segments from crowdsourcing traces by a cluster based on magnetism sequence similarity and constructs an indoor pathway map with Wi-Fi signal strengths annotated on. Through experiments in real world indoor areas, the method is proved to have good performance on magnetism similarity calculation, road segment clustering and pathway map construction. The Wi-Fi radio maps constructed by crowdsourcing data are validated to provide competitive indoor localization accuracy.

Geomagnetism-Aided Indoor Wi-Fi Radio-Map Construction via Smartphone Crowdsourcing

Directory of Open Access Journals (Sweden)

Wen Li

2018-05-01

Full Text Available Wi-Fi radio-map construction is an important phase in indoor fingerprint localization systems. Traditional methods for Wi-Fi radio-map construction have the problems of being time-consuming and labor-intensive. In this paper, an indoor Wi-Fi radio-map construction method is proposed which utilizes crowdsourcing data contributed by smartphone users. We draw indoor pathway map and construct Wi-Fi radio-map without requiring manual site survey, exact floor layout and extra infrastructure support. The key novelty is that it recognizes road segments from crowdsourcing traces by a cluster based on magnetism sequence similarity and constructs an indoor pathway map with Wi-Fi signal strengths annotated on. Through experiments in real world indoor areas, the method is proved to have good performance on magnetism similarity calculation, road segment clustering and pathway map construction. The Wi-Fi radio maps constructed by crowdsourcing data are validated to provide competitive indoor localization accuracy.

Segmentation of consumer's markets and evaluation of market's segments

OpenAIRE

ŠVECOVÁ, Iveta

2013-01-01

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

Study on Load-displacement Test of Rubber Pads of Coal Mine Roadway Constructed by Shield

Science.gov (United States)

Yang, Yue; Chen, Xiaoguo; Yang, Liyun

2017-12-01

Shield method construction of coal mine roadway is the future trend of the development of deep coal mining. The main shaft supporting is the segment. There is rubber pads between segment and segment. The performance of compression deformation of rubber pad is essential for the overall stability of lining. Through load test, displacement of the rubber pad under load, the thrust force law of the rubber pad deformation, and provide a theoretical basis for the stability analysis of coal mine tunnel shield construction.

Concept project of joining segment, connecting two folding bridge structures MS-54 and widened DMS-65

Directory of Open Access Journals (Sweden)

Jan Marszałek

2015-09-01

Full Text Available The article includes the concept project of truss segment enabling the constructions of MS-54 and DMS-65 bridges to joint. At the beginning, the basic technical and exploitative characteristics of joined constructions are introduced. On the basis of this data, geometrical analysis of the component is carried out. As a result, the concept project of fitting, enabling the crossing from two types of foldable constructions to be built, is developed. Sequentially, the computer calculations of the bridge including the part of the designed fitting are carried out.The article contains the fragments of M.A. dissertation awarded by the rector of Military University of Technology as the best from the Faculty of Civil Engineering in 2014. The article is summarized with the conclusions.[b]Keywords[/b]: construction, folding bridges, truss segment

Responsiveness of culture-based segmentation of organizational buyers

Directory of Open Access Journals (Sweden)

Veronika Jadczaková

2013-01-01

Full Text Available Much published work over the four decades has acknowledged market segmentation in business-to-business settings yet primarily focusing on observable segmentation bases such as firmographics or geographics. However, such bases were proved to have a weak predictive validity with respect to industrial buying behavior. Therefore, this paper attempts to add a debate to this topic by introducing new (unobservable segmentation base incorporating several facets of business culture, denoted as psychographics. The justification for this approach is that the business culture captures the collective mindset of an organization and thus enables marketers to target the organization as a whole. Given the hypothesis that culture has a merit for micro-segmentation a sample of 278 manufacturing firms was first subjected to principal component analysis and Varimax to reveal underlying cultural traits. In next step, cluster analysis was performed on retained factors to construct business profiles. Finally, non-parametric one-way analysis of variance confirmed discriminative power between profiles based on psychographics in terms of industrial buying behavior. Owing to this, business culture may assist marketers when targeting more effectively than some traditional approaches.

PTBS segmentation scheme for synthetic aperture radar

Science.gov (United States)

Friedland, Noah S.; Rothwell, Brian J.

1995-07-01

The Image Understanding Group at Martin Marietta Technologies in Denver, Colorado has developed a model-based synthetic aperture radar (SAR) automatic target recognition (ATR) system using an integrated resource architecture (IRA). IRA, an adaptive Markov random field (MRF) environment, utilizes information from image, model, and neighborhood resources to create a discrete, 2D feature-based world description (FBWD). The IRA FBWD features are peak, target, background and shadow (PTBS). These features have been shown to be very useful for target discrimination. The FBWD is used to accrue evidence over a model hypothesis set. This paper presents the PTBS segmentation process utilizing two IRA resources. The image resource (IR) provides generic (the physics of image formation) and specific (the given image input) information. The neighborhood resource (NR) provides domain knowledge of localized FBWD site behaviors. A simulated annealing optimization algorithm is used to construct a `most likely' PTBS state. Results on simulated imagery illustrate the power of this technique to correctly segment PTBS features, even when vehicle signatures are immersed in heavy background clutter. These segmentations also suppress sidelobe effects and delineate shadows.

Multi-atlas segmentation for abdominal organs with Gaussian mixture models

Science.gov (United States)

Burke, Ryan P.; Xu, Zhoubing; Lee, Christopher P.; Baucom, Rebeccah B.; Poulose, Benjamin K.; Abramson, Richard G.; Landman, Bennett A.

2015-03-01

Abdominal organ segmentation with clinically acquired computed tomography (CT) is drawing increasing interest in the medical imaging community. Gaussian mixture models (GMM) have been extensively used through medical segmentation, most notably in the brain for cerebrospinal fluid / gray matter / white matter differentiation. Because abdominal CT exhibit strong localized intensity characteristics, GMM have recently been incorporated in multi-stage abdominal segmentation algorithms. In the context of variable abdominal anatomy and rich algorithms, it is difficult to assess the marginal contribution of GMM. Herein, we characterize the efficacy of an a posteriori framework that integrates GMM of organ-wise intensity likelihood with spatial priors from multiple target-specific registered labels. In our study, we first manually labeled 100 CT images. Then, we assigned 40 images to use as training data for constructing target-specific spatial priors and intensity likelihoods. The remaining 60 images were evaluated as test targets for segmenting 12 abdominal organs. The overlap between the true and the automatic segmentations was measured by Dice similarity coefficient (DSC). A median improvement of 145% was achieved by integrating the GMM intensity likelihood against the specific spatial prior. The proposed framework opens the opportunities for abdominal organ segmentation by efficiently using both the spatial and appearance information from the atlases, and creates a benchmark for large-scale automatic abdominal segmentation.

Automating the segmentation of medical images for the production of voxel tomographic computational models

International Nuclear Information System (INIS)

Caon, M.

2001-01-01

Radiation dosimetry for the diagnostic medical imaging procedures performed on humans requires anatomically accurate, computational models. These may be constructed from medical images as voxel-based tomographic models. However, they are time consuming to produce and as a consequence, there are few available. This paper discusses the emergence of semi-automatic segmentation techniques and describes an application (iRAD) written in Microsoft Visual Basic that allows the bitmap of a medical image to be segmented interactively and semi-automatically while displayed in Microsoft Excel. iRAD will decrease the time required to construct voxel models. Copyright (2001) Australasian College of Physical Scientists and Engineers in Medicine

Assessing urban and rural neighborhood characteristics using audit and GIS data: derivation and reliability of constructs

Directory of Open Access Journals (Sweden)

Laraia Barbara A

2009-07-01

Full Text Available Abstract Background Measures to assess neighborhood environments are needed to better understand the salient features that may enhance outdoor physical activities, such as walking and bicycling for transport or leisure. The purpose of this study was to derive constructs to describe neighborhoods using both primary (neighborhood audit and secondary (geographic information systems data. Methods We collected detailed information on 10,770 road segments using an audit and secondary data. The road segment sample was randomly split into an exploratory (60% and validation sample (40% for cross-validation. Using the exploratory sample (n = 6,388, seven a priori constructs were assessed separately (functionality, safety, aesthetics, destinations, incivilities, territorality, social spaces by urbanicity using multi-group confirmatory factor analysis (CFA. Additionally, new a posteriori constructs were derived using exploratory factor analysis (EFA. For cross-validation (n = 4,382, we tested factor loadings, thresholds, correlated errors, and correlations among a posteriori constructs between the two subsamples. Two-week test-retest reliability of the final constructs using a subsample of road segments (n = 464 was examined using Spearman correlation coefficients. Results CFA indicated the a priori constructs did not hold in this geographic area, with the exception of physical incivilities. Therefore, we used EFA to derive a four-factor solution on the exploratory sample: arterial or thoroughfare, walkable neighborhood, physical incivilities, and decoration. Using CFA on the validation sample, the internal validity for these a posteriori constructs was high (range 0.43 to 0.73 and the fit was acceptable. Spearman correlations indicated the arterial or thoroughfare factor displayed near perfect reliability in both urban and rural segments (r = 0.96. Both the physical incivilities factor and the walkable neighborhood factor had substantial to near perfect

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

Abdominal multi-organ segmentation from CT images using conditional shape-location and unsupervised intensity priors.

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Okada, Toshiyuki; Linguraru, Marius George; Hori, Masatoshi; Summers, Ronald M; Tomiyama, Noriyuki; Sato, Yoshinobu

2015-12-01

This paper addresses the automated segmentation of multiple organs in upper abdominal computed tomography (CT) data. The aim of our study is to develop methods to effectively construct the conditional priors and use their prediction power for more accurate segmentation as well as easy adaptation to various imaging conditions in CT images, as observed in clinical practice. We propose a general framework of multi-organ segmentation which effectively incorporates interrelations among multiple organs and easily adapts to various imaging conditions without the need for supervised intensity information. The features of the framework are as follows: (1) A method for modeling conditional shape and location (shape-location) priors, which we call prediction-based priors, is developed to derive accurate priors specific to each subject, which enables the estimation of intensity priors without the need for supervised intensity information. (2) Organ correlation graph is introduced, which defines how the conditional priors are constructed and segmentation processes of multiple organs are executed. In our framework, predictor organs, whose segmentation is sufficiently accurate by using conventional single-organ segmentation methods, are pre-segmented, and the remaining organs are hierarchically segmented using conditional shape-location priors. The proposed framework was evaluated through the segmentation of eight abdominal organs (liver, spleen, left and right kidneys, pancreas, gallbladder, aorta, and inferior vena cava) from 134 CT data from 86 patients obtained under six imaging conditions at two hospitals. The experimental results show the effectiveness of the proposed prediction-based priors and the applicability to various imaging conditions without the need for supervised intensity information. Average Dice coefficients for the liver, spleen, and kidneys were more than 92%, and were around 73% and 67% for the pancreas and gallbladder, respectively. Copyright © 2015

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.

Automated segmentation of pulmonary structures in thoracic computed tomography scans: a review

International Nuclear Information System (INIS)

Van Rikxoort, Eva M; Van Ginneken, Bram

2013-01-01

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

Five low energy phosphorene allotropes constructed through gene segments recombination.

Science.gov (United States)

He, Chaoyu; Zhang, ChunXiao; Tang, Chao; Ouyang, Tao; Li, Jin; Zhong, Jianxin

2017-04-27

Based on the crystal structures of the previously proposed low energy η-P and θ-P, five new phosphorene allotropes were predicted through gene segments recombination method. These five new phosphorene allotropes are confirmed dynamically stable and energetically more favorable than their parents (η-P and θ-P). Especially, the XX-XX type G1-P is confirmed energetically more favorable than most of all the previously proposed phosphorene allotropes, including black phosphorene and blue phosphorene, which is highly expected to be synthesized in future experiment through vapor deposition or epitaxial growth method like blue β-P. The calculated results also show that such a new promising phosphorene allotrope G1-P is a potential candidate for application in nano-electronics according to its middle band gap of about 1.491 eV from DFT-HSE06 calculation.

Constructing a Sophistication Index as a Method of Market ...

African Journals Online (AJOL)

This study investigates the process of index construction as a means of measuring a hypothetical construct that can typically not be measured by a single question or item and applying it as a method of market segmentation. The availability of incidental secondary data provided a relevant quantitative basis to illustrate this ...

LDR segmented mirror technology assessment study

Science.gov (United States)

Krim, M.; Russo, J.

1983-01-01

In the mid-1990s, NASA plans to orbit a giant telescope, whose aperture may be as great as 30 meters, for infrared and sub-millimeter astronomy. Its primary mirror will be deployed or assembled in orbit from a mosaic of possibly hundreds of mirror segments. Each segment must be shaped to precise curvature tolerances so that diffraction-limited performance will be achieved at 30 micron (nominal operating wavelength). All panels must lie within 1 micron on a theoretical surface described by the optical precipitation of the telescope's primary mirror. To attain diffraction-limited performance, the issues of alignment and/or position sensing, position control of micron tolerances, and structural, thermal, and mechanical considerations for stowing, deploying, and erecting the reflector must be resolved. Radius of curvature precision influences panel size, shape, material, and type of construction. Two superior material choices emerged: fused quartz (sufficiently homogeneous with respect to thermal expansivity to permit a thin shell substrate to be drape molded between graphite dies to a precise enough off-axis asphere for optical finishing on the as-received a segment) and a Pyrex or Duran (less expensive than quartz and formable at lower temperatures). The optimal reflector panel size is between 1-1/2 and 2 meters. Making one, two-meter mirror every two weeks requires new approaches to manufacturing off-axis parabolic or aspheric segments (drape molding on precision dies and subsequent finishing on a nonrotationally symmetric dependent machine). Proof-of-concept developmental programs were identified to prove the feasibility of the materials and manufacturing ideas.

Beyond Retinal Layers: A Deep Voting Model for Automated Geographic Atrophy Segmentation in SD-OCT Images.

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Ji, Zexuan; Chen, Qiang; Niu, Sijie; Leng, Theodore; Rubin, Daniel L

2018-01-01

To automatically and accurately segment geographic atrophy (GA) in spectral-domain optical coherence tomography (SD-OCT) images by constructing a voting system with deep neural networks without the use of retinal layer segmentation. An automatic GA segmentation method for SD-OCT images based on the deep network was constructed. The structure of the deep network was composed of five layers, including one input layer, three hidden layers, and one output layer. During the training phase, the labeled A-scans with 1024 features were directly fed into the network as the input layer to obtain the deep representations. Then a soft-max classifier was trained to determine the label of each individual pixel. Finally, a voting decision strategy was used to refine the segmentation results among 10 trained models. Two image data sets with GA were used to evaluate the model. For the first dataset, our algorithm obtained a mean overlap ratio (OR) 86.94% ± 8.75%, absolute area difference (AAD) 11.49% ± 11.50%, and correlation coefficients (CC) 0.9857; for the second dataset, the mean OR, AAD, and CC of the proposed method were 81.66% ± 10.93%, 8.30% ± 9.09%, and 0.9952, respectively. The proposed algorithm was capable of improving over 5% and 10% segmentation accuracy, respectively, when compared with several state-of-the-art algorithms on two data sets. Without retinal layer segmentation, the proposed algorithm could produce higher segmentation accuracy and was more stable when compared with state-of-the-art methods that relied on retinal layer segmentation results. Our model may provide reliable GA segmentations from SD-OCT images and be useful in the clinical diagnosis of advanced nonexudative AMD. Based on the deep neural networks, this study presents an accurate GA segmentation method for SD-OCT images without using any retinal layer segmentation results, and may contribute to improved understanding of advanced nonexudative AMD.

A proposed framework for consensus-based lung tumour volume auto-segmentation in 4D computed tomography imaging

International Nuclear Information System (INIS)

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

2015-01-01

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

A proposed framework for consensus-based lung tumour volume auto-segmentation in 4D computed tomography imaging

Science.gov (United States)

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

2015-02-01

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

An Automatic Cognitive Graph-Based Segmentation for Detection of Blood Vessels in Retinal Images

Directory of Open Access Journals (Sweden)

Rasha Al Shehhi

2016-01-01

Full Text Available This paper presents a hierarchical graph-based segmentation for blood vessel detection in digital retinal images. This segmentation employs some of perceptual Gestalt principles: similarity, closure, continuity, and proximity to merge segments into coherent connected vessel-like patterns. The integration of Gestalt principles is based on object-based features (e.g., color and black top-hat (BTH morphology and context and graph-analysis algorithms (e.g., Dijkstra path. The segmentation framework consists of two main steps: preprocessing and multiscale graph-based segmentation. Preprocessing is to enhance lighting condition, due to low illumination contrast, and to construct necessary features to enhance vessel structure due to sensitivity of vessel patterns to multiscale/multiorientation structure. Graph-based segmentation is to decrease computational processing required for region of interest into most semantic objects. The segmentation was evaluated on three publicly available datasets. Experimental results show that preprocessing stage achieves better results compared to state-of-the-art enhancement methods. The performance of the proposed graph-based segmentation is found to be consistent and comparable to other existing methods, with improved capability of detecting small/thin vessels.

Brookhaven segment interconnect

International Nuclear Information System (INIS)

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

1983-01-01

We have performed a high energy physics experiment using a multisegment Brookhaven FASTBUS system. The system was composed of three crate segments and two cable segments. We discuss the segment interconnect module which permits communication between the various segments

E-Learning System Using Segmentation-Based MR Technique for Learning Circuit Construction

Science.gov (United States)

Takemura, Atsushi

2016-01-01

This paper proposes a novel e-Learning system using the mixed reality (MR) technique for technical experiments involving the construction of electronic circuits. The proposed system comprises experimenters' mobile computers and a remote analysis system. When constructing circuits, each learner uses a mobile computer to transmit image data from the…

Asphalt Pavement Pothole Detection and Segmentation Based on Wavelet Energy Field

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Penghui Wang

2017-01-01

Full Text Available Potholes are one type of pavement surface distresses whose assessment is essential for developing road network maintenance strategies. Existing methods for automatic pothole detection either rely on expensive and high-maintenance equipment or could not segment the pothole accurately. In this paper, an asphalt pavement pothole detection and segmentation method based on energy field is put forward. The proposed method mainly includes two processes. Firstly, the wavelet energy field of the pavement image is constructed to detect the pothole by morphological processing and geometric criterions. Secondly, the detected pothole is segmented by Markov random field model and the pothole edge is extracted accurately. This methodology has been implemented in a MATLAB prototype, trained, and tested on 120 pavement images. The results show that it can effectively distinguish potholes from cracks, patches, greasy dirt, shadows, and manhole covers and accurately segment the pothole. For pothole detection, the method reaches an overall accuracy of 86.7%, with 83.3% precision and 87.5% recall. For pothole segmentation, the overlap degree between the extracted pothole region and the original pothole region is mostly more than 85%, which accounts for 88.6% of the total detected pavement pothole images.

Geophysical investigations over a segment of the Central Indian Ridge, Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

KameshRaju, K.A.; Ramprasad, T.; Subrahmanyam, C.

Swath bathymetric, gravity, and magnetic studies were carried out over a 55 km long segment of the Central Indian Ridge. The ridge is characterized by 12 to 15 km wide rift valley bounded by steep walls and prominent volcanic constructional ridges...

Active Segmentation.

Science.gov (United States)

Mishra, Ajay; Aloimonos, Yiannis

2009-01-01

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

Evaluation of serosal patch supplementation of surgical anastomoses in intestinal segments from canine cadavers.

Science.gov (United States)

Hansen, Lane A; Monnet, Eric L

2013-08-01

To compare leakage and maximum intraluminal pressures of intestinal anastomoses with and without serosal patch supplementation in dogs. Healthy small intestine segments from cadavers of 2 dogs euthanized for reasons unrelated to the study. 12 enterectomy constructs were created by anastomosis of intestinal segments with a standard simple continuous suture pattern. Half of the constructs were randomly selected for additional serosal patch support. Leakage and maximum intraluminal pressures were measured in and compared between patch-supplemented and nonsupplemented constructs. Mean ± SD leakage pressure was significantly greater for the patch-supplemented anastomoses (81.8 ± 6.7 mm Hg) than for the nonsupplemented anastomoses (28.0 ± 6.7 mm Hg). Maximum intraluminal pressures were not significantly different between the groups. Serosal patch-supplemented anastomoses were able to sustain a significantly higher pressure before leakage than were nonsupplemented anastomoses in intestinal specimens from canine cadavers. The serosal patch supplementation may protect against leakage immediately after enterectomy in dogs.

Modeling vehicle interior noise exposure dose on freeways: Considering weaving segment designs and engine operation.

Science.gov (United States)

Li, Qing; Qiao, Fengxiang; Yu, Lei; Shi, Junqing

2017-07-05

Vehicle interior noise functions at the dominant frequencies of 500 Hz below and around 800 Hz, which fall into the bands that may impair hearing. Recent studies demonstrated that freeway commuters are chronically exposed to vehicle interior noise, bearing the risk of hearing impairment. The interior noise evaluation process is mostly conducted in a laboratory environment. The test results and the developed noise models may underestimate or ignore the noise effects from dynamic traffic and road conditions and configuration. However, the interior noise is highly associated with vehicle maneuvering. The vehicle maneuvering on a freeway weaving segment is more complex because of its nature of conflicting areas. This research is intended to explore the risk of the interior noise exposure on freeway weaving segments for freeway commuters and to improve the interior noise estimation by constructing a decision tree learning-based noise exposure dose (NED) model, considering weaving segment designs and engine operation. On-road driving tests were conducted on 12 subjects on State Highway 288 in Houston, Texas. On-board Diagnosis (OBD) II, a smartphone-based roughness app, and a digital sound meter were used to collect vehicle maneuvering and engine information, International Roughness Index, and interior noise levels, respectively. Eleven variables were obtainable from the driving tests, including the length and type of a weaving segment, serving as predictors. The importance of the predictors was estimated by their out-of-bag-permuted predictor delta errors. The hazardous exposure level of the interior noise on weaving segments was quantified to hazard quotient, NED, and daily noise exposure level, respectively. Results showed that the risk of hearing impairment on freeway is acceptable; the interior noise level is the most sensitive to the pavement roughness and is subject to freeway configuration and traffic conditions. The constructed NED model shows high predictive

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.

Assignment of simian rotavirus SA11 temperature-sensitive mutant groups B and E to genome segments

International Nuclear Information System (INIS)

Gombold, J.L.; Estes, M.K.; Ramig, R.F.

1985-01-01

Recombinant (reassortant) viruses were selected from crosses between temperature-sensitive (ts) mutants of simian rotavirus SA11 and wild-type human rotavirus Wa. The double-stranded genome RNAs of the reassortants were examined by electrophoresis in Tris-glycine-buffered polyacrylamide gels and by dot hybridization with a cloned DNA probe for genome segment 2. Analysis of replacements of genome segments in the reassortants allowed construction of a map correlating genome segments providing functions interchangeable between SA11 and Wa. The reassortants revealed a functional correspondence in order of increasing electrophoretic mobility of genome segments. Analysis of the parental origin of genome segments in ts+ SA11/Wa reassortants derived from the crosses SA11 tsB(339) X Wa and SA11 tsE(1400) X Wa revealed that the group B lesion of tsB(339) was located on genome segment 3 and the group E lesion of tsE(1400) was on segment 8

Assignment of simian rotavirus SA11 temperature-sensitive mutant groups B and E to genome segments

Energy Technology Data Exchange (ETDEWEB)

Gombold, J.L.; Estes, M.K.; Ramig, R.F.

1985-05-01

Recombinant (reassortant) viruses were selected from crosses between temperature-sensitive (ts) mutants of simian rotavirus SA11 and wild-type human rotavirus Wa. The double-stranded genome RNAs of the reassortants were examined by electrophoresis in Tris-glycine-buffered polyacrylamide gels and by dot hybridization with a cloned DNA probe for genome segment 2. Analysis of replacements of genome segments in the reassortants allowed construction of a map correlating genome segments providing functions interchangeable between SA11 and Wa. The reassortants revealed a functional correspondence in order of increasing electrophoretic mobility of genome segments. Analysis of the parental origin of genome segments in ts+ SA11/Wa reassortants derived from the crosses SA11 tsB(339) X Wa and SA11 tsE(1400) X Wa revealed that the group B lesion of tsB(339) was located on genome segment 3 and the group E lesion of tsE(1400) was on segment 8.

Managing Media: Segmenting Media Through Consumer Expectancies

Directory of Open Access Journals (Sweden)

Matt Eastin

2014-04-01

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

Single-segment and double-segment INTACS for post-LASIK ectasia.

Directory of Open Access Journals (Sweden)

Hassan Hashemi

2014-09-01

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

Registration-based segmentation with articulated model from multipostural magnetic resonance images for hand bone motion animation.

Science.gov (United States)

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

2010-06-01

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

Fabrication of a segmented composite stainless steel-alumina discharge tube for a theta-pinch coil

International Nuclear Information System (INIS)

Dickinson, J.M.; Stoddard, S.D.; Muller, J.F.

1975-11-01

An 80-mm-diam segmented discharge tube that simulated in a simplified way the blanket and first wall of the Reference Theta-Pinch Reactor (RTPR) has been constructed. The segments were fabricated by plasma-arc spraying an alumina coating on tubular stainless steel trapezoids. These were laid up to form a cylinder that was contained in a fully dense alumina vacuum tube. The fabrication processes are discussed in detail

Thermal and water regime of green roof segments filled with Technosol

Science.gov (United States)

Jelínková, Vladimíra; Šácha, Jan; Dohnal, Michal; Skala, Vojtěch

2016-04-01

Artificial soil systems and structures comprise appreciable part of the urban areas and are considered to be perspective for number of reasons. One of the most important lies in contribution of green roofs and facades to the heat island effect mitigation, air quality improvement, storm water reduction, etc. The aim of the presented study is to evaluate thermal and water regime of the anthropogenic soil systems during the first months of the construction life cycle. Green roof test segments filled with two different anthropogenic soils were built to investigate the benefits of such systems in the temperate climate. Temperature and water balance measurements complemented with meteorological observations and knowledge of physical properties of the soil substrates provided basis for detailed analysis of thermal and hydrological regime. Water balance of green roof segments was calculated for available vegetation seasons and individual rainfall events. On the basis of an analysis of individual rainfall events rainfall-runoff dependency was found for green roof segments. The difference between measured actual evapotranspiration and calculated potential evapotranspiration was discussed on period with contrasting conditions in terms of the moisture stress. Thermal characteristics of soil substrates resulted in highly contrasting diurnal variation of soils temperatures. Green roof systems under study were able to reduce heat load of the roof construction when comparing with a concrete roof construction. Similarly, received rainfall was significantly reduced. The extent of the rainfall reduction mainly depends on soil, vegetation status and experienced weather patterns. The research was realized as a part of the University Centre for Energy Efficient Buildings supported by the EU and with financial support from the Czech Science Foundation under project number 14-10455P.

Medical Image Segmentation by Combining Graph Cut and Oriented Active Appearance Models

Science.gov (United States)

Chen, Xinjian; Udupa, Jayaram K.; Bağcı, Ulaş; Zhuge, Ying; Yao, Jianhua

2017-01-01

In this paper, we propose a novel 3D segmentation method based on the effective combination of the active appearance model (AAM), live wire (LW), and graph cut (GC). The proposed method consists of three main parts: model building, initialization, and segmentation. In the model building part, we construct the AAM and train the LW cost function and GC parameters. In the initialization part, a novel algorithm is proposed for improving the conventional AAM matching method, which effectively combines the AAM and LW method, resulting in Oriented AAM (OAAM). A multi-object strategy is utilized to help in object initialization. We employ a pseudo-3D initialization strategy, and segment the organs slice by slice via multi-object OAAM method. For the segmentation part, a 3D shape constrained GC method is proposed. The object shape generated from the initialization step is integrated into the GC cost computation, and an iterative GC-OAAM method is used for object delineation. The proposed method was tested in segmenting the liver, kidneys, and spleen on a clinical CT dataset and also tested on the MICCAI 2007 grand challenge for liver segmentation training dataset. The results show the following: (a) An overall segmentation accuracy of true positive volume fraction (TPVF) > 94.3%, false positive volume fraction (FPVF) wordpress.com/research/. PMID:22311862

Classification with an edge: Improving semantic image segmentation with boundary detection

Science.gov (United States)

Marmanis, D.; Schindler, K.; Wegner, J. D.; Galliani, S.; Datcu, M.; Stilla, U.

2018-01-01

We present an end-to-end trainable deep convolutional neural network (DCNN) for semantic segmentation with built-in awareness of semantically meaningful boundaries. Semantic segmentation is a fundamental remote sensing task, and most state-of-the-art methods rely on DCNNs as their workhorse. A major reason for their success is that deep networks learn to accumulate contextual information over very large receptive fields. However, this success comes at a cost, since the associated loss of effective spatial resolution washes out high-frequency details and leads to blurry object boundaries. Here, we propose to counter this effect by combining semantic segmentation with semantically informed edge detection, thus making class boundaries explicit in the model. First, we construct a comparatively simple, memory-efficient model by adding boundary detection to the SEGNET encoder-decoder architecture. Second, we also include boundary detection in FCN-type models and set up a high-end classifier ensemble. We show that boundary detection significantly improves semantic segmentation with CNNs in an end-to-end training scheme. Our best model achieves >90% overall accuracy on the ISPRS Vaihingen benchmark.

A Vision Chip for Color Segmentation and Pattern Matching

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Ralph Etienne-Cummings

2003-06-01

Full Text Available A 128(H × 64(V × RGB CMOS imager is integrated with region-of-interest selection, RGB-to-HSI transformation, HSI-based pixel segmentation, (36bins × 12bits-HSI histogramming, and sum-of-absolute-difference (SAD template matching. Thirty-two learned color templates are stored and compared to each image. The chip captures the R, G, and B images using in-pixel storage before passing the pixel content to a multiplying digital-to-analog converter (DAC for white balancing. The DAC can also be used to pipe in images for a PC. The color processing uses a biologically inspired color opponent representation and an analog lookup table to determine the Hue (H of each pixel. Saturation (S is computed using a loser-take-all circuit. Intensity (I is given by the sum of the color components. A histogram of the segments of the image, constructed by counting the number of pixels falling into 36 Hue intervals of 10 degrees, is stored on a chip and compared against the histograms of new segments using SAD comparisons. We demonstrate color-based image segmentation and object recognition with this chip. Running at 30 fps, it uses 1 mW. To our knowledge, this is the first chip that integrates imaging, color segmentation, and color-based object recognition at the focal plane.

Segmentation of deformable organs from medical images using particle swarm optimization and nonlinear shape priors

Science.gov (United States)

Afifi, Ahmed; Nakaguchi, Toshiya; Tsumura, Norimichi

2010-03-01

In many medical applications, the automatic segmentation of deformable organs from medical images is indispensable and its accuracy is of a special interest. However, the automatic segmentation of these organs is a challenging task according to its complex shape. Moreover, the medical images usually have noise, clutter, or occlusion and considering the image information only often leads to meager image segmentation. In this paper, we propose a fully automated technique for the segmentation of deformable organs from medical images. In this technique, the segmentation is performed by fitting a nonlinear shape model with pre-segmented images. The kernel principle component analysis (KPCA) is utilized to capture the complex organs deformation and to construct the nonlinear shape model. The presegmentation is carried out by labeling each pixel according to its high level texture features extracted using the overcomplete wavelet packet decomposition. Furthermore, to guarantee an accurate fitting between the nonlinear model and the pre-segmented images, the particle swarm optimization (PSO) algorithm is employed to adapt the model parameters for the novel images. In this paper, we demonstrate the competence of proposed technique by implementing it to the liver segmentation from computed tomography (CT) scans of different patients.

Estimating the concentration of gold nanoparticles incorporated on natural rubber membranes using multi-level starlet optimal segmentation

Energy Technology Data Exchange (ETDEWEB)

Siqueira, A. F. de, E-mail: siqueiraaf@gmail.com; Cabrera, F. C., E-mail: flavioccabrera@yahoo.com.br [UNESP – Univ Estadual Paulista, Dep de Física, Química e Biologia (Brazil); Pagamisse, A., E-mail: aylton@fct.unesp.br [UNESP – Univ Estadual Paulista, Dep de Matemática e Computação (Brazil); Job, A. E., E-mail: job@fct.unesp.br [UNESP – Univ Estadual Paulista, Dep de Física, Química e Biologia (Brazil)

2014-12-15

This study consolidates multi-level starlet segmentation (MLSS) and multi-level starlet optimal segmentation (MLSOS) techniques for photomicrograph segmentation, based on starlet wavelet detail levels to separate areas of interest in an input image. Several segmentation levels can be obtained using MLSS; after that, Matthews correlation coefficient is used to choose an optimal segmentation level, giving rise to MLSOS. In this paper, MLSOS is employed to estimate the concentration of gold nanoparticles with diameter around 47  nm, reduced on natural rubber membranes. These samples were used for the construction of SERS/SERRS substrates and in the study of the influence of natural rubber membranes with incorporated gold nanoparticles on the physiology of Leishmania braziliensis. Precision, recall, and accuracy are used to evaluate the segmentation performance, and MLSOS presents an accuracy greater than 88 % for this application.

Level set method for image segmentation based on moment competition

Science.gov (United States)

Min, Hai; Wang, Xiao-Feng; Huang, De-Shuang; Jin, Jing; Wang, Hong-Zhi; Li, Hai

2015-05-01

We propose a level set method for image segmentation which introduces the moment competition and weakly supervised information into the energy functional construction. Different from the region-based level set methods which use force competition, the moment competition is adopted to drive the contour evolution. Here, a so-called three-point labeling scheme is proposed to manually label three independent points (weakly supervised information) on the image. Then the intensity differences between the three points and the unlabeled pixels are used to construct the force arms for each image pixel. The corresponding force is generated from the global statistical information of a region-based method and weighted by the force arm. As a result, the moment can be constructed and incorporated into the energy functional to drive the evolving contour to approach the object boundary. In our method, the force arm can take full advantage of the three-point labeling scheme to constrain the moment competition. Additionally, the global statistical information and weakly supervised information are successfully integrated, which makes the proposed method more robust than traditional methods for initial contour placement and parameter setting. Experimental results with performance analysis also show the superiority of the proposed method on segmenting different types of complicated images, such as noisy images, three-phase images, images with intensity inhomogeneity, and texture images.

Modelling the factors influencing the selection of the construction equipment for Indian construction organizations

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S.V.S. Raja Prasad

2016-09-01

Full Text Available The contribution of Indian construction sector to the GDP is approximately 10%. Under new government policy, it is anticipated that $1000 Billion share for exclusively infrastructure segment would be completed within the next few years. Construction sector in developing country like India still depends on labor and the practice of mechanization, adopting to use of versatile construction equipment is not in force. The need for implementing new technologies and automation is essential to improve the quality, safety and efficiency. To meet the challenges ahead the construction, organizations should focus on utilization of machinery/equipment to achieve desirable results. Modern construction is characterized by the increase in utilization of equipment to accomplish numerous construction activities. The selection of construction equipment often affects the required amount of time and effort. It is therefore important for managements of construction organizations and planners to be familiar with the features of various types of equipment commonly used in construction activities. The selection of appropriate equipment is a crucial decision making process as it involves huge capital investment. The purpose of the present study is to develop a model pertaining to the factors influencing the selection of construction equipment by using interpretive structural modelling and the results indicate that productivity and safety are the important factors in selection of equipment in Indian construction organizations.

Accounting for segment correlations in segmented gamma-ray scans

International Nuclear Information System (INIS)

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

1994-01-01

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

3D liver segmentation using multiple region appearances and graph cuts

Energy Technology Data Exchange (ETDEWEB)

Peng, Jialin, E-mail: 2004pjl@163.com; Zhang, Hongbo [College of Computer Science and Technology, Huaqiao University, Xiamen 361021 (China); Hu, Peijun; Lu, Fang; Kong, Dexing [College of Mathematics, Zhejiang University, Hangzhou 310027 (China); Peng, Zhiyi [Department of Radiology, First Affiliated Hospital, Zhejiang University, Hangzhou 310027 (China)

2015-12-15

. In addition, user operator variability experiments showed its good reproducibility. Conclusions: A multiregion-appearance based method is proposed and evaluated to segment liver. This approach does not require prior model construction and so eliminates the burdens associated with model construction and matching. The proposed method provides comparable results with state-of-the-art methods. Validation results suggest that it may be suitable for the clinical use.

MR brain scan tissues and structures segmentation: local cooperative Markovian agents and Bayesian formulation

International Nuclear Information System (INIS)

Scherrer, B.

2008-12-01

Accurate magnetic resonance brain scan segmentation is critical in a number of clinical and neuroscience applications. This task is challenging due to artifacts, low contrast between tissues and inter-individual variability that inhibit the introduction of a priori knowledge. In this thesis, we propose a new MR brain scan segmentation approach. Unique features of this approach include (1) the coupling of tissue segmentation, structure segmentation and prior knowledge construction, and (2) the consideration of local image properties. Locality is modeled through a multi-agent framework: agents are distributed into the volume and perform a local Markovian segmentation. As an initial approach (LOCUS, Local Cooperative Unified Segmentation), intuitive cooperation and coupling mechanisms are proposed to ensure the consistency of local models. Structures are segmented via the introduction of spatial localization constraints based on fuzzy spatial relations between structures. In a second approach, (LOCUS-B, LOCUS in a Bayesian framework) we consider the introduction of a statistical atlas to describe structures. The problem is reformulated in a Bayesian framework, allowing a statistical formalization of coupling and cooperation. Tissue segmentation, local model regularization, structure segmentation and local affine atlas registration are then coupled in an EM framework and mutually improve. The evaluation on simulated and real images shows good results, and in particular, a robustness to non-uniformity and noise with low computational cost. Local distributed and cooperative MRF models then appear as a powerful and promising approach for medical image segmentation. (author)

Hyperspectral image segmentation using a cooperative nonparametric approach

Science.gov (United States)

Taher, Akar; Chehdi, Kacem; Cariou, Claude

2013-10-01

In this paper a new unsupervised nonparametric cooperative and adaptive hyperspectral image segmentation approach is presented. The hyperspectral images are partitioned band by band in parallel and intermediate classification results are evaluated and fused, to get the final segmentation result. Two unsupervised nonparametric segmentation methods are used in parallel cooperation, namely the Fuzzy C-means (FCM) method, and the Linde-Buzo-Gray (LBG) algorithm, to segment each band of the image. The originality of the approach relies firstly on its local adaptation to the type of regions in an image (textured, non-textured), and secondly on the introduction of several levels of evaluation and validation of intermediate segmentation results before obtaining the final partitioning of the image. For the management of similar or conflicting results issued from the two classification methods, we gradually introduced various assessment steps that exploit the information of each spectral band and its adjacent bands, and finally the information of all the spectral bands. In our approach, the detected textured and non-textured regions are treated separately from feature extraction step, up to the final classification results. This approach was first evaluated on a large number of monocomponent images constructed from the Brodatz album. Then it was evaluated on two real applications using a respectively multispectral image for Cedar trees detection in the region of Baabdat (Lebanon) and a hyperspectral image for identification of invasive and non invasive vegetation in the region of Cieza (Spain). A correct classification rate (CCR) for the first application is over 97% and for the second application the average correct classification rate (ACCR) is over 99%.

A KST framework for correlation network construction from time series signals

Science.gov (United States)

Qi, Jin-Peng; Gu, Quan; Zhu, Ying; Zhang, Ping

2018-04-01

A KST (Kolmogorov-Smirnov test and T statistic) method is used for construction of a correlation network based on the fluctuation of each time series within the multivariate time signals. In this method, each time series is divided equally into multiple segments, and the maximal data fluctuation in each segment is calculated by a KST change detection procedure. Connections between each time series are derived from the data fluctuation matrix, and are used for construction of the fluctuation correlation network (FCN). The method was tested with synthetic simulations and the result was compared with those from using KS or T only for detection of data fluctuation. The novelty of this study is that the correlation analyses was based on the data fluctuation in each segment of each time series rather than on the original time signals, which would be more meaningful for many real world applications and for analysis of large-scale time signals where prior knowledge is uncertain.

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

NARCIS (Netherlands)

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

2007-01-01

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

Incremental and Enhanced Scanline-Based Segmentation Method for Surface Reconstruction of Sparse LiDAR Data

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Weimin Wang

2016-11-01

Full Text Available The segmentation of point clouds is an important aspect of automated processing tasks such as semantic extraction. However, the sparsity and non-uniformity of the point clouds gathered by the popular 3D mobile LiDAR devices pose many challenges for existing segmentation methods. To improve the segmentation results of point clouds from mobile LiDAR devices, we propose an optimized segmentation method based on Scanline Continuity Constraint (SLCC in this work. Unlike conventional scanline-based segmentation methods, SLCC clusters scanlines using the continuity constraints in terms of the distance as well as the direction of two consecutive points. In addition, scanline clusters are agglomerated not only into primitive geometrical shapes but also irregular shapes. Another downside to existing segmentation methods is that they are not capable of incremental processing. This causes unnecessary memory and time consumption for applications that require frame-wise segmentation or when new point clouds are added. In order to address this, we propose an incremental scheme—the Incremental Recursive Segmentation (IRIS, that can be easily applied to any segmentation method. IRIS is achieved by combining the segments of newly added point clouds and the previously segmented results. Furthermore, as an example application, we construct a processing pipeline consisting of plane fitting and surface reconstruction using the segmentation results. Finally, we evaluate the proposed methods on three datasets acquired from a handheld Velodyne HDL-32E LiDAR device. The experimental results verify the efficiency of IRIS for any segmentation method and the advantages of SLCC for processing mobile LiDAR data.

Precise Alignment and Permanent Mounting of Thin and Lightweight X-ray Segments

Science.gov (United States)

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

2012-01-01

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

Localized Segment Based Processing for Automatic Building Extraction from LiDAR Data

Science.gov (United States)

Parida, G.; Rajan, K. S.

2017-05-01

The current methods of object segmentation and extraction and classification of aerial LiDAR data is manual and tedious task. This work proposes a technique for object segmentation out of LiDAR data. A bottom-up geometric rule based approach was used initially to devise a way to segment buildings out of the LiDAR datasets. For curved wall surfaces, comparison of localized surface normals was done to segment buildings. The algorithm has been applied to both synthetic datasets as well as real world dataset of Vaihingen, Germany. Preliminary results show successful segmentation of the buildings objects from a given scene in case of synthetic datasets and promissory results in case of real world data. The advantages of the proposed work is non-dependence on any other form of data required except LiDAR. It is an unsupervised method of building segmentation, thus requires no model training as seen in supervised techniques. It focuses on extracting the walls of the buildings to construct the footprint, rather than focussing on roof. The focus on extracting the wall to reconstruct the buildings from a LiDAR scene is crux of the method proposed. The current segmentation approach can be used to get 2D footprints of the buildings, with further scope to generate 3D models. Thus, the proposed method can be used as a tool to get footprints of buildings in urban landscapes, helping in urban planning and the smart cities endeavour.

LOCALIZED SEGMENT BASED PROCESSING FOR AUTOMATIC BUILDING EXTRACTION FROM LiDAR DATA

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G. Parida

2017-05-01

Full Text Available The current methods of object segmentation and extraction and classification of aerial LiDAR data is manual and tedious task. This work proposes a technique for object segmentation out of LiDAR data. A bottom-up geometric rule based approach was used initially to devise a way to segment buildings out of the LiDAR datasets. For curved wall surfaces, comparison of localized surface normals was done to segment buildings. The algorithm has been applied to both synthetic datasets as well as real world dataset of Vaihingen, Germany. Preliminary results show successful segmentation of the buildings objects from a given scene in case of synthetic datasets and promissory results in case of real world data. The advantages of the proposed work is non-dependence on any other form of data required except LiDAR. It is an unsupervised method of building segmentation, thus requires no model training as seen in supervised techniques. It focuses on extracting the walls of the buildings to construct the footprint, rather than focussing on roof. The focus on extracting the wall to reconstruct the buildings from a LiDAR scene is crux of the method proposed. The current segmentation approach can be used to get 2D footprints of the buildings, with further scope to generate 3D models. Thus, the proposed method can be used as a tool to get footprints of buildings in urban landscapes, helping in urban planning and the smart cities endeavour.

Spinal segmental dysgenesis

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N Mahomed

2009-06-01

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

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.

Whole vertebral bone segmentation method with a statistical intensity-shape model based approach

Science.gov (United States)

Hanaoka, Shouhei; Fritscher, Karl; Schuler, Benedikt; Masutani, Yoshitaka; Hayashi, Naoto; Ohtomo, Kuni; Schubert, Rainer

2011-03-01

An automatic segmentation algorithm for the vertebrae in human body CT images is presented. Especially we focused on constructing and utilizing 4 different statistical intensity-shape combined models for the cervical, upper / lower thoracic and lumbar vertebrae, respectively. For this purpose, two previously reported methods were combined: a deformable model-based initial segmentation method and a statistical shape-intensity model-based precise segmentation method. The former is used as a pre-processing to detect the position and orientation of each vertebra, which determines the initial condition for the latter precise segmentation method. The precise segmentation method needs prior knowledge on both the intensities and the shapes of the objects. After PCA analysis of such shape-intensity expressions obtained from training image sets, vertebrae were parametrically modeled as a linear combination of the principal component vectors. The segmentation of each target vertebra was performed as fitting of this parametric model to the target image by maximum a posteriori estimation, combined with the geodesic active contour method. In the experimental result by using 10 cases, the initial segmentation was successful in 6 cases and only partially failed in 4 cases (2 in the cervical area and 2 in the lumbo-sacral). In the precise segmentation, the mean error distances were 2.078, 1.416, 0.777, 0.939 mm for cervical, upper and lower thoracic, lumbar spines, respectively. In conclusion, our automatic segmentation algorithm for the vertebrae in human body CT images showed a fair performance for cervical, thoracic and lumbar vertebrae.

An Overview of Techniques for Cardiac Left Ventricle Segmentation on Short-Axis MRI

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Krasnobaev Arseny

2016-01-01

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

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

Remote Sensing Image Registration with Line Segments and Their Intersections

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Chengjin Lyu

2017-05-01

Full Text Available Image registration is a basic but essential step for remote sensing image processing, and finding stable features in multitemporal images is one of the most considerable challenges in the field. The main shape contours of artificial objects (e.g., roads, buildings, farmlands, and airports can be generally described as a group of line segments, which are stable features, even in images with evident background changes (e.g., images taken before and after a disaster. In this study, a registration method that uses line segments and their intersections is proposed for multitemporal remote sensing images. First, line segments are extracted in image pyramids to unify the scales of the reference image and the test image. Then, a line descriptor based on the gradient distribution of local areas is constructed, and the segments are matched in image pyramids. Lastly, triplets of intersections of matching lines are selected to estimate affine transformation between two images. Additional corresponding intersections are provided based on the estimated transformation, and an iterative process is adopted to remove outliers. The performance of the proposed method is tested on a variety of optical remote sensing image pairs, including synthetic and real data. Compared with existing methods, our method can provide more accurate registration results, even in images with significant background changes.

Engraftment of Prevascularized, Tissue Engineered Constructs in a Novel Rabbit Segmental Bone Defect Model

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Alexandre Kaempfen

2015-06-01

Full Text Available The gold standard treatment of large segmental bone defects is autologous bone transfer, which suffers from low availability and additional morbidity. Tissue engineered bone able to engraft orthotopically and a suitable animal model for pre-clinical testing are direly needed. This study aimed to evaluate engraftment of tissue-engineered bone with different prevascularization strategies in a novel segmental defect model in the rabbit humerus. Decellularized bone matrix (Tutobone seeded with bone marrow mesenchymal stromal cells was used directly orthotopically or combined with a vessel and inserted immediately (1-step or only after six weeks of subcutaneous “incubation” (2-step. After 12 weeks, histological and radiological assessment was performed. Variable callus formation was observed. No bone formation or remodeling of the graft through TRAP positive osteoclasts could be detected. Instead, a variable amount of necrotic tissue formed. Although necrotic area correlated significantly with amount of vessels and the 2-step strategy had significantly more vessels than the 1-step strategy, no significant reduction of necrotic area was found. In conclusion, the animal model developed here represents a highly challenging situation, for which a suitable engineered bone graft with better prevascularization, better resorbability and higher osteogenicity has yet to be developed.

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.

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

segmental branches, and longitudinal matching of airway branches in repeated scans of the same subject. Methods and Materials: The segmentation process begins from an automatically detected seed point in the trachea. The airway centerline tree is then constructed by iteratively adding locally optimal paths...... differences. Results: The segmentation method has been used on 9711 low dose CT images from the Danish Lung Cancer Screening Trial (DLCST). Manual inspection of thumbnail images revealed gross errors in a total of 44 images. 29 were missing branches at the lobar level and only 15 had obvious false positives...... measurements to segments matched in multiple images of the same subject using image registration was observed to increase their reproducibility. The anatomical branch labeling tool was validated on a subset of 20 subjects, 5 of each category: asymptomatic, mild, moderate and severe COPD. The average inter...

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

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Praveen Agarwal

2017-06-01

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

Hierarchical graph-based segmentation for extracting road networks from high-resolution satellite images

Science.gov (United States)

Alshehhi, Rasha; Marpu, Prashanth Reddy

2017-04-01

Extraction of road networks in urban areas from remotely sensed imagery plays an important role in many urban applications (e.g. road navigation, geometric correction of urban remote sensing images, updating geographic information systems, etc.). It is normally difficult to accurately differentiate road from its background due to the complex geometry of the buildings and the acquisition geometry of the sensor. In this paper, we present a new method for extracting roads from high-resolution imagery based on hierarchical graph-based image segmentation. The proposed method consists of: 1. Extracting features (e.g., using Gabor and morphological filtering) to enhance the contrast between road and non-road pixels, 2. Graph-based segmentation consisting of (i) Constructing a graph representation of the image based on initial segmentation and (ii) Hierarchical merging and splitting of image segments based on color and shape features, and 3. Post-processing to remove irregularities in the extracted road segments. Experiments are conducted on three challenging datasets of high-resolution images to demonstrate the proposed method and compare with other similar approaches. The results demonstrate the validity and superior performance of the proposed method for road extraction in urban areas.

Robust generative asymmetric GMM for brain MR image segmentation.

Science.gov (United States)

Ji, Zexuan; Xia, Yong; Zheng, Yuhui

2017-11-01

Accurate segmentation of brain tissues from magnetic resonance (MR) images based on the unsupervised statistical models such as Gaussian mixture model (GMM) has been widely studied during last decades. However, most GMM based segmentation methods suffer from limited accuracy due to the influences of noise and intensity inhomogeneity in brain MR images. To further improve the accuracy for brain MR image segmentation, this paper presents a Robust Generative Asymmetric GMM (RGAGMM) for simultaneous brain MR image segmentation and intensity inhomogeneity correction. First, we develop an asymmetric distribution to fit the data shapes, and thus construct a spatial constrained asymmetric model. Then, we incorporate two pseudo-likelihood quantities and bias field estimation into the model's log-likelihood, aiming to exploit the neighboring priors of within-cluster and between-cluster and to alleviate the impact of intensity inhomogeneity, respectively. Finally, an expectation maximization algorithm is derived to iteratively maximize the approximation of the data log-likelihood function to overcome the intensity inhomogeneity in the image and segment the brain MR images simultaneously. To demonstrate the performances of the proposed algorithm, we first applied the proposed algorithm to a synthetic brain MR image to show the intermediate illustrations and the estimated distribution of the proposed algorithm. The next group of experiments is carried out in clinical 3T-weighted brain MR images which contain quite serious intensity inhomogeneity and noise. Then we quantitatively compare our algorithm to state-of-the-art segmentation approaches by using Dice coefficient (DC) on benchmark images obtained from IBSR and BrainWeb with different level of noise and intensity inhomogeneity. The comparison results on various brain MR images demonstrate the superior performances of the proposed algorithm in dealing with the noise and intensity inhomogeneity. In this paper, the RGAGMM

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.

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.

Market Segmentation in Business Technology Base: The Case of Segmentation of Sparkling

Directory of Open Access Journals (Sweden)

Valéria Riscarolli

2014-08-01

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

Object segmentation using graph cuts and active contours in a pyramidal framework

Science.gov (United States)

Subudhi, Priyambada; Mukhopadhyay, Susanta

2018-03-01

Graph cuts and active contours are two very popular interactive object segmentation techniques in the field of computer vision and image processing. However, both these approaches have their own well-known limitations. Graph cut methods perform efficiently giving global optimal segmentation result for smaller images. However, for larger images, huge graphs need to be constructed which not only takes an unacceptable amount of memory but also increases the time required for segmentation to a great extent. On the other hand, in case of active contours, initial contour selection plays an important role in the accuracy of the segmentation. So a proper selection of initial contour may improve the complexity as well as the accuracy of the result. In this paper, we have tried to combine these two approaches to overcome their above-mentioned drawbacks and develop a fast technique of object segmentation. Here, we have used a pyramidal framework and applied the mincut/maxflow algorithm on the lowest resolution image with the least number of seed points possible which will be very fast due to the smaller size of the image. Then, the obtained segmentation contour is super-sampled and and worked as the initial contour for the next higher resolution image. As the initial contour is very close to the actual contour, so fewer number of iterations will be required for the convergence of the contour. The process is repeated for all the high-resolution images and experimental results show that our approach is faster as well as memory efficient as compare to both graph cut or active contour segmentation alone.

A region-based segmentation method for ultrasound images in HIFU therapy

International Nuclear Information System (INIS)

Zhang, Dong; Liu, Yu; Yang, Yan; Xu, Menglong; Yan, Yu; Qin, Qianqing

2016-01-01

Purpose: Precisely and efficiently locating a tumor with less manual intervention in ultrasound-guided high-intensity focused ultrasound (HIFU) therapy is one of the keys to guaranteeing the therapeutic result and improving the efficiency of the treatment. The segmentation of ultrasound images has always been difficult due to the influences of speckle, acoustic shadows, and signal attenuation as well as the variety of tumor appearance. The quality of HIFU guidance images is even poorer than that of conventional diagnostic ultrasound images because the ultrasonic probe used for HIFU guidance usually obtains images without making contact with the patient’s body. Therefore, the segmentation becomes more difficult. To solve the segmentation problem of ultrasound guidance image in the treatment planning procedure for HIFU therapy, a novel region-based segmentation method for uterine fibroids in HIFU guidance images is proposed. Methods: Tumor partitioning in HIFU guidance image without manual intervention is achieved by a region-based split-and-merge framework. A new iterative multiple region growing algorithm is proposed to first split the image into homogenous regions (superpixels). The features extracted within these homogenous regions will be more stable than those extracted within the conventional neighborhood of a pixel. The split regions are then merged by a superpixel-based adaptive spectral clustering algorithm. To ensure the superpixels that belong to the same tumor can be clustered together in the merging process, a particular construction strategy for the similarity matrix is adopted for the spectral clustering, and the similarity matrix is constructed by taking advantage of a combination of specifically selected first-order and second-order texture features computed from the gray levels and the gray level co-occurrence matrixes, respectively. The tumor region is picked out automatically from the background regions by an algorithm according to a priori

A region-based segmentation method for ultrasound images in HIFU therapy

Energy Technology Data Exchange (ETDEWEB)

Zhang, Dong, E-mail: dongz@whu.edu.cn; Liu, Yu; Yang, Yan; Xu, Menglong; Yan, Yu [School of Physics and Technology, Wuhan University, Wuhan 430072 (China); Qin, Qianqing [State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072 (China)

2016-06-15

Purpose: Precisely and efficiently locating a tumor with less manual intervention in ultrasound-guided high-intensity focused ultrasound (HIFU) therapy is one of the keys to guaranteeing the therapeutic result and improving the efficiency of the treatment. The segmentation of ultrasound images has always been difficult due to the influences of speckle, acoustic shadows, and signal attenuation as well as the variety of tumor appearance. The quality of HIFU guidance images is even poorer than that of conventional diagnostic ultrasound images because the ultrasonic probe used for HIFU guidance usually obtains images without making contact with the patient’s body. Therefore, the segmentation becomes more difficult. To solve the segmentation problem of ultrasound guidance image in the treatment planning procedure for HIFU therapy, a novel region-based segmentation method for uterine fibroids in HIFU guidance images is proposed. Methods: Tumor partitioning in HIFU guidance image without manual intervention is achieved by a region-based split-and-merge framework. A new iterative multiple region growing algorithm is proposed to first split the image into homogenous regions (superpixels). The features extracted within these homogenous regions will be more stable than those extracted within the conventional neighborhood of a pixel. The split regions are then merged by a superpixel-based adaptive spectral clustering algorithm. To ensure the superpixels that belong to the same tumor can be clustered together in the merging process, a particular construction strategy for the similarity matrix is adopted for the spectral clustering, and the similarity matrix is constructed by taking advantage of a combination of specifically selected first-order and second-order texture features computed from the gray levels and the gray level co-occurrence matrixes, respectively. The tumor region is picked out automatically from the background regions by an algorithm according to a priori

Fluence map segmentation

International Nuclear Information System (INIS)

Rosenwald, J.-C.

2008-01-01

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

Strategic market segmentation

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.

Why segmentation matters: Experience-driven segmentation errors impair "morpheme" learning.

Science.gov (United States)

Finn, Amy S; Hudson Kam, Carla L

2015-09-01

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

Measuring the three process segments of a customer's service experience for an out-patient surgery center.

Science.gov (United States)

Wicks, Angela M; Chin, Wynne W

2008-01-01

The purpose of this research is to develop an alternative method of measuring out-patient satisfaction where satisfaction is the central construct. The Gap Model operationalized by SERVQUAL is widely used to measure service quality. However, the SERVQUAL instrument only measures expectations (resulting from the pre-process segment of the service experience) and perceptions (resulting from the post-process segment). All three segments should be measured. The lack of proper segmentation and methodological criticisms in the literature motivated this study. A partial least squares (PLS) approach, a form of structural equation modeling, is used to develop a framework to evaluate patient satisfaction in three service process segments: pre-process, process, and post-process service experiences. Results indicate that each process stage mediates subsequent stages, that the process segment is the most important to the patient and that the antecedents have differing impacts on patient satisfaction depending where in the process the antecedent is evaluated. Only one out-patient surgery center was evaluated. Patient satisfaction criteria specific to hospital selection are not included in this study. Results indicate what is important to patients in each service process segment that focus where ambulatory surgery centers should allocate resources. This study is the first to evaluate patient satisfaction with all three process segments.

Application of a semi-automatic cartilage segmentation method for biomechanical modeling of the knee joint.

Science.gov (United States)

Liukkonen, Mimmi K; Mononen, Mika E; Tanska, Petri; Saarakkala, Simo; Nieminen, Miika T; Korhonen, Rami K

2017-10-01

Manual segmentation of articular cartilage from knee joint 3D magnetic resonance images (MRI) is a time consuming and laborious task. Thus, automatic methods are needed for faster and reproducible segmentations. In the present study, we developed a semi-automatic segmentation method based on radial intensity profiles to generate 3D geometries of knee joint cartilage which were then used in computational biomechanical models of the knee joint. Six healthy volunteers were imaged with a 3T MRI device and their knee cartilages were segmented both manually and semi-automatically. The values of cartilage thicknesses and volumes produced by these two methods were compared. Furthermore, the influences of possible geometrical differences on cartilage stresses and strains in the knee were evaluated with finite element modeling. The semi-automatic segmentation and 3D geometry construction of one knee joint (menisci, femoral and tibial cartilages) was approximately two times faster than with manual segmentation. Differences in cartilage thicknesses, volumes, contact pressures, stresses, and strains between segmentation methods in femoral and tibial cartilage were mostly insignificant (p > 0.05) and random, i.e. there were no systematic differences between the methods. In conclusion, the devised semi-automatic segmentation method is a quick and accurate way to determine cartilage geometries; it may become a valuable tool for biomechanical modeling applications with large patient groups.

Segmentation algorithm on smartphone dual camera: application to plant organs in the wild

Science.gov (United States)

Bertrand, Sarah; Cerutti, Guillaume; Tougne, Laure

2018-04-01

In order to identify the species of a tree, the different organs that are the leaves, the bark, the flowers and the fruits, are inspected by botanists. So as to develop an algorithm that identifies automatically the species, we need to extract these objects of interest from their complex natural environment. In this article, we focus on the segmentation of flowers and fruits and we present a new method of segmentation based on an active contour algorithm using two probability maps. The first map is constructed via the dual camera that we can find on the back of the latest smartphones. The second map is made with the help of a multilayer perceptron (MLP). The combination of these two maps to drive the evolution of the object contour allows an efficient segmentation of the organ from a natural background.

Estimating construction and demolition debris generation using a materials flow analysis approach.

Science.gov (United States)

Cochran, K M; Townsend, T G

2010-11-01

The magnitude and composition of a region's construction and demolition (C&D) debris should be understood when developing rules, policies and strategies for managing this segment of the solid waste stream. In the US, several national estimates have been conducted using a weight-per-construction-area approximation; national estimates using alternative procedures such as those used for other segments of the solid waste stream have not been reported for C&D debris. This paper presents an evaluation of a materials flow analysis (MFA) approach for estimating C&D debris generation and composition for a large region (the US). The consumption of construction materials in the US and typical waste factors used for construction materials purchasing were used to estimate the mass of solid waste generated as a result of construction activities. Debris from demolition activities was predicted from various historical construction materials consumption data and estimates of average service lives of the materials. The MFA approach estimated that approximately 610-78 × 10(6)Mg of C&D debris was generated in 2002. This predicted mass exceeds previous estimates using other C&D debris predictive methodologies and reflects the large waste stream that exists. Copyright © 2010 Elsevier Ltd. All rights reserved.

Improved dynamic-programming-based algorithms for segmentation of masses in mammograms

International Nuclear Information System (INIS)

Dominguez, Alfonso Rojas; Nandi, Asoke K.

2007-01-01

In this paper, two new boundary tracing algorithms for segmentation of breast masses are presented. These new algorithms are based on the dynamic programming-based boundary tracing (DPBT) algorithm proposed in Timp and Karssemeijer, [S. Timp and N. Karssemeijer, Med. Phys. 31, 958-971 (2004)] The DPBT algorithm contains two main steps: (1) construction of a local cost function, and (2) application of dynamic programming to the selection of the optimal boundary based on the local cost function. The validity of some assumptions used in the design of the DPBT algorithm is tested in this paper using a set of 349 mammographic images. Based on the results of the tests, modifications to the computation of the local cost function have been designed and have resulted in the Improved-DPBT (IDPBT) algorithm. A procedure for the dynamic selection of the strength of the components of the local cost function is presented that makes these parameters independent of the image dataset. Incorporation of this dynamic selection procedure has produced another new algorithm which we have called ID 2 PBT. Methods for the determination of some other parameters of the DPBT algorithm that were not covered in the original paper are presented as well. The merits of the new IDPBT and ID 2 PBT algorithms are demonstrated experimentally by comparison against the DPBT algorithm. The segmentation results are evaluated with base on the area overlap measure and other segmentation metrics. Both of the new algorithms outperform the original DPBT; the improvements in the algorithms performance are more noticeable around the values of the segmentation metrics corresponding to the highest segmentation accuracy, i.e., the new algorithms produce more optimally segmented regions, rather than a pronounced increase in the average quality of all the segmented regions

Chain segmentation for the Monte Carlo solution of particle transport problems

International Nuclear Information System (INIS)

Ragheb, M.M.H.

1984-01-01

A Monte Carlo approach is proposed where the random walk chains generated in particle transport simulations are segmented. Forward and adjoint-mode estimators are then used in conjunction with the firstevent source density on the segmented chains to obtain multiple estimates of the individual terms of the Neumann series solution at each collision point. The solution is then constructed by summation of the series. The approach is compared to the exact analytical and to the Monte Carlo nonabsorption weighting method results for two representative slowing down and deep penetration problems. Application of the proposed approach leads to unbiased estimates for limited numbers of particle simulations and is useful in suppressing an effective bias problem observed in some cases of deep penetration particle transport problems

Targeted tandem duplication of a large chromosomal segment in Aspergillus oryzae.

Science.gov (United States)

Takahashi, Tadashi; Sato, Atsushi; Ogawa, Masahiro; Hanya, Yoshiki; Oguma, Tetsuya

2014-08-01

We describe here the first successful construction of a targeted tandem duplication of a large chromosomal segment in Aspergillus oryzae. The targeted tandem chromosomal duplication was achieved by using strains that had a 5'-deleted pyrG upstream of the region targeted for tandem chromosomal duplication and a 3'-deleted pyrG downstream of the target region. Consequently,strains bearing a 210-kb targeted tandem chromosomal duplication near the centromeric region of chromosome 8 and strains bearing a targeted tandem chromosomal duplication of a 700-kb region of chromosome 2 were successfully constructed. The strains bearing the tandem chromosomal duplication were efficiently obtained from the regenerated protoplast of the parental strains. However, the generation of the chromosomal duplication did not depend on the introduction of double-stranded breaks(DSBs) by I-SceI. The chromosomal duplications of these strains were stably maintained after five generations of culture under nonselective conditions. The strains bearing the tandem chromosomal duplication in the 700-kb region of chromosome 2 showed highly increased protease activity in solid-state culture, indicating that the duplication of large chromosomal segments could be a useful new breeding technology and gene analysis method.

Meta-shell Approach for Constructing Lightweight and High Resolution X-Ray Optics

Science.gov (United States)

McClelland, Ryan S.

2016-01-01

Lightweight and high resolution optics are needed for future space-based x-ray telescopes to achieve advances in high-energy astrophysics. Past missions such as Chandra and XMM-Newton have achieved excellent angular resolution using a full shell mirror approach. Other missions such as Suzaku and NuSTAR have achieved lightweight mirrors using a segmented approach. This paper describes a new approach, called meta-shells, which combines the fabrication advantages of segmented optics with the alignment advantages of full shell optics. Meta-shells are built by layering overlapping mirror segments onto a central structural shell. The resulting optic has the stiffness and rotational symmetry of a full shell, but with an order of magnitude greater collecting area. Several meta-shells so constructed can be integrated into a large x-ray mirror assembly by proven methods used for Chandra and XMM-Newton. The mirror segments are mounted to the meta-shell using a novel four point semi-kinematic mount. The four point mount deterministically locates the segment in its most performance sensitive degrees of freedom. Extensive analysis has been performed to demonstrate the feasibility of the four point mount and meta-shell approach. A mathematical model of a meta-shell constructed with mirror segments bonded at four points and subject to launch loads has been developed to determine the optimal design parameters, namely bond size, mirror segment span, and number of layers per meta-shell. The parameters of an example 1.3 m diameter mirror assembly are given including the predicted effective area. To verify the mathematical model and support opto-mechanical analysis, a detailed finite element model of a meta-shell was created. Finite element analysis predicts low gravity distortion and low thermal distortion. Recent results are discussed including Structural Thermal Optical Performance (STOP) analysis as well as vibration and shock testing of prototype meta-shells.

Construction of a long-distance, sharply curved underground sewerage system by the pit/drift continuous shielding method. Construction of the Arakawa trunk line by the Tokyo Metropolitan Government; Juo renzoku shield koho ni yoru chokyori kyukyokusen seko. Tokyoto gesuidokyoku Arakawa kansen koji

Energy Technology Data Exchange (ETDEWEB)

Nagashima, Y.; Okai, F.; Akasaka, J.

1998-06-25

The problems encountered in construction of sewarage systems in urban areas are reduced pitting sites, and construction of deeper, longer-distance and more sharply curved systems, resulting from overpopulation both on and under the ground. The Arakawa trunk line, constructed by the Tokyo Metropolitan Government, is to connect the existing Mikawashima sewage plant to Higashioku Sewage Purification Center now under construction, 2400m in total length, 40m as pit depth and 15m in the minimum curvature R, and needs shielding works for segment external forms of 4700mm. The construction method employed is the pit/drift continuous shielding method, which allows continuous works from a pit to drift by a single shielding machine. The machine is equipped with a spherical body holding a drift shielding machine built in a pit shielding machine, to excavate a pit to a given depth, and then a drift after turning the spherical body by 90deg. Each pit is equipped with a lift and each drift with an adequate system to move the segments. Bag-equipped segments are used for sharp curves. The pit/drift shielding method has been already applied to 5 cases, including the Arakawa trunk line construction, centered by those for sewarage systems. 1 ref., 6 figs.

I/O-Efficient Construction of Constrained Delaunay Triangulations

DEFF Research Database (Denmark)

Agarwal, Pankaj Kumar; Arge, Lars; Yi, Ke

2005-01-01

In this paper, we designed and implemented an I/O-efficient algorithm for constructing constrained Delaunay triangulations. If the number of constraining segments is smaller than the memory size, our algorithm runs in expected O( N B logM/B NB ) I/Os for triangulating N points in the plane, where...

DeepCotton: in-field cotton segmentation using deep fully convolutional network

Science.gov (United States)

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

2017-09-01

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

a Super Voxel-Based Riemannian Graph for Multi Scale Segmentation of LIDAR Point Clouds

Science.gov (United States)

Li, Minglei

2018-04-01

Automatically segmenting LiDAR points into respective independent partitions has become a topic of great importance in photogrammetry, remote sensing and computer vision. In this paper, we cast the problem of point cloud segmentation as a graph optimization problem by constructing a Riemannian graph. The scale space of the observed scene is explored by an octree-based over-segmentation with different depths. The over-segmentation produces many super voxels which restrict the structure of the scene and will be used as nodes of the graph. The Kruskal coordinates are used to compute edge weights that are proportional to the geodesic distance between nodes. Then we compute the edge-weight matrix in which the elements reflect the sectional curvatures associated with the geodesic paths between super voxel nodes on the scene surface. The final segmentation results are generated by clustering similar super voxels and cutting off the weak edges in the graph. The performance of this method was evaluated on LiDAR point clouds for both indoor and outdoor scenes. Additionally, extensive comparisons to state of the art techniques show that our algorithm outperforms on many metrics.

Development of a hadron blind detector using a finely segmented pad readout

International Nuclear Information System (INIS)

Kanno, Koki; Aoki, Kazuya; Aramaki, Yoki; En'yo, Hideto; Kawama, Daisuke; Komatsu, Yusuke; Masumoto, Shinichi; Nakai, Wataru; Obara, Yuki; Ozawa, Kyoichiro; Sekimoto, Michiko; Shibukawa, Takuya; Takahashi, Tomonori; Watanabe, Yosuke; Yokkaichi, Satoshi

2016-01-01

We constructed a hadron blind detector (HBD) using a finely segmented pad readout. The finely segmented pad readout enabled us to adopt an advanced particle identification method which applies a threshold to the number of pad hits in addition to the total amount of collected charge. The responses of the detector to electrons and pions were evaluated using a negatively charged secondary beam at 1.0 GeV/c containing 20% electrons at the J-PARC K1.1BR beam line. We observed 7.3 photoelectrons per incident electron. Using the advanced particle identification method, an electron detection efficiency of 83% was achieved with a pion rejection factor of 120. The method improved the pion rejection by approximately a factor of five, compared to the one which just applies a threshold to the amount of collected charge. The newly introduced finely segmented pad readout was found to be effective in rejecting pions.

Development of a hadron blind detector using a finely segmented pad readout

Energy Technology Data Exchange (ETDEWEB)

Kanno, Koki, E-mail: kkanno@post.kek.jp [Department of Physics, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); RIKEN Nishina Center for Accelerator-Based Science, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan); Aoki, Kazuya [High Energy Accelerator Research Organization (KEK), 1-1 Oho, Tsukuba-shi, Ibaraki 305-0801 (Japan); Aramaki, Yoki; En' yo, Hideto; Kawama, Daisuke [RIKEN Nishina Center for Accelerator-Based Science, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan); Komatsu, Yusuke; Masumoto, Shinichi [Department of Physics, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Nakai, Wataru [Department of Physics, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); RIKEN Nishina Center for Accelerator-Based Science, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan); Obara, Yuki [Department of Physics, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Ozawa, Kyoichiro; Sekimoto, Michiko [High Energy Accelerator Research Organization (KEK), 1-1 Oho, Tsukuba-shi, Ibaraki 305-0801 (Japan); Shibukawa, Takuya [Department of Physics, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Takahashi, Tomonori [Research Center for Nuclear Physics (RCNP), Osaka University, 10-1 Mihogaoka, Ibaraki, Osaka 567-0047 (Japan); Watanabe, Yosuke [Department of Physics, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Yokkaichi, Satoshi [RIKEN Nishina Center for Accelerator-Based Science, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan)

2016-05-21

We constructed a hadron blind detector (HBD) using a finely segmented pad readout. The finely segmented pad readout enabled us to adopt an advanced particle identification method which applies a threshold to the number of pad hits in addition to the total amount of collected charge. The responses of the detector to electrons and pions were evaluated using a negatively charged secondary beam at 1.0 GeV/c containing 20% electrons at the J-PARC K1.1BR beam line. We observed 7.3 photoelectrons per incident electron. Using the advanced particle identification method, an electron detection efficiency of 83% was achieved with a pion rejection factor of 120. The method improved the pion rejection by approximately a factor of five, compared to the one which just applies a threshold to the amount of collected charge. The newly introduced finely segmented pad readout was found to be effective in rejecting pions.

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

Speaker segmentation and clustering

OpenAIRE

Kotti, M; Moschou, V; Kotropoulos, C

2008-01-01

07.08.13 KB. Ok to add the accepted version to Spiral, Elsevier says ok whlile mandate not enforced. This survey focuses on two challenging speech processing topics, namely: speaker segmentation and speaker clustering. Speaker segmentation aims at finding speaker change points in an audio stream, whereas speaker clustering aims at grouping speech segments based on speaker characteristics. Model-based, metric-based, and hybrid speaker segmentation algorithms are reviewed. Concerning speaker...

Segmentation of the Infant Food Market

OpenAIRE

Hrůzová, Daniela

2015-01-01

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

Pancreas and cyst segmentation

Science.gov (United States)

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

2016-03-01

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

Phasing multi-segment undulators

International Nuclear Information System (INIS)

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

1996-01-01

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

FRAMEWORK FOR COMPARING SEGMENTATION ALGORITHMS

Directory of Open Access Journals (Sweden)

G. Sithole

2015-05-01

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

ESTIMATED DATE OF COMPLETION OF THE PLANNED MOTORWAY SEGMENTS IN THE CENTRAL, NORTH-WESTERN AND WESTERN REGIONS OF ROMANIA

Directory of Open Access Journals (Sweden)

CSUTAK ISTVAN

2013-08-01

Full Text Available Romania’s highways are standing ahead of considerably high investments. In the last few decades thetransport infrastructure has been pushed into the background due to lack of financial support. The 21st Centuryhas brought important breakthroughs in the building of highways. In the report on global risks in 2013published by WEF (World Economic Forum the "The prolonged neglect of infrastructure" is being consideredsuch a risk. Our study focuses on the construction works that have been carried out in the Central, North-Western and Western regions of Romania. The highways of the above mentioned regions will be analysed basedon three main points of focus: highways that have already been built, highways currently under construction andhighways that are planned to be built. The aim is to present and compare the 3 regions’ highway infrastructure,determination of an approximate end date for the highways that are currently under construction. It has beenconcluded, that until 2013 the construction work on segments funded by the EU progressed much faster, than theones funded by the government. The results of the study refer to how soon could the construction works reach anend on segments currently in progress.

Why segmentation matters: experience-driven segmentation errors impair “morpheme” learning

Science.gov (United States)

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

2015-01-01

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

Segment-Tube: Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation

OpenAIRE

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

2018-01-01

Inspired by the recent spatio-temporal action localization efforts with tubelets (sequences of bounding boxes), we present a new spatio-temporal action localization detector Segment-tube, which consists of sequences of per-frame segmentation masks. The proposed Segment-tube detector can temporally pinpoint the starting/ending frame of each action category in the presence of preceding/subsequent interference actions in untrimmed videos. Simultaneously, the Segment-tube detector produces per-fr...

Realization of Chinese word segmentation based on deep learning method

Science.gov (United States)

Wang, Xuefei; Wang, Mingjiang; Zhang, Qiquan

2017-08-01

In recent years, with the rapid development of deep learning, it has been widely used in the field of natural language processing. In this paper, I use the method of deep learning to achieve Chinese word segmentation, with large-scale corpus, eliminating the need to construct additional manual characteristics. In the process of Chinese word segmentation, the first step is to deal with the corpus, use word2vec to get word embedding of the corpus, each character is 50. After the word is embedded, the word embedding feature is fed to the bidirectional LSTM, add a linear layer to the hidden layer of the output, and then add a CRF to get the model implemented in this paper. Experimental results show that the method used in the 2014 People's Daily corpus to achieve a satisfactory accuracy.

Effects of Armature Winding Segmentation with Multiple Converters on the Short Circuit Torque of 10-MW Superconducting Wind Turbine Generators

DEFF Research Database (Denmark)

Liu, Dong; Polinder, Henk; Abrahamsen, Asger Bech

2017-01-01

Superconducting synchronous generators (SCSGs) are drawing more attention in large direct-drive wind turbine applications. Despite low weight and compactness, the short circuit torque of an SCSG may be too high for wind turbine constructions due to a large magnetic air gap of an SCSG. This paper...... aims at assessing the effects of armature winding segmentation on reducing the short circuit torque of 10-MW SCSGs. A concept of armature winding segmentation with multiple power electronic converters is presented. Four SCSG designs using different topologies are examined. Results show that armature...... winding segmentation effectively reduce the short circuit torque in all the four SCSG designs when one segment is shorted at the terminal....

Obtention of tumor volumes in PET images stacks using techniques of colored image segmentation

International Nuclear Information System (INIS)

Vieira, Jose W.; Lopes Filho, Ferdinand J.; Vieira, Igor F.

2014-01-01

This work demonstrated step by step how to segment color images of the chest of an adult in order to separate the tumor volume without significantly changing the values of the components R (Red), G (Green) and B (blue) of the colors of the pixels. For having information which allow to build color map you need to segment and classify the colors present at appropriate intervals in images. The used segmentation technique is to select a small rectangle with color samples in a given region and then erase with a specific color called 'rubber' the other regions of image. The tumor region was segmented into one of the images available and the procedure is displayed in tutorial format. All necessary computational tools have been implemented in DIP (Digital Image Processing), software developed by the authors. The results obtained, in addition to permitting the construction the colorful map of the distribution of the concentration of activity in PET images will also be useful in future work to enter tumors in voxel phantoms in order to perform dosimetric assessments

Construction of tomographic head model using sectioned photographic images of cadaver

International Nuclear Information System (INIS)

Lee, Choon Sik; Lee, Jai Ki; Park, Jin Seo; Chung, Min Suk

2004-01-01

Tomographic models are currently the most complete, developed and realistic models of the human anatomy. They have been used to estimate organ doses for diagnostic radiation examination and radiotherapy treatment planning, and radiation protection. The quality of original anatomic images is a key factor to build a quality tomographic model. Computed tomography (CT) and magnetic resonance imaging (MRI) scan, from which most of current tomographic models are constructed, have their inherent shortcomings. In this study, a tomographic model of Korean adult male head was constructed by using serially sectioned photographs of cadaver. The cadaver was embedded, frozen, serially sectioned and photographed by high resolution digital camera at 0.2 mm interval. The contours of organs and tissues in photographs were segmented by several trained anatomists. The 120 segmented images of head at 2mm interval were converted into binary files and ported into Monte Carlo code to perform an example calculation of organ dose. Whole body tomographic model will be constructed by using the procedure developed in this study

Global multi-scale segmentation of continental and coastal waters from the watersheds to the continental margins

NARCIS (Netherlands)

Laruelle, G.G.; Dürr, H.H.; Lauerwald, R.; Hartmann, J.; Slomp, C.P.; Goossens, N.; Regnier, P.A.G.

2013-01-01

Past characterizations of the land–ocean continuum were constructed either from a continental perspective through an analysis of watershed river basin properties (COSCATs: COastal Segmentation and related CATchments) or from an oceanic perspective, through a regionalization of the proximal and

Preliminary Analysis of the Knipovich Ridge Segmentation - Influence of Focused Magmatism and Ridge Obliquity on an Ultraslow Spreading System

Science.gov (United States)

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

2002-12-01

Bathymetry, gravity and deep-tow sonar image data are used to define the segmentation of a 400 km long portion of the ultraslow-spreading Knipovich Ridge in the Norwegian-Greenland Sea, Northeast Atlantic 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 (SWIR). 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° from north to south, respectively, while spreading rate and axial depth remain approximately constant. The increased obliquity may contribute to decreased effective spreading rates, lower upwelling magma velocity and melt formation, and limited horizontal dike propagation near the surface. We also identify small, magmatically weaker segments with low relief, little or no MBA anomaly, and no off axis expression. We suggest that these segments are either fed by lateral melt migration from adjacent magmatically stronger segments or represent smaller, discrete mantle upwelling centers with short-lived melt supply.

Preliminary analysis of the Knipovich Ridge segmentation: influence of focused magmatism and ridge obliquity on an ultraslow spreading system

Science.gov (United States)

Okino, Kyoko; Curewitz, Daniel; Asada, Miho; Tamaki, Kensaku; Vogt, Peter; Crane, Kathleen

2002-09-01

Bathymetry, gravity and deep-tow sonar image data are used to define the segmentation of a 400 km long portion of the ultraslow-spreading Knipovich Ridge in the Norwegian-Greenland Sea, Northeast Atlantic 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° from north to south, respectively, while spreading rate and axial depth remain approximately constant. The increased obliquity may contribute to decreased effective spreading rates, lower upwelling magma velocity and melt formation, and limited horizontal dike propagation near the surface. We also identify small, magmatically weaker segments with low relief, little or no MBA anomaly, and no off-axis expression. We suggest that these segments are either fed by lateral melt migration from adjacent magmatically stronger segments or represent smaller, discrete mantle upwelling centers with short-lived melt supply.

Phase congruency map driven brain tumour segmentation

Science.gov (United States)

Szilágyi, Tünde; Brady, Michael; Berényi, Ervin

2015-03-01

Computer Aided Diagnostic (CAD) systems are already of proven value in healthcare, especially for surgical planning, nevertheless much remains to be done. Gliomas are the most common brain tumours (70%) in adults, with a survival time of just 2-3 months if detected at WHO grades III or higher. Such tumours are extremely variable, necessitating multi-modal Magnetic Resonance Images (MRI). The use of Gadolinium-based contrast agents is only relevant at later stages of the disease where it highlights the enhancing rim of the tumour. Currently, there is no single accepted method that can be used as a reference. There are three main challenges with such images: to decide whether there is tumour present and is so localize it; to construct a mask that separates healthy and diseased tissue; and to differentiate between the tumour core and the surrounding oedema. This paper presents two contributions. First, we develop tumour seed selection based on multiscale multi-modal texture feature vectors. Second, we develop a method based on a local phase congruency based feature map to drive level-set segmentation. The segmentations achieved with our method are more accurate than previously presented methods, particularly for challenging low grade tumours.

Dynamic Post-Earthquake Image Segmentation with an Adaptive Spectral-Spatial Descriptor

Directory of Open Access Journals (Sweden)

Genyun Sun

2017-08-01

Full Text Available The region merging algorithm is a widely used segmentation technique for very high resolution (VHR remote sensing images. However, the segmentation of post-earthquake VHR images is more difficult due to the complexity of these images, especially high intra-class and low inter-class variability among damage objects. Herein two key issues must be resolved: the first is to find an appropriate descriptor to measure the similarity of two adjacent regions since they exhibit high complexity among the diverse damage objects, such as landslides, debris flow, and collapsed buildings. The other is how to solve over-segmentation and under-segmentation problems, which are commonly encountered with conventional merging strategies due to their strong dependence on local information. To tackle these two issues, an adaptive dynamic region merging approach (ADRM is introduced, which combines an adaptive spectral-spatial descriptor and a dynamic merging strategy to adapt to the changes of merging regions for successfully detecting objects scattered globally in a post-earthquake image. In the new descriptor, the spectral similarity and spatial similarity of any two adjacent regions are automatically combined to measure their similarity. Accordingly, the new descriptor offers adaptive semantic descriptions for geo-objects and thus is capable of characterizing different damage objects. Besides, in the dynamic region merging strategy, the adaptive spectral-spatial descriptor is embedded in the defined testing order and combined with graph models to construct a dynamic merging strategy. The new strategy can find the global optimal merging order and ensures that the most similar regions are merged at first. With combination of the two strategies, ADRM can identify spatially scattered objects and alleviates the phenomenon of over-segmentation and under-segmentation. The performance of ADRM has been evaluated by comparing with four state-of-the-art segmentation methods

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.

Segmentation-DrivenTomographic Reconstruction

DEFF Research Database (Denmark)

Kongskov, Rasmus Dalgas

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

Design of large size segmented GEM foils and Drift PCB for CBM MUCH

International Nuclear Information System (INIS)

Saini, J.; Dubey, A.K.; Chattopadhyay, S.

2016-01-01

Triple GEM (Gas Electron Multiplier), sector shaped detectors will be used for Muon tracking in the Compressed Baryonic Matter (CBM) experiment at Anti-proton Ion Research (FAIR) facility at Darmstadt, Germany. The sizes of the detectors modules in the Muon Chambers (MUCH) are of the order of 1 meter with active area of about 75cms. Progressive pad geometry is chosen for the readout from these detectors. In construction of these chambers, three GEM foils are stacked on top of each other in a 3/2/2/2 gap configuration. The GEM foils are double layered copper clad 50μm thin Kapton foil. Each GEM foil has millions of holes on it. Foils of large surface area are prone to damages due to discharges owing to the high capacitance of the foil. Hence, these foils have their top surfaces divided into segments of about 100 sq.cm. Further segmentation may be necessary when there are high rate requirements, as in the case of CBM. For the GEM foils of CBM MUCH, a 24 segment layout has been adopted. Short-circuit in any of the GEM-holes will make entire foil un-usable. To reduce such occurrences, segment to segment isolation using opto-coupler in series with the GEM-foil segments has been introduced. Hence, a novel design for GEM chamber drift-PCB and foils has been made. In this scheme, each segment is powered and controlled individually. At the same time, the design takes into account, the space constraints, not only in x-y plane, but also in the z, due to compact assembly of MUCH detector layers

Repair of segmental bone defect using Totally Vitalized tissue engineered bone graft by a combined perfusion seeding and culture system.

Directory of Open Access Journals (Sweden)

Lin Wang

Full Text Available BACKGROUND: The basic strategy to construct tissue engineered bone graft (TEBG is to combine osteoblastic cells with three dimensional (3D scaffold. Based on this strategy, we proposed the "Totally Vitalized TEBG" (TV-TEBG which was characterized by abundant and homogenously distributed cells with enhanced cell proliferation and differentiation and further investigated its biological performance in repairing segmental bone defect. METHODS: In this study, we constructed the TV-TEBG with the combination of customized flow perfusion seeding/culture system and β-tricalcium phosphate (β-TCP scaffold fabricated by Rapid Prototyping (RP technique. We systemically compared three kinds of TEBG constructed by perfusion seeding and perfusion culture (PSPC method, static seeding and perfusion culture (SSPC method, and static seeding and static culture (SSSC method for their in vitro performance and bone defect healing efficacy with a rabbit model. RESULTS: Our study has demonstrated that TEBG constructed by PSPC method exhibited better biological properties with higher daily D-glucose consumption, increased cell proliferation and differentiation, and better cell distribution, indicating the successful construction of TV-TEBG. After implanted into rabbit radius defects for 12 weeks, PSPC group exerted higher X-ray score close to autograft, much greater mechanical property evidenced by the biomechanical testing and significantly higher new bone formation as shown by histological analysis compared with the other two groups, and eventually obtained favorable healing efficacy of the segmental bone defect that was the closest to autograft transplantation. CONCLUSION: This study demonstrated the feasibility of TV-TEBG construction with combination of perfusion seeding, perfusion culture and RP technique which exerted excellent biological properties. The application of TV-TEBG may become a preferred candidate for segmental bone defect repair in orthopedic and

ℓ1/2-norm regularized nonnegative low-rank and sparse affinity graph for remote sensing image segmentation

Science.gov (United States)

Tian, Shu; Zhang, Ye; Yan, Yiming; Su, Nan

2016-10-01

Segmentation of real-world remote sensing images is a challenge due to the complex texture information with high heterogeneity. Thus, graph-based image segmentation methods have been attracting great attention in the field of remote sensing. However, most of the traditional graph-based approaches fail to capture the intrinsic structure of the feature space and are sensitive to noises. A ℓ-norm regularization-based graph segmentation method is proposed to segment remote sensing images. First, we use the occlusion of the random texture model (ORTM) to extract the local histogram features. Then, a ℓ-norm regularized low-rank and sparse representation (LNNLRS) is implemented to construct a ℓ-regularized nonnegative low-rank and sparse graph (LNNLRS-graph), by the union of feature subspaces. Moreover, the LNNLRS-graph has a high ability to discriminate the manifold intrinsic structure of highly homogeneous texture information. Meanwhile, the LNNLRS representation takes advantage of the low-rank and sparse characteristics to remove the noises and corrupted data. Last, we introduce the LNNLRS-graph into the graph regularization nonnegative matrix factorization to enhance the segmentation accuracy. The experimental results using remote sensing images show that when compared to five state-of-the-art image segmentation methods, the proposed method achieves more accurate segmentation results.

A Novel Plant Root Foraging Algorithm for Image Segmentation Problems

Directory of Open Access Journals (Sweden)

Lianbo Ma

2014-01-01

Full Text Available This paper presents a new type of biologically-inspired global optimization methodology for image segmentation based on plant root foraging behavior, namely, artificial root foraging algorithm (ARFO. The essential motive of ARFO is to imitate the significant characteristics of plant root foraging behavior including branching, regrowing, and tropisms for constructing a heuristic algorithm for multidimensional and multimodal problems. A mathematical model is firstly designed to abstract various plant root foraging patterns. Then, the basic process of ARFO algorithm derived in the model is described in details. When tested against ten benchmark functions, ARFO shows the superiority to other state-of-the-art algorithms on several benchmark functions. Further, we employed the ARFO algorithm to deal with multilevel threshold image segmentation problem. Experimental results of the new algorithm on a variety of images demonstrated the suitability of the proposed method for solving such problem.

Global multi-scale segmentation of continental and coastal waters from the watersheds to the continental margins

KAUST Repository

Laruelle, G. G.; Dü rr, H. H.; Lauerwald, R.; Hartmann, J.; Slomp, C. P.; Goossens, N.; Regnier, P. A. G.

2013-01-01

Past characterizations of the land-ocean continuum were constructed either from a continental perspective through an analysis of watershed river basin properties (COSCATs: COastal Segmentation and related CATchments) or from an oceanic perspective, through a regionalization of the proximal and distal continental margins (LMEs: large marine ecosystems). Here, we present a global-scale coastal segmentation, composed of three consistent levels, that includes the whole aquatic continuum with its riverine, estuarine and shelf sea components. Our work delineates comprehensive ensembles by harmonizing previous segmentations and typologies in order to retain the most important physical characteristics of both the land and shelf areas. The proposed multi-scale segmentation results in a distribution of global exorheic watersheds, estuaries and continental shelf seas among 45 major zones (MARCATS: MARgins and CATchments Segmentation) and 149 sub-units (COSCATs). Geographic and hydrologic parameters such as the surface area, volume and freshwater residence time are calculated for each coastal unit as well as different hypsometric profiles. Our analysis provides detailed insights into the distributions of coastal and continental shelf areas and how they connect with incoming riverine fluxes. The segmentation is also used to re-evaluate the global estuarine CO2 flux at the air-water interface combining global and regional average emission rates derived from local studies. © 2013 Author(s).

Global multi-scale segmentation of continental and coastal waters from the watersheds to the continental margins

Directory of Open Access Journals (Sweden)

G. G. Laruelle

2013-05-01

Full Text Available Past characterizations of the land–ocean continuum were constructed either from a continental perspective through an analysis of watershed river basin properties (COSCATs: COastal Segmentation and related CATchments or from an oceanic perspective, through a regionalization of the proximal and distal continental margins (LMEs: large marine ecosystems. Here, we present a global-scale coastal segmentation, composed of three consistent levels, that includes the whole aquatic continuum with its riverine, estuarine and shelf sea components. Our work delineates comprehensive ensembles by harmonizing previous segmentations and typologies in order to retain the most important physical characteristics of both the land and shelf areas. The proposed multi-scale segmentation results in a distribution of global exorheic watersheds, estuaries and continental shelf seas among 45 major zones (MARCATS: MARgins and CATchments Segmentation and 149 sub-units (COSCATs. Geographic and hydrologic parameters such as the surface area, volume and freshwater residence time are calculated for each coastal unit as well as different hypsometric profiles. Our analysis provides detailed insights into the distributions of coastal and continental shelf areas and how they connect with incoming riverine fluxes. The segmentation is also used to re-evaluate the global estuarine CO2 flux at the air–water interface combining global and regional average emission rates derived from local studies.

Global multi-scale segmentation of continental and coastal waters from the watersheds to the continental margins

KAUST Repository

Laruelle, G. G.

2012-10-04

Past characterizations of the land–ocean continuum were constructed either from a continental perspective through an analysis of watershed river basin properties (COSCATs: COastal Segmentation and related CATchments) or from an oceanic perspective, through a regionalization of the proximal and distal continental margins (LMEs: large marine ecosystems). Here, we present a global-scale coastal segmentation, composed of three consistent levels, that includes the whole aquatic continuum with its riverine, estuarine and shelf sea components. Our work delineates comprehensive ensembles by harmonizing previous segmentations and typologies in order to retain the most important physical characteristics of both the land and shelf areas. The proposed multi-scale segmentation results in a distribution of global exorheic watersheds, estuaries and continental shelf seas among 45 major zones (MARCATS: MARgins and CATchments Segmentation) and 149 sub-units (COSCATs). Geographic and hydrologic parameters such as the surface area, volume and freshwater residence time are calculated for each coastal unit as well as different hypsometric pro- files. Our analysis provides detailed insights into the distributions of coastal and continental shelf areas and how they connect with incoming riverine fluxes. The segmentation is also used to re-evaluate the global estuarine CO2 flux at the air–water interface combining global and regional average emission rates derived from local studies.

Global multi-scale segmentation of continental and coastal waters from the watersheds to the continental margins

KAUST Repository

Laruelle, G. G.

2013-05-29

Past characterizations of the land-ocean continuum were constructed either from a continental perspective through an analysis of watershed river basin properties (COSCATs: COastal Segmentation and related CATchments) or from an oceanic perspective, through a regionalization of the proximal and distal continental margins (LMEs: large marine ecosystems). Here, we present a global-scale coastal segmentation, composed of three consistent levels, that includes the whole aquatic continuum with its riverine, estuarine and shelf sea components. Our work delineates comprehensive ensembles by harmonizing previous segmentations and typologies in order to retain the most important physical characteristics of both the land and shelf areas. The proposed multi-scale segmentation results in a distribution of global exorheic watersheds, estuaries and continental shelf seas among 45 major zones (MARCATS: MARgins and CATchments Segmentation) and 149 sub-units (COSCATs). Geographic and hydrologic parameters such as the surface area, volume and freshwater residence time are calculated for each coastal unit as well as different hypsometric profiles. Our analysis provides detailed insights into the distributions of coastal and continental shelf areas and how they connect with incoming riverine fluxes. The segmentation is also used to re-evaluate the global estuarine CO2 flux at the air-water interface combining global and regional average emission rates derived from local studies. © 2013 Author(s).

Lung segment geometry study: simulation of largest possible tumours that fit into bronchopulmonary segments.

Science.gov (United States)

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

2012-03-01

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

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.)

Sipunculans and segmentation

DEFF Research Database (Denmark)

Wanninger, Andreas; Kristof, Alen; Brinkmann, Nora

2009-01-01

mechanisms may act on the level of gene expression, cell proliferation, tissue differentiation and organ system formation in individual segments. Accordingly, in some polychaete annelids the first three pairs of segmental peripheral neurons arise synchronously, while the metameric commissures of the ventral...

Development of segmented germanium detectors for neutrinoless double beta decay experiments

International Nuclear Information System (INIS)

Liu, Jing

2009-01-01

The results from neutrino oscillation experiments indicate that at least two neutrinos have mass. However, the value of the masses and whether neutrinos and anti-neutrinos are identical, i.e., Majorana particles, remain unknown. Neutrinoless double beta decay experiments can help to improve our understanding in both cases and are the only method currently possible to tackle the second question. The GERmanium Detector Array (GERDA) experiment, which will search for the neutrinoless double beta decay of 76 Ge, is currently under construction in Hall A of the INFN Gran Sasso National Laboratory (LNGS), Italy. In order to achieve an extremely low background level, segmented germanium detectors are considered to be operated directly in liquid argon which serves simultaneously as cooling and shielding medium. Several test cryostats were built at the Max-Planck-Institut fuer Physik in Muenchen to operate segmented germanium detectors both in vacuum and submerged in cryogenic liquid. The performance and the background discrimination power of segmented germanium detectors were studied in detail. It was proven for the first time that segmented germanium detectors can be operated stably over long periods submerged in a cryogenic liquid. It was confirmed that the segmentation scheme employed does well in the identification of photon induced background and demonstrated for the first time that also neutron interactions can be identified. The C++ Monte Carlo framework, MaGe (Majorana-GERDA), is a joint development of the Majorana and GERDA collaborations. It is based on GEANT4, but tailored especially to simulate the response of ultra-low background detectors to ionizing radiation. The predictions of the simulation were veri ed to be accurate for a wide range of conditions. Some shortcomings were found and corrected. Pulse shape analysis is complementary to segmentation in identifying background events. Its efficiency can only be correctly determined using reliable pulse shape

Development of segmented germanium detectors for neutrinoless double beta decay experiments

Energy Technology Data Exchange (ETDEWEB)

Liu, Jing

2009-06-09

The results from neutrino oscillation experiments indicate that at least two neutrinos have mass. However, the value of the masses and whether neutrinos and anti-neutrinos are identical, i.e., Majorana particles, remain unknown. Neutrinoless double beta decay experiments can help to improve our understanding in both cases and are the only method currently possible to tackle the second question. The GERmanium Detector Array (GERDA) experiment, which will search for the neutrinoless double beta decay of {sup 76}Ge, is currently under construction in Hall A of the INFN Gran Sasso National Laboratory (LNGS), Italy. In order to achieve an extremely low background level, segmented germanium detectors are considered to be operated directly in liquid argon which serves simultaneously as cooling and shielding medium. Several test cryostats were built at the Max-Planck-Institut fuer Physik in Muenchen to operate segmented germanium detectors both in vacuum and submerged in cryogenic liquid. The performance and the background discrimination power of segmented germanium detectors were studied in detail. It was proven for the first time that segmented germanium detectors can be operated stably over long periods submerged in a cryogenic liquid. It was confirmed that the segmentation scheme employed does well in the identification of photon induced background and demonstrated for the first time that also neutron interactions can be identified. The C++ Monte Carlo framework, MaGe (Majorana-GERDA), is a joint development of the Majorana and GERDA collaborations. It is based on GEANT4, but tailored especially to simulate the response of ultra-low background detectors to ionizing radiation. The predictions of the simulation were veri ed to be accurate for a wide range of conditions. Some shortcomings were found and corrected. Pulse shape analysis is complementary to segmentation in identifying background events. Its efficiency can only be correctly determined using reliable pulse

Using Predictability for Lexical Segmentation.

Science.gov (United States)

Çöltekin, Çağrı

2017-09-01

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

Efficient graph-cut tattoo segmentation

Science.gov (United States)

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

2015-03-01

Law enforcement is interested in exploiting tattoos as an information source to identify, track and prevent gang-related crimes. Many tattoo image retrieval systems have been described. In a retrieval system tattoo segmentation is an important step for retrieval accuracy since segmentation removes background information in a tattoo image. Existing segmentation methods do not extract the tattoo very well when the background includes textures and color similar to skin tones. In this paper we describe a tattoo segmentation approach by determining skin pixels in regions near the tattoo. In these regions graph-cut segmentation using a skin color model and a visual saliency map is used to find skin pixels. After segmentation we determine which set of skin pixels are connected with each other that form a closed contour including a tattoo. The regions surrounded by the closed contours are considered tattoo regions. Our method segments tattoos well when the background includes textures and color similar to skin.

3D 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

Communication: Proton NMR dipolar-correlation effect as a method for investigating segmental diffusion in polymer melts

International Nuclear Information System (INIS)

Lozovoi, A.; Mattea, C.; Stapf, S.; Herrmann, A.; Rössler, E. A.; Fatkullin, N.

2016-01-01

A simple and fast method for the investigation of segmental diffusion in high molar mass polymer melts is presented. The method is based on a special function, called proton dipolar-correlation build-up function, which is constructed from Hahn Echo signals measured at times t and t/2. The initial rise of this function contains additive contributions from both inter- and intramolecular magnetic dipole-dipole interactions. The intermolecular contribution depends on the relative mean squared displacements (MSDs) of polymer segments from different macromolecules, while the intramolecular part reflects segmental reorientations. Separation of both contributions via isotope dilution provides access to segmental displacements in polymer melts at millisecond range, which is hardly accessible by other methods. The feasibility of the method is illustrated by investigating protonated and deuterated polybutadiene melts with molecular mass 196 000 g/mol at different temperatures. The observed exponent of the power law of the segmental MSD is close to 0.32 ± 0.03 at times when the root MSD is in between 45 Å and 75 Å, and the intermolecular proton dipole-dipole contribution to the total proton Hahn Echo NMR signal is larger than 50% and increases with time.

Fold distributions at clover, crystal and segment levels for segmented clover detectors

International Nuclear Information System (INIS)

Kshetri, R; Bhattacharya, P

2014-01-01

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

Intercalary bone segment transport in treatment of segmental tibial defects

International Nuclear Information System (INIS)

Iqbal, A.; Amin, M.S.

2002-01-01

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

Detection and correction of false segmental duplications caused by genome mis-assembly

Science.gov (United States)

2010-01-01

Diploid genomes with divergent chromosomes present special problems for assembly software as two copies of especially polymorphic regions may be mistakenly constructed, creating the appearance of a recent segmental duplication. We developed a method for identifying such false duplications and applied it to four vertebrate genomes. For each genome, we corrected mis-assemblies, improved estimates of the amount of duplicated sequence, and recovered polymorphisms between the sequenced chromosomes. PMID:20219098

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...

A Higher-Order Neural Network Design for Improving Segmentation Performance in Medical Image Series

International Nuclear Information System (INIS)

Selvi, Eşref; Selver, M Alper; Güzeliş, Cüneyt; Dicle, Oǧuz

2014-01-01

Segmentation of anatomical structures from medical image series is an ongoing field of research. Although, organs of interest are three-dimensional in nature, slice-by-slice approaches are widely used in clinical applications because of their ease of integration with the current manual segmentation scheme. To be able to use slice-by-slice techniques effectively, adjacent slice information, which represents likelihood of a region to be the structure of interest, plays critical role. Recent studies focus on using distance transform directly as a feature or to increase the feature values at the vicinity of the search area. This study presents a novel approach by constructing a higher order neural network, the input layer of which receives features together with their multiplications with the distance transform. This allows higher-order interactions between features through the non-linearity introduced by the multiplication. The application of the proposed method to 9 CT datasets for segmentation of the liver shows higher performance than well-known higher order classification neural networks

Noise destroys feedback enhanced figure-ground segmentation but not feedforward figure-ground segmentation

Science.gov (United States)

Romeo, August; Arall, Marina; Supèr, Hans

2012-01-01

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

High-Resolution Isotropic Three-Dimensional MR Imaging of the Extraforaminal Segments of the Cranial Nerves.

Science.gov (United States)

Wen, Jessica; Desai, Naman S; Jeffery, Dean; Aygun, Nafi; Blitz, Ari

2018-02-01

High-resolution isotropic 3-dimensional (D) MR imaging with and without contrast is now routinely used for imaging evaluation of cranial nerve anatomy and pathologic conditions. The anatomic details of the extraforaminal segments are well-visualized on these techniques. A wide range of pathologic entities may cause enhancement or displacement of the nerve, which is now visible to an extent not available on standard 2D imaging. This article highlights the anatomy of extraforaminal segments of the cranial nerves and uses select cases to illustrate the utility and power of these sequences, with a focus on constructive interference in steady-state. Copyright © 2017 Elsevier Inc. All rights reserved.

ADVANCED CLUSTER BASED IMAGE SEGMENTATION

Directory of Open Access Journals (Sweden)

D. Kesavaraja

2011-11-01

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

Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods

Energy Technology Data Exchange (ETDEWEB)

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

2012-03-15

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

Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods

International Nuclear Information System (INIS)

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

2012-01-01

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

Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods.

Science.gov (United States)

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

2012-03-01

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

Blood vessel-based liver segmentation through the portal phase of a CT dataset

Science.gov (United States)

Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Moriyama, Noriyuki; Utsunomiya, Toru; Shimada, Mitsuo

2013-02-01

Blood vessels are dispersed throughout the human body organs and carry unique information for each person. This information can be used to delineate organ boundaries. The proposed method relies on abdominal blood vessels (ABV) to segment the liver considering the potential presence of tumors through the portal phase of a CT dataset. ABV are extracted and classified into hepatic (HBV) and nonhepatic (non-HBV) with a small number of interactions. HBV and non-HBV are used to guide an automatic segmentation of the liver. HBV are used to individually segment the core region of the liver. This region and non-HBV are used to construct a boundary surface between the liver and other organs to separate them. The core region is classified based on extracted posterior distributions of its histogram into low intensity tumor (LIT) and non-LIT core regions. Non-LIT case includes normal part of liver, HBV, and high intensity tumors if exist. Each core region is extended based on its corresponding posterior distribution. Extension is completed when it reaches either a variation in intensity or the constructed boundary surface. The method was applied to 80 datasets (30 Medical Image Computing and Computer Assisted Intervention (MICCAI) and 50 non-MICCAI data) including 60 datasets with tumors. Our results for the MICCAI-test data were evaluated by sliver07 [1] with an overall score of 79.7, which ranks seventh best on the site (December 2013). This approach seems a promising method for extraction of liver volumetry of various shapes and sizes and low intensity hepatic tumors.

Cluster Ensemble-Based Image Segmentation

Directory of Open Access Journals (Sweden)

Xiaoru Wang

2013-07-01

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

Albedo estimation for scene segmentation

Energy Technology Data Exchange (ETDEWEB)

Lee, C H; Rosenfeld, A

1983-03-01

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

Segmenting the Adult Education Market.

Science.gov (United States)

Aurand, Tim

1994-01-01

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

Gamifying Video Object Segmentation.

Science.gov (United States)

Spampinato, Concetto; Palazzo, Simone; Giordano, Daniela

2017-10-01

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

Consequential Constructions in Contemporary European Portuguese: A Contribution

Directory of Open Access Journals (Sweden)

Ana Cristina Macário Lopes

2016-11-01

Full Text Available The aim of this study is to provide an integrated description of consequential constructions in European contemporary Portuguese, relating their syntactic, semantic and pragmatic behavior. It will be argued that the discourse segment introduced by the connectives 'consequentemente', 'de forma que', 'daí' '(que', 'de modo que', 'por isso', 'assim' can be analyzed in terms of a supplement (Huddleston & Pullum 2002, not syntactically integrated with its anchor, but semantically related to it. Semantically, consequential constructions may be paraphrased by causal ones involving an adverbial subordinate clause. But, unlike causal constructions, consequential ones connect two distinct speech acts. The suppression of the consequential connective may trigger two different readings, but it will be argued that, for pragmatic reasons (Levinson 2000, the preferential reading is still the consequential one.

U.S. Army Custom Segmentation System

Science.gov (United States)

2007-06-01

segmentation is individual or intergroup differences in response to marketing - mix variables. Presumptions about segments: •different demands in a...product or service category, •respond differently to changes in the marketing mix Criteria for segments: •The segments must exist in the environment

Poly(ether amide) segmented block copolymers with adipicacid based tetra amide segments

NARCIS (Netherlands)

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

2007-01-01

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

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.

Cerebrovascular plaque segmentation using object class uncertainty snake in MR images

Science.gov (United States)

Das, Bipul; Saha, Punam K.; Wolf, Ronald; Song, Hee Kwon; Wright, Alexander C.; Wehrli, Felix W.

2005-04-01

Atherosclerotic cerebrovascular disease leads to formation of lipid-laden plaques that can form emboli when ruptured causing blockage to cerebral vessels. The clinical manifestation of this event sequence is stroke; a leading cause of disability and death. In vivo MR imaging provides detailed image of vascular architecture for the carotid artery making it suitable for analysis of morphological features. Assessing the status of carotid arteries that supplies blood to the brain is of primary interest to such investigations. Reproducible quantification of carotid artery dimensions in MR images is essential for plaque analysis. Manual segmentation being the only method presently makes it time consuming and sensitive to inter and intra observer variability. This paper presents a deformable model for lumen and vessel wall segmentation of carotid artery from MR images. The major challenges of carotid artery segmentation are (a) low signal-to-noise ratio, (b) background intensity inhomogeneity and (c) indistinct inner and/or outer vessel wall. We propose a new, effective object-class uncertainty based deformable model with additional features tailored toward this specific application. Object-class uncertainty optimally utilizes MR intensity characteristics of various anatomic entities that enable the snake to avert leakage through fuzzy boundaries. To strengthen the deformable model for this application, some other properties are attributed to it in the form of (1) fully arc-based deformation using a Gaussian model to maximally exploit vessel wall smoothness, (2) construction of a forbidden region for outer-wall segmentation to reduce interferences by prominent lumen features and (3) arc-based landmark for efficient user interaction. The algorithm has been tested upon T1- and PD- weighted images. Measures of lumen area and vessel wall area are computed from segmented data of 10 patient MR images and their accuracy and reproducibility are examined. These results correspond

Market Segmentation for Information Services.

Science.gov (United States)

Halperin, Michael

1981-01-01

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

Probabilistic Segmentation of Folk Music Recordings

Directory of Open Access Journals (Sweden)

Ciril Bohak

2016-01-01

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

Automated medical image segmentation techniques

Directory of Open Access Journals (Sweden)

Sharma Neeraj

2010-01-01

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

Prognostic validation of a 17-segment score derived from a 20-segment score for myocardial perfusion SPECT interpretation.

Science.gov (United States)

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

2004-01-01

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

NUCLEAR SEGMENTATION IN MICROSCOPE CELL IMAGES: A HAND-SEGMENTED DATASET AND COMPARISON OF ALGORITHMS

OpenAIRE

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

2009-01-01

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

Generalized pixel profiling and comparative segmentation with application to arteriovenous malformation segmentation.

Science.gov (United States)

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

2012-07-01

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

Robust shape regression for supervised vessel segmentation and its application to coronary segmentation in CTA

DEFF Research Database (Denmark)

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

2011-01-01

This paper presents a vessel segmentation method which learns the geometry and appearance of vessels in medical images from annotated data and uses this knowledge to segment vessels in unseen images. Vessels are segmented in a coarse-to-fine fashion. First, the vessel boundaries are estimated...

Engineering of multi-segmented light tunnel and flattop focus with designed axial lengths and gaps

Science.gov (United States)

Yu, Yanzhong; Huang, Han; Zhou, Mianmian; Zhan, Qiwen

2018-01-01

Based on the radiation pattern from a sectional-uniform line source antenna, a three-dimensional (3D) focus engineering technique for the creation of multi-segmented light tunnel and flattop focus with designed axial lengths and gaps is proposed. Under a 4Pi focusing system, the fields radiated from sectional-uniform magnetic and electromagnetic current line source antennas are employed to generate multi-segmented optical tube and flattop focus, respectively. Numerical results demonstrate that the produced light tube and flattop focus remain homogeneous along the optical axis; and their lengths of the nth segment and the nth gap between consecutive segments can be easily adjusted and only depend on the sizes of the nth section and the nth blanking between adjacent sectional antennas. The optical tube is a pure azimuthally polarized field but for the flattop focus the longitudinal polarization is dominant on the optical axis. To obtain the required pupil plane illumination for constructing the above focal field with prescribed characteristics, the inverse problem of the antenna radiation field is solved. These peculiar focusing fields might find potential applications in multi-particle acceleration, multi-particle trapping and manipulation.

A higher-order tensor vessel tractography for segmentation of vascular structures.

Science.gov (United States)

Cetin, Suheyla; Unal, Gozde

2015-10-01

A new vascular structure segmentation method, which is based on a cylindrical flux-based higher order tensor (HOT), is presented. On a vessel structure, the HOT naturally models branching points, which create challenges for vessel segmentation algorithms. In a general linear HOT model embedded in 3D, one has to work with an even order tensor due to an enforced antipodal-symmetry on the unit sphere. However, in scenarios such as in a bifurcation, the antipodally-symmetric tensor embedded in 3D will not be useful. In order to overcome that limitation, we embed the tensor in 4D and obtain a structure that can model asymmetric junction scenarios. During construction of a higher order tensor (e.g. third or fourth order) in 4D, the orientation vectors lie on the unit 3-sphere, in contrast to the unit 2-sphere in 3D tensor modeling. This 4D tensor is exploited in a seed-based vessel segmentation algorithm, where the principal directions of the 4D HOT is obtained by decomposition, and used in a HOT tractography approach. We demonstrate quantitative validation of the proposed algorithm on both synthetic complex tubular structures as well as real cerebral vasculature in Magnetic Resonance Angiography (MRA) datasets and coronary arteries from Computed Tomography Angiography (CTA) volumes.

Structure-properties relationships of novel poly(carbonate-co-amide) segmented copolymers with polyamide-6 as hard segments and polycarbonate as soft segments

Science.gov (United States)

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

2018-04-01

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

Segmentation and informality in Vietnam : a survey of the literature: country case study on labour market segmentation

OpenAIRE

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

2014-01-01

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

Segmentation by Large Scale Hypothesis Testing - Segmentation as Outlier Detection

DEFF Research Database (Denmark)

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

2010-01-01

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

Decomposing the Hounsfield unit: probabilistic segmentation of brain tissue in computed tomography.

Science.gov (United States)

Kemmling, A; Wersching, H; Berger, K; Knecht, S; Groden, C; Nölte, I

2012-03-01

The aim of this study was to present and evaluate a standardized technique for brain segmentation of cranial computed tomography (CT) using probabilistic partial volume tissue maps based on a database of high resolution T1 magnetic resonance images (MRI). Probabilistic tissue maps of white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) were derived from 600 normal brain MRIs (3.0 Tesla, T1-3D-turbo-field-echo) of 2 large community-based population studies (BiDirect and SEARCH Health studies). After partial tissue segmentation (FAST 4.0), MR images were linearly registered to MNI-152 standard space (FLIRT 5.5) with non-linear refinement (FNIRT 1.0) to obtain non-binary probabilistic volume images for each tissue class which were subsequently used for CT segmentation. From 150 normal cerebral CT scans a customized reference image in standard space was constructed with iterative non-linear registration to MNI-152 space. The inverse warp of tissue-specific probability maps to CT space (MNI-152 to individual CT) was used to decompose a CT image into tissue specific components (GM, WM, CSF). Potential benefits and utility of this novel approach with regard to unsupervised quantification of CT images and possible visual enhancement are addressed. Illustrative examples of tissue segmentation in different pathological cases including perfusion CT are presented. Automated tissue segmentation of cranial CT images using highly refined tissue probability maps derived from high resolution MR images is feasible. Potential applications include automated quantification of WM in leukoaraiosis, CSF in hydrocephalic patients, GM in neurodegeneration and ischemia and perfusion maps with separate assessment of GM and WM.

A three-dimensional image processing program for accurate, rapid, and semi-automated segmentation of neuronal somata with dense neurite outgrowth

Science.gov (United States)

Ross, James D.; Cullen, D. Kacy; Harris, James P.; LaPlaca, Michelle C.; DeWeerth, Stephen P.

2015-01-01

Three-dimensional (3-D) image analysis techniques provide a powerful means to rapidly and accurately assess complex morphological and functional interactions between neural cells. Current software-based identification methods of neural cells generally fall into two applications: (1) segmentation of cell nuclei in high-density constructs or (2) tracing of cell neurites in single cell investigations. We have developed novel methodologies to permit the systematic identification of populations of neuronal somata possessing rich morphological detail and dense neurite arborization throughout thick tissue or 3-D in vitro constructs. The image analysis incorporates several novel automated features for the discrimination of neurites and somata by initially classifying features in 2-D and merging these classifications into 3-D objects; the 3-D reconstructions automatically identify and adjust for over and under segmentation errors. Additionally, the platform provides for software-assisted error corrections to further minimize error. These features attain very accurate cell boundary identifications to handle a wide range of morphological complexities. We validated these tools using confocal z-stacks from thick 3-D neural constructs where neuronal somata had varying degrees of neurite arborization and complexity, achieving an accuracy of ≥95%. We demonstrated the robustness of these algorithms in a more complex arena through the automated segmentation of neural cells in ex vivo brain slices. These novel methods surpass previous techniques by improving the robustness and accuracy by: (1) the ability to process neurites and somata, (2) bidirectional segmentation correction, and (3) validation via software-assisted user input. This 3-D image analysis platform provides valuable tools for the unbiased analysis of neural tissue or tissue surrogates within a 3-D context, appropriate for the study of multi-dimensional cell-cell and cell-extracellular matrix interactions. PMID

Pavement management segment consolidation

Science.gov (United States)

1998-01-01

Dividing roads into "homogeneous" segments has been a major problem for all areas of highway engineering. SDDOT uses Deighton Associates Limited software, dTIMS, to analyze life-cycle costs for various rehabilitation strategies on each segment of roa...

Automatic segmentation of vertebrae from radiographs

DEFF Research Database (Denmark)

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

2011-01-01

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

Segmented detector for recoil neutrons in the p(γ, n)π+ reaction

International Nuclear Information System (INIS)

Korkmaz, E.; O'Rielly, G.V.; Hutcheon, D.A.; Feldman, G.; Jordan, D.; Kolb, N.R.; Pywell, R.E.; Retzlaff, G.A.; Sawatzky, B.D.; Skopik, D.M.; Vogt, J.M.; Cairns, E.; Giesen, U.; Holm, L.; Opper, A.K.; Rozon, F.M.; Soukup, J.

1999-01-01

A segmented neutron detector has been constructed and used for recoil neutron (6-13 MeV) measurements of the reaction γp→nπ + very close to threshold. BC-505 liquid scintillator was used to allow pulse shape discrimination between neutrons and photons. A measurement of the absolute efficiency of the detector was performed using stopped pions in the reaction π - p→nγ. Results of the efficiency calibration are compared to a Monte Carlo simulation. (author)

Impact of freeway weaving segment design on light-duty vehicle exhaust emissions.

Science.gov (United States)

Li, Qing; Qiao, Fengxiang; Yu, Lei; Chen, Shuyan; Li, Tiezhu

2018-06-01

data set as well as in the validation data set, with the R values of 0.91 and 0.90, respectively. Existing emission models usually rely on vehicle operation information to compute a generalized emission result, regardless of road configuration. In practice, while driving through a weaving segment, drivers are inclined to perform erratic maneuvers, such as hard braking and hard acceleration due to the complex weaving maneuver required. As a result, the exhaust emissions within a weaving segment vary from those on a basic segment. This research proposes to involve road configuration, in terms of the type and length of a weaving segment, in constructing an emission nonlinear model, which significantly improves emission estimations at a microscopic level.

A Hierarchical Building Segmentation in Digital Surface Models for 3D Reconstruction

Directory of Open Access Journals (Sweden)

Yiming Yan

2017-01-01

Full Text Available In this study, a hierarchical method for segmenting buildings in a digital surface model (DSM, which is used in a novel framework for 3D reconstruction, is proposed. Most 3D reconstructions of buildings are model-based. However, the limitations of these methods are overreliance on completeness of the offline-constructed models of buildings, and the completeness is not easily guaranteed since in modern cities buildings can be of a variety of types. Therefore, a model-free framework using high precision DSM and texture-images buildings was introduced. There are two key problems with this framework. The first one is how to accurately extract the buildings from the DSM. Most segmentation methods are limited by either the terrain factors or the difficult choice of parameter-settings. A level-set method are employed to roughly find the building regions in the DSM, and then a recently proposed ‘occlusions of random textures model’ are used to enhance the local segmentation of the buildings. The second problem is how to generate the facades of buildings. Synergizing with the corresponding texture-images, we propose a roof-contour guided interpolation of building facades. The 3D reconstruction results achieved by airborne-like images and satellites are compared. Experiments show that the segmentation method has good performance, and 3D reconstruction is easily performed by our framework, and better visualization results can be obtained by airborne-like images, which can be further replaced by UAV images.

A combined segmenting and non-segmenting approach to signal quality estimation for ambulatory photoplethysmography

International Nuclear Information System (INIS)

Wander, J D; Morris, D

2014-01-01

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

Rhythm-based segmentation of Popular Chinese Music

DEFF Research Database (Denmark)

Jensen, Karl Kristoffer

2005-01-01

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

Unsupervised Performance Evaluation of Image Segmentation

Directory of Open Access Journals (Sweden)

Chabrier Sebastien

2006-01-01

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

Methods of evaluating segmentation characteristics and segmentation of major faults

Energy Technology Data Exchange (ETDEWEB)

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

2000-03-15

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

Methods of evaluating segmentation characteristics and segmentation of major faults

International Nuclear Information System (INIS)

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

2000-03-01

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

A new framework for interactive images segmentation

International Nuclear Information System (INIS)

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

2017-01-01

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

Characterizing system dynamics with a weighted and directed network constructed from time series data

International Nuclear Information System (INIS)

Sun, Xiaoran; Small, Michael; Zhao, Yi; Xue, Xiaoping

2014-01-01

In this work, we propose a novel method to transform a time series into a weighted and directed network. For a given time series, we first generate a set of segments via a sliding window, and then use a doubly symbolic scheme to characterize every windowed segment by combining absolute amplitude information with an ordinal pattern characterization. Based on this construction, a network can be directly constructed from the given time series: segments corresponding to different symbol-pairs are mapped to network nodes and the temporal succession between nodes is represented by directed links. With this conversion, dynamics underlying the time series has been encoded into the network structure. We illustrate the potential of our networks with a well-studied dynamical model as a benchmark example. Results show that network measures for characterizing global properties can detect the dynamical transitions in the underlying system. Moreover, we employ a random walk algorithm to sample loops in our networks, and find that time series with different dynamics exhibits distinct cycle structure. That is, the relative prevalence of loops with different lengths can be used to identify the underlying dynamics

Characterizing system dynamics with a weighted and directed network constructed from time series data

Energy Technology Data Exchange (ETDEWEB)

Sun, Xiaoran, E-mail: sxr0806@gmail.com [Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055 (China); School of Mathematics and Statistics, The University of Western Australia, Crawley WA 6009 (Australia); Small, Michael, E-mail: michael.small@uwa.edu.au [School of Mathematics and Statistics, The University of Western Australia, Crawley WA 6009 (Australia); Zhao, Yi [Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055 (China); Xue, Xiaoping [Department of Mathematics, Harbin Institute of Technology, Harbin 150025 (China)

2014-06-15

In this work, we propose a novel method to transform a time series into a weighted and directed network. For a given time series, we first generate a set of segments via a sliding window, and then use a doubly symbolic scheme to characterize every windowed segment by combining absolute amplitude information with an ordinal pattern characterization. Based on this construction, a network can be directly constructed from the given time series: segments corresponding to different symbol-pairs are mapped to network nodes and the temporal succession between nodes is represented by directed links. With this conversion, dynamics underlying the time series has been encoded into the network structure. We illustrate the potential of our networks with a well-studied dynamical model as a benchmark example. Results show that network measures for characterizing global properties can detect the dynamical transitions in the underlying system. Moreover, we employ a random walk algorithm to sample loops in our networks, and find that time series with different dynamics exhibits distinct cycle structure. That is, the relative prevalence of loops with different lengths can be used to identify the underlying dynamics.

Performance of an open-source heart sound segmentation algorithm on eight independent databases.

Science.gov (United States)

Liu, Chengyu; Springer, David; Clifford, Gari D

2017-08-01

Heart sound segmentation is a prerequisite step for the automatic analysis of heart sound signals, facilitating the subsequent identification and classification of pathological events. Recently, hidden Markov model-based algorithms have received increased interest due to their robustness in processing noisy recordings. In this study we aim to evaluate the performance of the recently published logistic regression based hidden semi-Markov model (HSMM) heart sound segmentation method, by using a wider variety of independently acquired data of varying quality. Firstly, we constructed a systematic evaluation scheme based on a new collection of heart sound databases, which we assembled for the PhysioNet/CinC Challenge 2016. This collection includes a total of more than 120 000 s of heart sounds recorded from 1297 subjects (including both healthy subjects and cardiovascular patients) and comprises eight independent heart sound databases sourced from multiple independent research groups around the world. Then, the HSMM-based segmentation method was evaluated using the assembled eight databases. The common evaluation metrics of sensitivity, specificity, accuracy, as well as the [Formula: see text] measure were used. In addition, the effect of varying the tolerance window for determining a correct segmentation was evaluated. The results confirm the high accuracy of the HSMM-based algorithm on a separate test dataset comprised of 102 306 heart sounds. An average [Formula: see text] score of 98.5% for segmenting S1 and systole intervals and 97.2% for segmenting S2 and diastole intervals were observed. The [Formula: see text] score was shown to increases with an increases in the tolerance window size, as expected. The high segmentation accuracy of the HSMM-based algorithm on a large database confirmed the algorithm's effectiveness. The described evaluation framework, combined with the largest collection of open access heart sound data, provides essential resources for

Improvement of field matching in segmented-field electron conformal therapy using a variable-SCD applicator

Energy Technology Data Exchange (ETDEWEB)

Richert, John D [Department of Physics and Astronomy, Louisiana State University, 202 Nicholson Hall, Baton Rouge, LA 70803-4001 (United States); Hogstrom, Kenneth R [Department of Physics and Astronomy, Louisiana State University, 202 Nicholson Hall, Baton Rouge, LA 70803-4001 (United States); Fields, Robert S [Mary Bird Perkins Cancer Center, 4950 Essen Lane, Baton Rouge, LA 70809-3482 (United States); II, Kenneth L Matthews [Department of Physics and Astronomy, Louisiana State University, 202 Nicholson Hall, Baton Rouge, LA 70803-4001 (United States); Boyd, Robert A [Department of Physics and Astronomy, Louisiana State University, 202 Nicholson Hall, Baton Rouge, LA 70803-4001 (United States)

2007-05-07

The purpose of the present study is to demonstrate that the use of an electron applicator with energy-dependent source-to-collimator distances (SCDs) will significantly improve the dose homogeneity for abutted electron fields in segmented-field electron conformal therapy (ECT). Multiple Coulomb scattering theory was used to calculate and study the P{sub 80-20} penumbra width of off-axis dose profiles as a function of air gap and depth. Collimating insert locations with air gaps (collimator-to-isocenter distance) of 5.0, 7.5, 11.5, 17.5 and 19.5 cm were selected to provide equal P{sub 80-20} at a depth of 1.5 cm in water for energies of 6, 9, 12, 16 and 20 MeV, respectively, for a Varian 2100EX radiation therapy accelerator. A 15 x 15 cm{sup 2} applicator was modified accordingly, and collimating inserts used in the variable-SCD applicator for segmented-field ECT were constructed with diverging edges using a computer-controlled hot-wire cutter, which resulted in 0.27 mm accuracy in the abutted edges. The resulting electron beams were commissioned for the pencil-beam algorithm (PBA) on the Pinnacle{sup 3} treatment planning system. Four hypothetical planning target volumes (PTVs) and one patient were planned for segmented-field ECT using the new variable-SCD applicator, and the resulting dose distributions were compared with those calculated for the identical plans using the conventional 95 cm SCD applicator. Also, a method for quality assurance of segmented-field ECT dose plans using the variable-SCD applicator was evaluated by irradiating a polystyrene phantom using the treatment plans for the hypothetical PTVs. Treatment plans for all four of the hypothetical PTVs using the variable-SCD applicator showed significantly improved dose homogeneity in the abutment regions of the segmented-field ECT plans. This resulted in the dose spread (maximum dose-minimum dose), {sigma}, and D{sub 90-10} in the PTV being reduced by an average of 32%, 29% and 32%, respectively

Ergonomic lumbar risk analysis of construction workers by NIOSH method

Directory of Open Access Journals (Sweden)

Cinara Caetano Pereira

2015-09-01

Full Text Available Work in construction has tasks directly connected with manual transport. One of the body segments suffering greater demand in works with these characteristics is the lumbar spine segment. The aim of this study was to analyze the level of risk of lumbar construction workers in the shipment of materials. The sample was composed of 74 construction workers. Were used as a research tool: the NIOSH method for lumbar risk verification expressed by weight limit recommended (WPR and the lifting Index (IL, Visual analogue scale (VAS for the evaluation of pain intensity, the e-1 Corlett.0 for the mapping of the pain and Borg to the subjective perception of the intensity of physical exertion. The present study identified the weight limit (WP of 8.707 for management activity of bags of cement for the load of 8.194 wheelbarrows used. These findings are 6 times under actual weights handled during the activities that revolve around 50 kg with the sacks and averaged 49.72 kg stands with mass. The dimensional settings found in the search are at high risk for ergonomic lumbar region, and measures of reconfiguration of workplaces and operation of auxiliary devices for lifting, transporting and unloading are fundamental, in addition to the need for reflection about the current logistical problems that induce producers to supply the cement sacks with 50 kg.

International EUREKA: Initialization Segment

International Nuclear Information System (INIS)

1982-02-01

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

Image Segmentation Using Minimum Spanning Tree

Science.gov (United States)

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

2018-04-01

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

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.

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.

Brain Tumor Image Segmentation in MRI Image

Science.gov (United States)

Peni Agustin Tjahyaningtijas, Hapsari

2018-04-01

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

Colour application on mammography image segmentation

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

2017-09-01

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

What are Segments in Google Analytics

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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.

Segmentation-less Digital Rock Physics

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

2017-12-01

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

Abdominal multi-organ CT segmentation using organ correlation graph and prediction-based shape and location priors.

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Okada, Toshiyuki; Linguraru, Marius George; Hori, Masatoshi; Summers, Ronald M; Tomiyama, Noriyuki; Sato, Yoshinobu

2013-01-01

The paper addresses the automated segmentation of multiple organs in upper abdominal CT data. We propose a framework of multi-organ segmentation which is adaptable to any imaging conditions without using intensity information in manually traced training data. The features of the framework are as follows: (1) the organ correlation graph (OCG) is introduced, which encodes the spatial correlations among organs inherent in human anatomy; (2) the patient-specific organ shape and location priors obtained using OCG enable the estimation of intensity priors from only target data and optionally a number of untraced CT data of the same imaging condition as the target data. The proposed methods were evaluated through segmentation of eight abdominal organs (liver, spleen, left and right kidney, pancreas, gallbladder, aorta, and inferior vena cava) from 86 CT data obtained by four imaging conditions at two hospitals. The performance was comparable to the state-of-the-art method using intensity priors constructed from manually traced data.

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

Development and Implementation of a Corriedale Ovine Brain Atlas for Use in Atlas-Based Segmentation.

Directory of Open Access Journals (Sweden)

Kishan Andre Liyanage

Full Text Available Segmentation is the process of partitioning an image into subdivisions and can be applied to medical images to isolate anatomical or pathological areas for further analysis. This process can be done manually or automated by the use of image processing computer packages. Atlas-based segmentation automates this process by the use of a pre-labelled template and a registration algorithm. We developed an ovine brain atlas that can be used as a model for neurological conditions such as Parkinson's disease and focal epilepsy. 17 female Corriedale ovine brains were imaged in-vivo in a 1.5T (low-resolution MRI scanner. 13 of the low-resolution images were combined using a template construction algorithm to form a low-resolution template. The template was labelled to form an atlas and tested by comparing manual with atlas-based segmentations against the remaining four low-resolution images. The comparisons were in the form of similarity metrics used in previous segmentation research. Dice Similarity Coefficients were utilised to determine the degree of overlap between eight independent, manual and atlas-based segmentations, with values ranging from 0 (no overlap to 1 (complete overlap. For 7 of these 8 segmented areas, we achieved a Dice Similarity Coefficient of 0.5-0.8. The amygdala was difficult to segment due to its variable location and similar intensity to surrounding tissues resulting in Dice Coefficients of 0.0-0.2. We developed a low resolution ovine brain atlas with eight clinically relevant areas labelled. This brain atlas performed comparably to prior human atlases described in the literature and to intra-observer error providing an atlas that can be used to guide further research using ovine brains as a model and is hosted online for public access.

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

Local Competition-Based Superpixel Segmentation Algorithm in Remote Sensing.

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Liu, Jiayin; Tang, Zhenmin; Cui, Ying; Wu, Guoxing

2017-06-12

Remote sensing technologies have been widely applied in urban environments' monitoring, synthesis and modeling. Incorporating spatial information in perceptually coherent regions, superpixel-based approaches can effectively eliminate the "salt and pepper" phenomenon which is common in pixel-wise approaches. Compared with fixed-size windows, superpixels have adaptive sizes and shapes for different spatial structures. Moreover, superpixel-based algorithms can significantly improve computational efficiency owing to the greatly reduced number of image primitives. Hence, the superpixel algorithm, as a preprocessing technique, is more and more popularly used in remote sensing and many other fields. In this paper, we propose a superpixel segmentation algorithm called Superpixel Segmentation with Local Competition (SSLC), which utilizes a local competition mechanism to construct energy terms and label pixels. The local competition mechanism leads to energy terms locality and relativity, and thus, the proposed algorithm is less sensitive to the diversity of image content and scene layout. Consequently, SSLC could achieve consistent performance in different image regions. In addition, the Probability Density Function (PDF), which is estimated by Kernel Density Estimation (KDE) with the Gaussian kernel, is introduced to describe the color distribution of superpixels as a more sophisticated and accurate measure. To reduce computational complexity, a boundary optimization framework is introduced to only handle boundary pixels instead of the whole image. We conduct experiments to benchmark the proposed algorithm with the other state-of-the-art ones on the Berkeley Segmentation Dataset (BSD) and remote sensing images. Results demonstrate that the SSLC algorithm yields the best overall performance, while the computation time-efficiency is still competitive.

Failure of cervical arthroplasty in a patient with adjacent segment disease associated with Klippel-Feil syndrome

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Ioannis D Papanastassiou

2011-01-01

Full Text Available Cervical arthroplasty may be justified in patients with Klippel-Feil syndrome (KFS in order to preserve cervical motion. The aim of this paper is to report an arthroplasty failure in a patient with KFS. A 36-year-old woman with KFS underwent two-level arthroplasty for adjacent segment disc degeneration. Anterior migration of the cranial prosthesis was encountered 5 months postoperatively and was successfully revised with anterior cervical fusion. Cervical arthroplasty in an extensively stiff and fused neck is challenging and may lead to catastrophic failure. Although motion preservation is desirable in KFS, the special biomechanical features may hinder arthroplasty. Fusion or hybrid constructs may represent more reasonable options, especially when multiple fused segments are present.

Medical image segmentation by combining graph cuts and oriented active appearance models.

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Chen, Xinjian; Udupa, Jayaram K; Bagci, Ulas; Zhuge, Ying; Yao, Jianhua

2012-04-01

In this paper, we propose a novel method based on a strategic combination of the active appearance model (AAM), live wire (LW), and graph cuts (GCs) for abdominal 3-D organ segmentation. The proposed method consists of three main parts: model building, object recognition, and delineation. In the model building part, we construct the AAM and train the LW cost function and GC parameters. In the recognition part, a novel algorithm is proposed for improving the conventional AAM matching method, which effectively combines the AAM and LW methods, resulting in the oriented AAM (OAAM). A multiobject strategy is utilized to help in object initialization. We employ a pseudo-3-D initialization strategy and segment the organs slice by slice via a multiobject OAAM method. For the object delineation part, a 3-D shape-constrained GC method is proposed. The object shape generated from the initialization step is integrated into the GC cost computation, and an iterative GC-OAAM method is used for object delineation. The proposed method was tested in segmenting the liver, kidneys, and spleen on a clinical CT data set and also on the MICCAI 2007 Grand Challenge liver data set. The results show the following: 1) The overall segmentation accuracy of true positive volume fraction TPVF > 94.3% and false positive volume fraction can be achieved; 2) the initialization performance can be improved by combining the AAM and LW; 3) the multiobject strategy greatly facilitates initialization; 4) compared with the traditional 3-D AAM method, the pseudo-3-D OAAM method achieves comparable performance while running 12 times faster; and 5) the performance of the proposed method is comparable to state-of-the-art liver segmentation algorithm. The executable version of the 3-D shape-constrained GC method with a user interface can be downloaded from http://xinjianchen.wordpress.com/research/.

Track segment synthesis method for NTA film

International Nuclear Information System (INIS)

Kumazawa, Shigeru

1980-03-01

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

Segmental absence of intestinal musculature with metachronous bowel perforations in an infant

Directory of Open Access Journals (Sweden)

Noboru Oyachi

2018-03-01

Full Text Available Segmental absence of intestinal musculature is a rare condition. A female patient was born at 39 weeks gestational age with birth weight of 2,900 g. The patient was prenatally diagnosed as having segmental bowel distension in the fetal stage. She manifested bilious emesis with abdominal distension at day 1. Although excretion of viscous meconium was observed by gastrografin enema, gastrointestinal perforation developed. Emergency laparotomy and peritoneal drainage was required at that time and further laparotomy was performed on day 15. Multiple perforations were recognized discontinuously from the jejunum to the transverse colon, and jejunostomy was constructed. Additional bowel perforations occurred and re-exploration was required at day 43. We found newly formed small perforations in the proximal jejunum, ileum and the transverse colon and a tube jejunostomy and a colostomy were established. The patient required prolonged TPN management, which induced correlated cholestasis and liver failure, and died at day 143. Pathologic findings showed partial hypoplasia of the intrinsic muscle layer in the small intestine and diagnosed as segmental absence of intestinal musculature. Her disorder was unusual in its presentation, which included prenatal bowel dilatation, metachronous superimposed bowel perforation, and extensive discrete lesions from the jejunum to the transverse colon.

The roles of segmental and tandem gene duplication in the evolution of large gene families in Arabidopsis thaliana

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Baumgarten Andrew

2004-06-01

Full Text Available Abstract Background Most genes in Arabidopsis thaliana are members of gene families. How do the members of gene families arise, and how are gene family copy numbers maintained? Some gene families may evolve primarily through tandem duplication and high rates of birth and death in clusters, and others through infrequent polyploidy or large-scale segmental duplications and subsequent losses. Results Our approach to understanding the mechanisms of gene family evolution was to construct phylogenies for 50 large gene families in Arabidopsis thaliana, identify large internal segmental duplications in Arabidopsis, map gene duplications onto the segmental duplications, and use this information to identify which nodes in each phylogeny arose due to segmental or tandem duplication. Examples of six gene families exemplifying characteristic modes are described. Distributions of gene family sizes and patterns of duplication by genomic distance are also described in order to characterize patterns of local duplication and copy number for large gene families. Both gene family size and duplication by distance closely follow power-law distributions. Conclusions Combining information about genomic segmental duplications, gene family phylogenies, and gene positions provides a method to evaluate contributions of tandem duplication and segmental genome duplication in the generation and maintenance of gene families. These differences appear to correspond meaningfully to differences in functional roles of the members of the gene families.

Choroidal vasculature characteristics based choroid segmentation for enhanced depth imaging optical coherence tomography images

Energy Technology Data Exchange (ETDEWEB)

Chen, Qiang; Niu, Sijie [School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094 (China); Yuan, Songtao; Fan, Wen, E-mail: fanwen1029@163.com; Liu, Qinghuai [Department of Ophthalmology, The First Affiliated Hospital with Nanjing Medical University, Nanjing 210029 (China)

2016-04-15

Purpose: In clinical research, it is important to measure choroidal thickness when eyes are affected by various diseases. The main purpose is to automatically segment choroid for enhanced depth imaging optical coherence tomography (EDI-OCT) images with five B-scans averaging. Methods: The authors present an automated choroid segmentation method based on choroidal vasculature characteristics for EDI-OCT images with five B-scans averaging. By considering the large vascular of the Haller’s layer neighbor with the choroid-sclera junction (CSJ), the authors measured the intensity ascending distance and a maximum intensity image in the axial direction from a smoothed and normalized EDI-OCT image. Then, based on generated choroidal vessel image, the authors constructed the CSJ cost and constrain the CSJ search neighborhood. Finally, graph search with smooth constraints was utilized to obtain the CSJ boundary. Results: Experimental results with 49 images from 10 eyes in 8 normal persons and 270 images from 57 eyes in 44 patients with several stages of diabetic retinopathy and age-related macular degeneration demonstrate that the proposed method can accurately segment the choroid of EDI-OCT images with five B-scans averaging. The mean choroid thickness difference and overlap ratio between the authors’ proposed method and manual segmentation drawn by experts were −11.43 μm and 86.29%, respectively. Conclusions: Good performance was achieved for normal and pathologic eyes, which proves that the authors’ method is effective for the automated choroid segmentation of the EDI-OCT images with five B-scans averaging.

Choroidal vasculature characteristics based choroid segmentation for enhanced depth imaging optical coherence tomography images

International Nuclear Information System (INIS)

Chen, Qiang; Niu, Sijie; Yuan, Songtao; Fan, Wen; Liu, Qinghuai

2016-01-01

Purpose: In clinical research, it is important to measure choroidal thickness when eyes are affected by various diseases. The main purpose is to automatically segment choroid for enhanced depth imaging optical coherence tomography (EDI-OCT) images with five B-scans averaging. Methods: The authors present an automated choroid segmentation method based on choroidal vasculature characteristics for EDI-OCT images with five B-scans averaging. By considering the large vascular of the Haller’s layer neighbor with the choroid-sclera junction (CSJ), the authors measured the intensity ascending distance and a maximum intensity image in the axial direction from a smoothed and normalized EDI-OCT image. Then, based on generated choroidal vessel image, the authors constructed the CSJ cost and constrain the CSJ search neighborhood. Finally, graph search with smooth constraints was utilized to obtain the CSJ boundary. Results: Experimental results with 49 images from 10 eyes in 8 normal persons and 270 images from 57 eyes in 44 patients with several stages of diabetic retinopathy and age-related macular degeneration demonstrate that the proposed method can accurately segment the choroid of EDI-OCT images with five B-scans averaging. The mean choroid thickness difference and overlap ratio between the authors’ proposed method and manual segmentation drawn by experts were −11.43 μm and 86.29%, respectively. Conclusions: Good performance was achieved for normal and pathologic eyes, which proves that the authors’ method is effective for the automated choroid segmentation of the EDI-OCT images with five B-scans averaging.

LIFE-STYLE SEGMENTATION WITH TAILORED INTERVIEWING

NARCIS (Netherlands)

KAMAKURA, WA; WEDEL, M

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

Segmented rail linear induction motor

Science.gov (United States)

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

1996-01-01

A segmented rail linear induction motor has a segmented rail consisting of a plurality of nonferrous electrically conductive segments aligned along a guideway. The motor further includes a carriage including at least one pair of opposed coils fastened to the carriage for moving the carriage. A power source applies an electric current to the coils to induce currents in the conductive surfaces to repel the coils from adjacent edges of the conductive surfaces.

The use of the Kalman filter in the automated segmentation of EIT lung images

International Nuclear Information System (INIS)

Zifan, A; Chapman, B E; Liatsis, P

2013-01-01

In this paper, we present a new pipeline for the fast and accurate segmentation of impedance images of the lungs using electrical impedance tomography (EIT). EIT is an emerging, promising, non-invasive imaging modality that produces real-time, low spatial but high temporal resolution images of impedance inside a body. Recovering impedance itself constitutes a nonlinear ill-posed inverse problem, therefore the problem is usually linearized, which produces impedance-change images, rather than static impedance ones. Such images are highly blurry and fuzzy along object boundaries. We provide a mathematical reasoning behind the high suitability of the Kalman filter when it comes to segmenting and tracking conductivity changes in EIT lung images. Next, we use a two-fold approach to tackle the segmentation problem. First, we construct a global lung shape to restrict the search region of the Kalman filter. Next, we proceed with augmenting the Kalman filter by incorporating an adaptive foreground detection system to provide the boundary contours for the Kalman filter to carry out the tracking of the conductivity changes as the lungs undergo deformation in a respiratory cycle. The proposed method has been validated by using performance statistics such as misclassified area, and false positive rate, and compared to previous approaches. The results show that the proposed automated method can be a fast and reliable segmentation tool for EIT imaging. (paper)

The use of the Kalman filter in the automated segmentation of EIT lung images.

Science.gov (United States)

Zifan, A; Liatsis, P; Chapman, B E

2013-06-01

In this paper, we present a new pipeline for the fast and accurate segmentation of impedance images of the lungs using electrical impedance tomography (EIT). EIT is an emerging, promising, non-invasive imaging modality that produces real-time, low spatial but high temporal resolution images of impedance inside a body. Recovering impedance itself constitutes a nonlinear ill-posed inverse problem, therefore the problem is usually linearized, which produces impedance-change images, rather than static impedance ones. Such images are highly blurry and fuzzy along object boundaries. We provide a mathematical reasoning behind the high suitability of the Kalman filter when it comes to segmenting and tracking conductivity changes in EIT lung images. Next, we use a two-fold approach to tackle the segmentation problem. First, we construct a global lung shape to restrict the search region of the Kalman filter. Next, we proceed with augmenting the Kalman filter by incorporating an adaptive foreground detection system to provide the boundary contours for the Kalman filter to carry out the tracking of the conductivity changes as the lungs undergo deformation in a respiratory cycle. The proposed method has been validated by using performance statistics such as misclassified area, and false positive rate, and compared to previous approaches. The results show that the proposed automated method can be a fast and reliable segmentation tool for EIT imaging.

Deformable segmentation via sparse shape representation.

Science.gov (United States)

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

2011-01-01

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

Segmenting hospitals for improved management strategy.

Science.gov (United States)

Malhotra, N K

1989-09-01

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

Development of targeted messages to promote smoking cessation among construction trade workers

Science.gov (United States)

Strickland, J. R.; Smock, N.; Casey, C.; Poor, T.; Kreuter, M. W.; Evanoff, B. A.

2015-01-01

Blue-collar workers, particularly those in the construction trades, are more likely to smoke and have less success in quitting when compared with white-collar workers. Little is known about health communication strategies that might influence this priority population. This article describes our formative work to develop targeted messages to increase participation in an existing smoking cessation program among construction workers. Using an iterative and sequential mixed-methods approach, we explored the culture, health attitudes and smoking behaviors of unionized construction workers. We used focus group and survey data to inform message development, and applied audience segmentation methods to identify potential subgroups. Among 144 current smokers, 65% reported wanting to quit smoking in the next 6 months and only 15% had heard of a union-sponsored smoking cessation program, despite widespread advertising. We tested 12 message concepts and 26 images with the target audience to evaluate perceived relevance and effectiveness. Participants responded most favorably to messages and images that emphasized family and work, although responses varied by audience segments based on age and parental status. This study is an important step towards integrating the culture of a high-risk group into targeted messages to increase participation in smoking cessation activities. PMID:25231165

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.

Supervised variational model with statistical inference and its application in medical image segmentation.

Science.gov (United States)

Li, Changyang; Wang, Xiuying; Eberl, Stefan; Fulham, Michael; Yin, Yong; Dagan Feng, David

2015-01-01

Automated and general medical image segmentation can be challenging because the foreground and the background may have complicated and overlapping density distributions in medical imaging. Conventional region-based level set algorithms often assume piecewise constant or piecewise smooth for segments, which are implausible for general medical image segmentation. Furthermore, low contrast and noise make identification of the boundaries between foreground and background difficult for edge-based level set algorithms. Thus, to address these problems, we suggest a supervised variational level set segmentation model to harness the statistical region energy functional with a weighted probability approximation. Our approach models the region density distributions by using the mixture-of-mixtures Gaussian model to better approximate real intensity distributions and distinguish statistical intensity differences between foreground and background. The region-based statistical model in our algorithm can intuitively provide better performance on noisy images. We constructed a weighted probability map on graphs to incorporate spatial indications from user input with a contextual constraint based on the minimization of contextual graphs energy functional. We measured the performance of our approach on ten noisy synthetic images and 58 medical datasets with heterogeneous intensities and ill-defined boundaries and compared our technique to the Chan-Vese region-based level set model, the geodesic active contour model with distance regularization, and the random walker model. Our method consistently achieved the highest Dice similarity coefficient when compared to the other methods.

LIGHT-WEIGHT LOAD-BEARING STRUCTURES REINFORCED BY CORE ELEMENTS MADE OF SEGMENTS AND A METHOD OF CASTING SUCH STRUCTURES

DEFF Research Database (Denmark)

2009-01-01

The invention relates to a light-weight load-bearing structure, reinforced by core elements (2) of a strong material constituting one or more compression or tension zones in the structure to be cast, which core (2) is surrounded by or adjacent to a material of less strength compared to the core (2......), where the core (2) is constructed from segments (1) of core elements (2) assembled by means of one or more prestressing elements (4). The invention further relates to a method of casting of light-weight load-bearing structures, reinforced by core elements (2) of a strong material constituting one...... or more compression or tension zones in the structure to be cast, which core (2) is surrounded by or adjacent to a material of less strength compared to the core (2), where the core (2) is constructed from segments (1) of core elements (2) assembled and hold together by means of one or more prestressing...

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

A statistical method for lung tumor segmentation uncertainty in PET images based on user inference.

Science.gov (United States)

Zheng, Chaojie; Wang, Xiuying; Feng, Dagan

2015-01-01

PET has been widely accepted as an effective imaging modality for lung tumor diagnosis and treatment. However, standard criteria for delineating tumor boundary from PET are yet to develop largely due to relatively low quality of PET images, uncertain tumor boundary definition, and variety of tumor characteristics. In this paper, we propose a statistical solution to segmentation uncertainty on the basis of user inference. We firstly define the uncertainty segmentation band on the basis of segmentation probability map constructed from Random Walks (RW) algorithm; and then based on the extracted features of the user inference, we use Principle Component Analysis (PCA) to formulate the statistical model for labeling the uncertainty band. We validated our method on 10 lung PET-CT phantom studies from the public RIDER collections [1] and 16 clinical PET studies where tumors were manually delineated by two experienced radiologists. The methods were validated using Dice similarity coefficient (DSC) to measure the spatial volume overlap. Our method achieved an average DSC of 0.878 ± 0.078 on phantom studies and 0.835 ± 0.039 on clinical studies.

Unsupervised motion-based object segmentation refined by color

Science.gov (United States)

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

2003-06-01

For various applications, such as data compression, structure from motion, medical imaging and video enhancement, there is a need for an algorithm that divides video sequences into independently moving objects. Because our focus is on video enhancement and structure from motion for consumer electronics, we strive for a low complexity solution. For still images, several approaches exist based on colour, but these lack in both speed and segmentation quality. For instance, colour-based watershed algorithms produce a so-called oversegmentation with many segments covering each single physical object. Other colour segmentation approaches exist which somehow limit the number of segments to reduce this oversegmentation problem. However, this often results in inaccurate edges or even missed objects. Most likely, colour is an inherently insufficient cue for real world object segmentation, because real world objects can display complex combinations of colours. For video sequences, however, an additional cue is available, namely the motion of objects. When different objects in a scene have different motion, the motion cue alone is often enough to reliably distinguish objects from one another and the background. However, because of the lack of sufficient resolution of efficient motion estimators, like the 3DRS block matcher, the resulting segmentation is not at pixel resolution, but at block resolution. Existing pixel resolution motion estimators are more sensitive to noise, suffer more from aperture problems or have less correspondence to the true motion of objects when compared to block-based approaches or are too computationally expensive. From its tendency to oversegmentation it is apparent that colour segmentation is particularly effective near edges of homogeneously coloured areas. On the other hand, block-based true motion estimation is particularly effective in heterogeneous areas, because heterogeneous areas improve the chance a block is unique and thus decrease the

Market Segmentation from a Behavioral Perspective

Science.gov (United States)

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

2010-01-01

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

Skip segment Hirschsprung disease and Waardenburg syndrome

OpenAIRE

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

2015-01-01

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

Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach.

Science.gov (United States)

Beichel, Reinhard R; Van Tol, Markus; Ulrich, Ethan J; Bauer, Christian; Chang, Tangel; Plichta, Kristin A; Smith, Brian J; Sunderland, John J; Graham, Michael M; Sonka, Milan; Buatti, John M

2016-06-01

The purpose of this work was to develop, validate, and compare a highly computer-aided method for the segmentation of hot lesions in head and neck 18F-FDG PET scans. A semiautomated segmentation method was developed, which transforms the segmentation problem into a graph-based optimization problem. For this purpose, a graph structure around a user-provided approximate lesion centerpoint is constructed and a suitable cost function is derived based on local image statistics. To handle frequently occurring situations that are ambiguous (e.g., lesions adjacent to each other versus lesion with inhomogeneous uptake), several segmentation modes are introduced that adapt the behavior of the base algorithm accordingly. In addition, the authors present approaches for the efficient interactive local and global refinement of initial segmentations that are based on the "just-enough-interaction" principle. For method validation, 60 PET/CT scans from 59 different subjects with 230 head and neck lesions were utilized. All patients had squamous cell carcinoma of the head and neck. A detailed comparison with the current clinically relevant standard manual segmentation approach was performed based on 2760 segmentations produced by three experts. Segmentation accuracy measured by the Dice coefficient of the proposed semiautomated and standard manual segmentation approach was 0.766 and 0.764, respectively. This difference was not statistically significant (p = 0.2145). However, the intra- and interoperator standard deviations were significantly lower for the semiautomated method. In addition, the proposed method was found to be significantly faster and resulted in significantly higher intra- and interoperator segmentation agreement when compared to the manual segmentation approach. Lack of consistency in tumor definition is a critical barrier for radiation treatment targeting as well as for response assessment in clinical trials and in clinical oncology decision-making. The properties

Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach

Energy Technology Data Exchange (ETDEWEB)

Beichel, Reinhard R., E-mail: reinhard-beichel@uiowa.edu [Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa 52242 (United States); Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Department of Internal Medicine, University of Iowa, Iowa City, Iowa 52242 (United States); Van Tol, Markus; Ulrich, Ethan J.; Bauer, Christian [Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa 52242 (United States); Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242 (United States); Chang, Tangel; Plichta, Kristin A. [Department of Radiation Oncology, University of Iowa, Iowa City, Iowa 52242 (United States); Smith, Brian J. [Department of Biostatistics, University of Iowa, Iowa City, Iowa 52242 (United States); Sunderland, John J.; Graham, Michael M. [Department of Radiology, University of Iowa, Iowa City, Iowa 52242 (United States); Sonka, Milan [Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa 52242 (United States); Department of Radiation Oncology, The University of Iowa, Iowa City, Iowa 52242 (United States); Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Buatti, John M. [Department of Radiation Oncology, University of Iowa, Iowa City, Iowa 52242 (United States); Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States)

2016-06-15

Purpose: The purpose of this work was to develop, validate, and compare a highly computer-aided method for the segmentation of hot lesions in head and neck 18F-FDG PET scans. Methods: A semiautomated segmentation method was developed, which transforms the segmentation problem into a graph-based optimization problem. For this purpose, a graph structure around a user-provided approximate lesion centerpoint is constructed and a suitable cost function is derived based on local image statistics. To handle frequently occurring situations that are ambiguous (e.g., lesions adjacent to each other versus lesion with inhomogeneous uptake), several segmentation modes are introduced that adapt the behavior of the base algorithm accordingly. In addition, the authors present approaches for the efficient interactive local and global refinement of initial segmentations that are based on the “just-enough-interaction” principle. For method validation, 60 PET/CT scans from 59 different subjects with 230 head and neck lesions were utilized. All patients had squamous cell carcinoma of the head and neck. A detailed comparison with the current clinically relevant standard manual segmentation approach was performed based on 2760 segmentations produced by three experts. Results: Segmentation accuracy measured by the Dice coefficient of the proposed semiautomated and standard manual segmentation approach was 0.766 and 0.764, respectively. This difference was not statistically significant (p = 0.2145). However, the intra- and interoperator standard deviations were significantly lower for the semiautomated method. In addition, the proposed method was found to be significantly faster and resulted in significantly higher intra- and interoperator segmentation agreement when compared to the manual segmentation approach. Conclusions: Lack of consistency in tumor definition is a critical barrier for radiation treatment targeting as well as for response assessment in clinical trials and in

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.

Multi-scale Modelling of Segmentation

DEFF Research Database (Denmark)

Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri

2016-01-01

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

S-net : Construction of large scale seafloor observatory network for tsunamis and earthquakes along the Japan Trench

Science.gov (United States)

Mochizuki, M.; Uehira, K.; Kanazawa, T.; Shiomi, K.; Kunugi, T.; Aoi, S.; Matsumoto, T.; Sekiguchi, S.; Yamamoto, N.; Takahashi, N.; Nakamura, T.; Shinohara, M.; Yamada, T.

2017-12-01

NIED has launched the project of constructing a seafloor observatory network for tsunamis and earthquakes after the occurrence of the 2011 Tohoku Earthquake to enhance reliability of early warnings of tsunamis and earthquakes. The observatory network was named "S-net". The S-net project has been financially supported by MEXT.The S-net consists of 150 seafloor observatories which are connected in line with submarine optical cables. The total length of submarine optical cable is about 5,500 km. The S-net covers the focal region of the 2011 Tohoku Earthquake and its vicinity regions. Each observatory equips two units of a high sensitive pressure gauges as a tsunami meter and four sets of three-component seismometers. The S-net is composed of six segment networks. Five of six segment networks had been already installed. Installation of the last segment network covering the outer rise area have been finally finished by the end of FY2016. The outer rise segment has special features like no other five segments of the S-net. Those features are deep water and long distance. Most of 25 observatories on the outer rise segment are located at the depth of deeper than 6,000m WD. Especially, three observatories are set on the seafloor of deeper than about 7.000m WD, and then the pressure gauges capable of being used even at 8,000m WD are equipped on those three observatories. Total length of the submarine cables of the outer rise segment is about two times longer than those of the other segments. The longer the cable system is, the higher voltage supply is needed, and thus the observatories on the outer rise segment have high withstanding voltage characteristics. We employ a dispersion management line of a low loss formed by combining a plurality of optical fibers for the outer rise segment cable, in order to achieve long-distance, high-speed and large-capacity data transmission Installation of the outer rise segment was finished and then full-scale operation of S-net has started

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.

Segmentation-Based And Segmentation-Free Methods for Spotting Handwritten Arabic Words

OpenAIRE

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

2006-01-01

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

Monitoring fish distributions along electrofishing segments

Science.gov (United States)

Miranda, Leandro E.

2014-01-01

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

Juxta-Vascular Pulmonary Nodule Segmentation in PET-CT Imaging Based on an LBF Active Contour Model with Information Entropy and Joint Vector

Directory of Open Access Journals (Sweden)

Rui Hao

2018-01-01

Full Text Available The accurate segmentation of pulmonary nodules is an important preprocessing step in computer-aided diagnoses of lung cancers. However, the existing segmentation methods may cause the problem of edge leakage and cannot segment juxta-vascular pulmonary nodules accurately. To address this problem, a novel automatic segmentation method based on an LBF active contour model with information entropy and joint vector is proposed in this paper. Our method extracts the interest area of pulmonary nodules by a standard uptake value (SUV in Positron Emission Tomography (PET images, and automatic threshold iteration is used to construct an initial contour roughly. The SUV information entropy and the gray-value joint vector of Positron Emission Tomography–Computed Tomography (PET-CT images are calculated to drive the evolution of contour curve. At the edge of pulmonary nodules, evolution will be stopped and accurate results of pulmonary nodule segmentation can be obtained. Experimental results show that our method can achieve 92.35% average dice similarity coefficient, 2.19 mm Hausdorff distance, and 3.33% false positive with the manual segmentation results. Compared with the existing methods, our proposed method that segments juxta-vascular pulmonary nodules in PET-CT images is more accurate and efficient.

A numerical study on seismic response of self-centring precast segmental columns at different post-tensioning forces

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Ehsan Nikbakht

Full Text Available Precast bridge columns have shown increasing demand over the past few years due to the advantages of such columns when compared against conventional bridge columns, particularly due to the fact that precast bridge columns can be constructed off site and erected in a short period of time. The present study analytically investigates the behaviour of self-centring precast segmental bridge columns under nonlinear-static and pseudo-dynamic loading at different prestressing strand levels. Self-centring segmental columns are composed of prefabricated reinforced concrete segments which are connected by central post-tensioning (PT strands. The present study develops a three dimensional (3D nonlinear finite element model for hybrid post-tensioned precast segmental bridge columns. The model is subjected to constant axial loading and lateral reverse cyclic loading. The lateral force displacement results of the analysed columns show good agreement with the experimental response of the columns. Bonded post-tensioned segmental columns at 25%, 40% and 70% prestressing strand stress levels are analysed and compared with an emulative monolithic conventional column. The columns with a higher initial prestressing strand levels show greater initial stiffness and strength but show higher stiffness reduction at large drifts. In the time-history analysis, the column samples are subjected to different earthquake records to investigate the effect post-tensioning force levels on their lateral seismic response in low and higher seismicity zones. The results indicate that, for low seismicity zones, post-tensioned segmental columns with a higher initial stress level deflect lower lateral peak displacement. However, in higher seismicity zones, applying a high initial stress level should be avoided for precast segmental self-centring columns with low energy dissipation capacity.

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.

Discovery and fusion of salient multimodal features toward news story segmentation

Science.gov (United States)

Hsu, Winston; Chang, Shih-Fu; Huang, Chih-Wei; Kennedy, Lyndon; Lin, Ching-Yung; Iyengar, Giridharan

2003-12-01

In this paper, we present our new results in news video story segmentation and classification in the context of TRECVID video retrieval benchmarking event 2003. We applied and extended the Maximum Entropy statistical model to effectively fuse diverse features from multiple levels and modalities, including visual, audio, and text. We have included various features such as motion, face, music/speech types, prosody, and high-level text segmentation information. The statistical fusion model is used to automatically discover relevant features contributing to the detection of story boundaries. One novel aspect of our method is the use of a feature wrapper to address different types of features -- asynchronous, discrete, continuous and delta ones. We also developed several novel features related to prosody. Using the large news video set from the TRECVID 2003 benchmark, we demonstrate satisfactory performance (F1 measures up to 0.76 in ABC news and 0.73 in CNN news), present how these multi-level multi-modal features construct the probabilistic framework, and more importantly observe an interesting opportunity for further improvement.

Process Segmentation Typology in Czech Companies

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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.

Algorithms for Cytoplasm Segmentation of Fluorescence Labelled Cells

Directory of Open Access Journals (Sweden)

Carolina Wählby

2002-01-01

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

A large-acceptance Bragg curve spectrometer with a longitudinal electric field and a segmented anode

International Nuclear Information System (INIS)

Farrar, K.A.; Hasan, A.T.; Prosser, F.W.; Sanders, S.J.; Henderson, D.J.

1994-01-01

A large-acceptance Bragg curve spectrometer with a longitudinal electron collection field and a segmented anode has been constructed and tested. The effects on the charge resolution of the entrance angle and entrance position of the incident particle have been studied. Simulations have been done in order to isolate the contribution to the overall detector performance of the signal-shaping electronics from that of the intrinsic design of the detector. ((orig.))

Simulating Deformations of MR Brain Images for Validation of Atlas-based Segmentation and Registration Algorithms

OpenAIRE

Xue, Zhong; Shen, Dinggang; Karacali, Bilge; Stern, Joshua; Rottenberg, David; Davatzikos, Christos

2006-01-01

Simulated deformations and images can act as the gold standard for evaluating various template-based image segmentation and registration algorithms. Traditional deformable simulation methods, such as the use of analytic deformation fields or the displacement of landmarks followed by some form of interpolation, are often unable to construct rich (complex) and/or realistic deformations of anatomical organs. This paper presents new methods aiming to automatically simulate realistic inter- and in...

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

Local Competition-Based Superpixel Segmentation Algorithm in Remote Sensing

Directory of Open Access Journals (Sweden)

Jiayin Liu

2017-06-01

Full Text Available Remote sensing technologies have been widely applied in urban environments’ monitoring, synthesis and modeling. Incorporating spatial information in perceptually coherent regions, superpixel-based approaches can effectively eliminate the “salt and pepper” phenomenon which is common in pixel-wise approaches. Compared with fixed-size windows, superpixels have adaptive sizes and shapes for different spatial structures. Moreover, superpixel-based algorithms can significantly improve computational efficiency owing to the greatly reduced number of image primitives. Hence, the superpixel algorithm, as a preprocessing technique, is more and more popularly used in remote sensing and many other fields. In this paper, we propose a superpixel segmentation algorithm called Superpixel Segmentation with Local Competition (SSLC, which utilizes a local competition mechanism to construct energy terms and label pixels. The local competition mechanism leads to energy terms locality and relativity, and thus, the proposed algorithm is less sensitive to the diversity of image content and scene layout. Consequently, SSLC could achieve consistent performance in different image regions. In addition, the Probability Density Function (PDF, which is estimated by Kernel Density Estimation (KDE with the Gaussian kernel, is introduced to describe the color distribution of superpixels as a more sophisticated and accurate measure. To reduce computational complexity, a boundary optimization framework is introduced to only handle boundary pixels instead of the whole image. We conduct experiments to benchmark the proposed algorithm with the other state-of-the-art ones on the Berkeley Segmentation Dataset (BSD and remote sensing images. Results demonstrate that the SSLC algorithm yields the best overall performance, while the computation time-efficiency is still competitive.

Structural Behavior of a Long-Span Partially Earth-Anchored Cable-Stayed Bridge during Installation of a Key Segment by Thermal Prestressing

Directory of Open Access Journals (Sweden)

Sang-Hyo Kim

2016-08-01

Full Text Available This study investigated structural behavior of long-span partially earth-anchored cable-stayed bridges with a main span length of 810 m that use a new key segment closing method based on a thermal prestressing technique. A detailed construction sequence analysis matched with the free cantilever method (FCM was performed using a three-dimensional finite element (FE model of a partially earth-anchored cable-stayed bridge. The new method offers an effective way of connecting key segments by avoiding large movements resulting from the removal of the longitudinal restraint owing to the asymmetry of axial forces in the girders near the pylons. The new method develops new member forces through the process of heating the cantilever system before installing the key segment and cooling the system continuously after installing key segments. The resulting forces developed by the thermal process enhance the structural behavior of partially earth-anchored cable-stayed bridges owing to decreased axial forces in the girders.

Unsupervised Retinal Vessel Segmentation Using Combined Filters.

Directory of Open Access Journals (Sweden)

Wendeson S Oliveira

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

Automatic segmentation of psoriasis lesions

Science.gov (United States)

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

2014-10-01

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

Conversion of functionally undefined homopentameric protein PbaA into a proteasome activator by mutational modification of its C-terminal segment conformation.

Science.gov (United States)

Yagi-Utsumi, Maho; Sikdar, Arunima; Kozai, Toshiya; Inoue, Rintaro; Sugiyama, Masaaki; Uchihashi, Takayuki; Yagi, Hirokazu; Satoh, Tadashi; Kato, Koichi

2018-01-01

Recent bioinformatic analyses identified proteasome assembly chaperone-like proteins, PbaA and PbaB, in archaea. PbaB forms a homotetramer and functions as a proteasome activator, whereas PbaA does not interact with the proteasome despite the presence of an apparent C-terminal proteasome activation motif. We revealed that PbaA forms a homopentamer predominantly in the closed conformation with its C-terminal segments packed against the core domains, in contrast to the PbaB homotetramer with projecting C-terminal segments. This prompted us to create a novel proteasome activator based on a well-characterized structural framework. We constructed a panel of chimeric proteins comprising the homopentameric scaffold of PbaA and C-terminal segment of PbaB and subjected them to proteasome-activating assays as well as small-angle X-ray scattering and high-speed atomic force microscopy. The results indicated that the open conformation and consequent proteasome activation activity could be enhanced by replacement of the crystallographically disordered C-terminal segment of PbaA with the corresponding disordered segment of PbaB. Moreover, these effects can be produced just by incorporating two glutamate residues into the disordered C-terminal segment of PbaA, probably due to electrostatic repulsion among the negatively charged segments. Thus, we successfully endowed a functionally undefined protein with proteasome-activating activity by modifying its C-terminal segment. © The Author(s) 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Online Speech/Music Segmentation Based on the Variance Mean of Filter Bank Energy

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Zdravko Kačič

2009-01-01

Full Text Available This paper presents a novel feature for online speech/music segmentation based on the variance mean of filter bank energy (VMFBE. The idea that encouraged the feature's construction is energy variation in a narrow frequency sub-band. The energy varies more rapidly, and to a greater extent for speech than for music. Therefore, an energy variance in such a sub-band is greater for speech than for music. The radio broadcast database and the BNSI broadcast news database were used for feature discrimination and segmentation ability evaluation. The calculation procedure of the VMFBE feature has 4 out of 6 steps in common with the MFCC feature calculation procedure. Therefore, it is a very convenient speech/music discriminator for use in real-time automatic speech recognition systems based on MFCC features, because valuable processing time can be saved, and computation load is only slightly increased. Analysis of the feature's speech/music discriminative ability shows an average error rate below 10% for radio broadcast material and it outperforms other features used for comparison, by more than 8%. The proposed feature as a stand-alone speech/music discriminator in a segmentation system achieves an overall accuracy of over 94% on radio broadcast material.

Online Speech/Music Segmentation Based on the Variance Mean of Filter Bank Energy

Science.gov (United States)

Kos, Marko; Grašič, Matej; Kačič, Zdravko

2009-12-01

This paper presents a novel feature for online speech/music segmentation based on the variance mean of filter bank energy (VMFBE). The idea that encouraged the feature's construction is energy variation in a narrow frequency sub-band. The energy varies more rapidly, and to a greater extent for speech than for music. Therefore, an energy variance in such a sub-band is greater for speech than for music. The radio broadcast database and the BNSI broadcast news database were used for feature discrimination and segmentation ability evaluation. The calculation procedure of the VMFBE feature has 4 out of 6 steps in common with the MFCC feature calculation procedure. Therefore, it is a very convenient speech/music discriminator for use in real-time automatic speech recognition systems based on MFCC features, because valuable processing time can be saved, and computation load is only slightly increased. Analysis of the feature's speech/music discriminative ability shows an average error rate below 10% for radio broadcast material and it outperforms other features used for comparison, by more than 8%. The proposed feature as a stand-alone speech/music discriminator in a segmentation system achieves an overall accuracy of over 94% on radio broadcast material.

Computer-Aided Grading of Gliomas Combining Automatic Segmentation and Radiomics

Directory of Open Access Journals (Sweden)

Wei Chen

2018-01-01

Full Text Available Gliomas are the most common primary brain tumors, and the objective grading is of great importance for treatment. This paper presents an automatic computer-aided diagnosis of gliomas that combines automatic segmentation and radiomics, which can improve the diagnostic ability. The MRI data containing 220 high-grade gliomas and 54 low-grade gliomas are used to evaluate our system. A multiscale 3D convolutional neural network is trained to segment whole tumor regions. A wide range of radiomic features including first-order features, shape features, and texture features is extracted. By using support vector machines with recursive feature elimination for feature selection, a CAD system that has an extreme gradient boosting classifier with a 5-fold cross-validation is constructed for the grading of gliomas. Our CAD system is highly effective for the grading of gliomas with an accuracy of 91.27%, a weighted macroprecision of 91.27%, a weighted macrorecall of 91.27%, and a weighted macro-F1 score of 90.64%. This demonstrates that the proposed CAD system can assist radiologists for high accurate grading of gliomas and has the potential for clinical applications.

Pancreas segmentation from 3D abdominal CT images using patient-specific weighted subspatial probabilistic atlases

Science.gov (United States)

Karasawa, Kenichi; Oda, Masahiro; Hayashi, Yuichiro; Nimura, Yukitaka; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Rueckert, Daniel; Mori, Kensaku

2015-03-01

Abdominal organ segmentations from CT volumes are now widely used in the computer-aided diagnosis and surgery assistance systems. Among abdominal organs, the pancreas is especially difficult to segment because of its large individual differences of the shape and position. In this paper, we propose a new pancreas segmentation method from 3D abdominal CT volumes using patient-specific weighted-subspatial probabilistic atlases. First of all, we perform normalization of organ shapes in training volumes and an input volume. We extract the Volume Of Interest (VOI) of the pancreas from the training volumes and an input volume. We divide each training VOI and input VOI into some cubic regions. We use a nonrigid registration method to register these cubic regions of the training VOI to corresponding regions of the input VOI. Based on the registration results, we calculate similarities between each cubic region of the training VOI and corresponding region of the input VOI. We select cubic regions of training volumes having the top N similarities in each cubic region. We subspatially construct probabilistic atlases weighted by the similarities in each cubic region. After integrating these probabilistic atlases in cubic regions into one, we perform a rough-to-precise segmentation of the pancreas using the atlas. The results of the experiments showed that utilization of the training volumes having the top N similarities in each cubic region led good results of the pancreas segmentation. The Jaccard Index and the average surface distance of the result were 58.9% and 2.04mm on average, respectively.

Simultaneous minimizing monitor units and number of segments without leaf end abutment for segmental intensity modulated radiation therapy delivery

International Nuclear Information System (INIS)

Li Kaile; Dai Jianrong; Ma Lijun

2004-01-01

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

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.

A Flux-Pinning Mechanism for Segment Assembly and Alignment

Science.gov (United States)

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

2011-01-01

Currently, the most compelling astrophysics questions include how planets and the first stars formed and whether there are protostellar disks that contain large organic molecules. Although answering these questions requires space telescopes with apertures of at least 10 meters, such large primaries are challenging to construct by scaling up previous designs; the limited capacity of a launch vehicle bounds the maximum diameter of a monolithic primary, and beyond a certain size, deployable telescopes cannot fit in current launch vehicle fairings. One potential solution is connecting the primary mirror segments edgewise using flux-pinning mechanisms, which are analogous to non-contacting damped springs. In the baseline design, a flux-pinning mechanism consists of a magnet and a superconductor separated by a predetermined gap, with the damping adjusted by placing aluminum near the interface. Since flux pinning is possible only when the superconductor is cooled below a critical temperature, flux-pinning mechanisms are uniquely suited for cryogenic space telescopes. By placing these mechanisms along the edges of the mirror segments, a primary can be built up over time. Since flux pinning requires no mechanical deployments, the assembly process could be robotic or use some other non-contacting scheme. Advantages of this approach include scalability and passive stability.

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.

VOF Modeling and Analysis of the Segmented Flow in Y-Shaped Microchannels for Microreactor Systems

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Xian Wang

2013-01-01

Full Text Available Microscaled devices receive great attention in microreactor systems for producing high renewable energy due to higher surface-to-volume, higher transport rates (heat or/and mass transfer rates, and other advantages over conventional-size reactors. In this paper, the two-phase liquid-liquid flow in a microchannel with various Y-shaped junctions has been studied numerically. Two kinds of immiscible liquids were injected into a microchannel from the Y-shaped junctions to generate the segment flow mode. The segment length was studied. The volume of fluid (VOF method was used to track the liquid-liquid interface and the piecewise-liner interface construction (PLIC technique was adopted to get a sharp interface. The interfacial tension was simulated with continuum surface force (CSF model and the wall adhesion boundary condition was taken into consideration. The simulated flow pattern presents consistence with our experimental one. The numerical results show that a segmented flow mode appears in the main channel. Under the same inlet velocities of two liquids, the segment lengths of the two liquids are the same and depend on the inclined angles of two lateral channels. The effect of inlet velocity is studied in a typical T-shaped microchannel. It is found that the ratio between the lengths of two liquids is almost equal to the ratio between their inlet velocities.

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

Roentgenological diagnoss of central segmental lung cancer

International Nuclear Information System (INIS)

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

1984-01-01

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

TU-H-CAMPUS-IeP3-01: Simultaneous PET Restoration and PET/CT Co-Segmentation Using a Variational Method

International Nuclear Information System (INIS)

Li, L; Tan, S; Lu, W

2016-01-01

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

Three-dimensional model-based object recognition and segmentation in cluttered scenes.

Science.gov (United States)

Mian, Ajmal S; Bennamoun, Mohammed; Owens, Robyn

2006-10-01

Viewpoint independent recognition of free-form objects and their segmentation in the presence of clutter and occlusions is a challenging task. We present a novel 3D model-based algorithm which performs this task automatically and efficiently. A 3D model of an object is automatically constructed offline from its multiple unordered range images (views). These views are converted into multidimensional table representations (which we refer to as tensors). Correspondences are automatically established between these views by simultaneously matching the tensors of a view with those of the remaining views using a hash table-based voting scheme. This results in a graph of relative transformations used to register the views before they are integrated into a seamless 3D model. These models and their tensor representations constitute the model library. During online recognition, a tensor from the scene is simultaneously matched with those in the library by casting votes. Similarity measures are calculated for the model tensors which receive the most votes. The model with the highest similarity is transformed to the scene and, if it aligns accurately with an object in the scene, that object is declared as recognized and is segmented. This process is repeated until the scene is completely segmented. Experiments were performed on real and synthetic data comprised of 55 models and 610 scenes and an overall recognition rate of 95 percent was achieved. Comparison with the spin images revealed that our algorithm is superior in terms of recognition rate and efficiency.

Automatic data-driven real-time segmentation and recognition of surgical workflow.

Science.gov (United States)

Dergachyova, Olga; Bouget, David; Huaulmé, Arnaud; Morandi, Xavier; Jannin, Pierre

2016-06-01

With the intention of extending the perception and action of surgical staff inside the operating room, the medical community has expressed a growing interest towards context-aware systems. Requiring an accurate identification of the surgical workflow, such systems make use of data from a diverse set of available sensors. In this paper, we propose a fully data-driven and real-time method for segmentation and recognition of surgical phases using a combination of video data and instrument usage signals, exploiting no prior knowledge. We also introduce new validation metrics for assessment of workflow detection. The segmentation and recognition are based on a four-stage process. Firstly, during the learning time, a Surgical Process Model is automatically constructed from data annotations to guide the following process. Secondly, data samples are described using a combination of low-level visual cues and instrument information. Then, in the third stage, these descriptions are employed to train a set of AdaBoost classifiers capable of distinguishing one surgical phase from others. Finally, AdaBoost responses are used as input to a Hidden semi-Markov Model in order to obtain a final decision. On the MICCAI EndoVis challenge laparoscopic dataset we achieved a precision and a recall of 91 % in classification of 7 phases. Compared to the analysis based on one data type only, a combination of visual features and instrument signals allows better segmentation, reduction of the detection delay and discovery of the correct phase order.

Method of manufacturing a large-area segmented photovoltaic module

Science.gov (United States)

Lenox, Carl

2013-11-05

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

Study of the morphology exhibited by linear segmented polyurethanes

International Nuclear Information System (INIS)

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

2009-01-01

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

Effects of thyroid hormone supplementation on anastomotic healing after segmental colonic resection.

Science.gov (United States)

Karaman, Kerem; Bostanci, Erdal Birol; Dincer, Nazmiye; Ulas, Murat; Ozer, Ilter; Dalgic, Tahsin; Ercin, Ugur; Bilgihan, Ayse; Ginis, Zeynep; Akoglu, Musa

2012-08-01

Alterations of thyroid hormones in colorectal surgery were previously studied. The aim of the present study was to determine the effects of triiodothyronine (T3) supplementation on anastomotic healing after segmental colectomy. Thirty male Wistar albino rats were divided into sham (n = 6), control (n = 12), and experimental (n = 12) groups. Sham group rats were immediately sacrificed after segmental colonic resection. Control and experimental group rats underwent resection and anastomosis. Experimental group rats received a single dose of T3 (400 μg/100 g) in postoperative day 1. Half of both control and experimental group rats were sacrificed on postoperative d 3 and the remaining half were sacrificed on postoperative d 7. Hydroxiproline (HP), myeloperoxidase (MPO), thyroid stimulating hormone (TSH), free T3 (FT3), and free thyroxine (FT4) levels, bursting pressure, and histologic analyses of the anastomotic segments were compared. FT3 levels significantly decreased in control groups rats compared with the sham group (P < 0.01). However, T3 hormone given rats had no decline in FT3 levels. Anastomotic bursting pressure was significantly higher in the experimental group rats on postoperative d 7 (P = 0.015). Histopathologic analyses of the anastomotic segments determined significantly more severe edema and necrosis in control group rats (P < 0.05). Collagen deposition in the anastomotic tissue was significantly higher in experimental group rats on postoperative d 7 (P = 0.015). Anastomosis after colon resection is associated with decreased FT3 level. T3 supplementation ameliorates the reduction in FT3 and seems to provide constructive therapeutic effects on anastomotic healing. Copyright © 2012 Elsevier Inc. All rights reserved.

CAnat: An algorithm for the automatic segmentation of anatomy of medical images

International Nuclear Information System (INIS)

Caon, M.; Gobert, L.; Mariusz, B.

2011-01-01

Full text: To develop a method to automatically categorise organs and tissues displayed in medical images. Dosimetry calculations using Monte Carlo methods require a mathematical representation of human anatomy e.g. a voxel phantom. For a whole body, their construction involves processing several hundred images to identify each organ and tissue-the process is very time-consuming. This project is developing a Computational Anatomy (CAnat) algorithm to automatically recognise and classify the different tissue in a tomographic image. Methods The algorithm utilizes the Statistical Region Merging technique (SRM). The SRM depends on one estimated parameter. The parameter is a measure of statistical complexity of the image and can be automatically adjusted to suit individual image features. This allows for automatic tuning of coarseness of the overall segmentation as well as object specific selection for further tasks. CAnat is tested on two CT images selected to represent different anatomical complexities. In the mid-thigh image, tissues/. regions of interest are air, fat, muscle, bone marrow and compact bone. In the pelvic image, fat, urinary bladder and anus/colon, muscle, cancellous bone, and compact bone. Segmentation results were evaluated using the Jaccard index which is a measure of set agreement. An index of one indicates perfect agreement between CAnat and manual segmentation. The Jaccard indices for the mid-thigh CT were 0.99, 0.89, 0.97, 0.63 and 0.88, respectively and for the pelvic CT were 0.99, 0.81, 0.77, 0.93, 0.53, 0.76, respectively. Conclusion The high accuracy preliminary segmentation results demonstrate the feasibility of the CAnat algorithm.

Determinants of procurement strategy for construction works: quantity surveyors’ perspectives

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Olanrewaju AbdulLateef

2016-01-01

Full Text Available The selection of the ‘appropriate’ procurement strategy is a prerequisite to the success or failure of a construction project. This paper investigates the factors determining the selection of appropriate procurement strategy for construction works in Nigeria. Data for the study was collected through an online survey questionnaire. The survey administration involves only quantity surveyors. Quantity surveyors were targeted because they advise clients and other stakeholders on procurement and contractual issues on construction works. A total of 33 usable responses were received and analysed for this study. On the basis of the results, it is concluded that the selection of procurement strategies for construction depend on complex interrelated factors. The study could not detect a particular factor or few factors responsible for a procurement strategy selection. The findings of this study is useful because it argues that the construction sector needs to broaden its considerations on the procurement strategy’s determinants rather than focusing solely on the client’s type and nature of projects as is often cited. Future research could segment these factors in terms of class of construction works or increase the sample size, which might lead to different findings.

Biomechanics of Artificial Disc Replacements Adjacent to a 2-Level Fusion in 4-Level Hybrid Constructs: An In Vitro Investigation

Science.gov (United States)

Liao, Zhenhua; Fogel, Guy R.; Wei, Na; Gu, Hongsheng; Liu, Weiqiang

2015-01-01

Background The ideal procedure for multilevel cervical degenerative disc diseases remains controversial. Recent studies on hybrid surgery combining anterior cervical discectomy and fusion (ACDF) and artificial cervical disc replacement (ACDR) for 2-level and 3-level constructs have been reported in the literature. The purpose of this study was to estimate the biomechanics of 3 kinds of 4-level hybrid constructs, which are more likely to be used clinically compared to 4-level arthrodesis. Material/Methods Eighteen human cadaveric spines (C2–T1) were evaluated in different testing conditions: intact, with 3 kinds of 4-level hybrid constructs (hybrid C3–4 ACDR+C4–6 ACDF+C6–7ACDR; hybrid C3–5ACDF+C5–6ACDR+C6–7ACDR; hybrid C3–4ACDR+C4–5ACDR+C5–7ACDF); and 4-level fusion. Results Four-level fusion resulted in significant decrease in the C3–C7 ROM compared with the intact spine. The 3 different 4-level hybrid treatment groups caused only slight change at the instrumented levels compared to intact except for flexion. At the adjacent levels, 4-level fusion resulted in significant increase of contribution of both upper and lower adjacent levels. However, for the 3 hybrid constructs, significant changes of motion increase far lower than 4P at adjacent levels were only noted in partial loading conditions. No destabilizing effect or hypermobility were observed in any 4-level hybrid construct. Conclusions Four-level fusion significantly eliminated motion within the construct and increased motion at the adjacent segments. For all 3 different 4-level hybrid constructs, ACDR normalized motion of the index segment and adjacent segments with no significant hypermobility. Compared with the 4-level ACDF condition, the artificial discs in 4-level hybrid constructs had biomechanical advantages compared to fusion in normalizing adjacent level motion. PMID:26694835

Study on construction method of concrete in the underground research laboratory. 2

International Nuclear Information System (INIS)

Iriya, Keishiro; Mikami, Tetsuji; Akiyoshi, Kenji; Uegaki, Yoshiaki

2002-02-01

The underground research laboratory, which will be constructed in Horonobe, plays a role of demonstration of construction technique upon nuclear waste repositories. Low alkalinity cement is one of candidates for repositories as a cementitious material in order to prevent alteration of bentonite and rock by hyper alkaline solution. JNC has developed a low alkalinity cement (HFSC) which contains a lot of fly ash, and has studied the physical and chemical properties by laboratory test. However workability which is required for construction procedure of repositories has not been studied enough yet. This study shows if requirements in actual construction, such as shotcreting, self-compacting, and, grouting, are fulfilled, and if the workability is preferable for tunneling construction. It is demonstrated that HFSC is applicable for shotcreting by testing in a modeled tunnel. It is pointed out that re-bars have a possibility of corrosion in low alkalinity cement. In-site test for saline water which may accelerate corrosion is started by setting specimen made in last year. Analyzing and assessing will be done next year. Construction method of tunnel lining is investigated in case of applying pre-cast segments. Self-compacting concrete is adopted, since added silica-fume needs superplasticizer and its workability is very flowable. Two piece of segment were made for the section which designed for a ordinary urban tunnel. It is noted that pre-casting concrete can be made by HFSC. Super fine cement powder for grouting which indicate low alkalinity can be selected by combination of grinned lime stone powder and silica fume with grinned ordinary Portland cement. The items to be improved toward using in Horonobe construction are pointed out by results of this study and summarized a study plan is described. Major problem to be solved is delaying compressive strength generation of HFSC. It is recognized in shotcrete and self-compacting concrete. Selecting types of fly ash and

RFA-cut: Semi-automatic segmentation of radiofrequency ablation zones with and without needles via optimal s-t-cuts.

Science.gov (United States)

Egger, Jan; Busse, Harald; Brandmaier, Philipp; Seider, Daniel; Gawlitza, Matthias; Strocka, Steffen; Voglreiter, Philip; Dokter, Mark; Hofmann, Michael; Kainz, Bernhard; Chen, Xiaojun; Hann, Alexander; Boechat, Pedro; Yu, Wei; Freisleben, Bernd; Alhonnoro, Tuomas; Pollari, Mika; Moche, Michael; Schmalstieg, Dieter

2015-01-01

In this contribution, we present a semi-automatic segmentation algorithm for radiofrequency ablation (RFA) zones via optimal s-t-cuts. Our interactive graph-based approach builds upon a polyhedron to construct the graph and was specifically designed for computed tomography (CT) acquisitions from patients that had RFA treatments of Hepatocellular Carcinomas (HCC). For evaluation, we used twelve post-interventional CT datasets from the clinical routine and as evaluation metric we utilized the Dice Similarity Coefficient (DSC), which is commonly accepted for judging computer aided medical segmentation tasks. Compared with pure manual slice-by-slice expert segmentations from interventional radiologists, we were able to achieve a DSC of about eighty percent, which is sufficient for our clinical needs. Moreover, our approach was able to handle images containing (DSC=75.9%) and not containing (78.1%) the RFA needles still in place. Additionally, we found no statistically significant difference (p<;0.423) between the segmentation results of the subgroups for a Mann-Whitney test. Finally, to the best of our knowledge, this is the first time a segmentation approach for CT scans including the RFA needles is reported and we show why another state-of-the-art segmentation method fails for these cases. Intraoperative scans including an RFA probe are very critical in the clinical practice and need a very careful segmentation and inspection to avoid under-treatment, which may result in tumor recurrence (up to 40%). If the decision can be made during the intervention, an additional ablation can be performed without removing the entire needle. This decreases the patient stress and associated risks and costs of a separate intervention at a later date. Ultimately, the segmented ablation zone containing the RFA needle can be used for a precise ablation simulation as the real needle position is known.

Prototype implementation of segment assembling software

Directory of Open Access Journals (Sweden)

Pešić Đorđe

2018-01-01

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

Smart markers for watershed-based cell segmentation.

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Can Fahrettin Koyuncu

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

Smart markers for watershed-based cell segmentation.

Science.gov (United States)

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

2012-01-01

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

An unsupervised strategy for biomedical image segmentation

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Roberto Rodríguez

2010-09-01

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

MOVING WINDOW SEGMENTATION FRAMEWORK FOR POINT CLOUDS

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G. Sithole

2012-07-01

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

Review of segmentation process in consumer markets

OpenAIRE

Veronika Jadczaková

2013-01-01

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

IFRS 8 – OPERATING SEGMENTS

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BOCHIS LEONICA

2009-05-01

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

The Hierarchy of Segment Reports

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Danilo Dorović

2015-05-01

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

Segmental dilatation of the ileum

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Tune-Yie Shih

2017-01-01

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

Techniques on semiautomatic segmentation using the Adobe Photoshop

Science.gov (United States)

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

2005-04-01

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

Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation

Energy Technology Data Exchange (ETDEWEB)

Akhbardeh, Alireza; Jacobs, Michael A. [Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205 (United States); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205 (United States) and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205 (United States)

2012-04-15

both synthetic and clinical data. In the synthetic data, the authors demonstrated the performance of the NLDR method compared with conventional linear DR methods. The NLDR approach enabled successful segmentation of the structures, whereas, in most cases, PCA and MDS failed. The NLDR approach was able to segment different breast tissue types with a high accuracy and the embedded image of the breast MRI data demonstrated fuzzy boundaries between the different types of breast tissue, i.e., fatty, glandular, and tissue with lesions (>86%). Conclusions: The proposed hybrid NLDR methods were able to segment clinical breast data with a high accuracy and construct an embedded image that visualized the contribution of different radiological parameters.

Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation

International Nuclear Information System (INIS)

Akhbardeh, Alireza; Jacobs, Michael A.

2012-01-01

synthetic and clinical data. In the synthetic data, the authors demonstrated the performance of the NLDR method compared with conventional linear DR methods. The NLDR approach enabled successful segmentation of the structures, whereas, in most cases, PCA and MDS failed. The NLDR approach was able to segment different breast tissue types with a high accuracy and the embedded image of the breast MRI data demonstrated fuzzy boundaries between the different types of breast tissue, i.e., fatty, glandular, and tissue with lesions (>86%). Conclusions: The proposed hybrid NLDR methods were able to segment clinical breast data with a high accuracy and construct an embedded image that visualized the contribution of different radiological parameters.

Automatic lung segmentation in functional SPECT images using active shape models trained on reference lung shapes from CT.

Science.gov (United States)

Cheimariotis, Grigorios-Aris; Al-Mashat, Mariam; Haris, Kostas; Aletras, Anthony H; Jögi, Jonas; Bajc, Marika; Maglaveras, Nicolaos; Heiberg, Einar

2018-02-01

Image segmentation is an essential step in quantifying the extent of reduced or absent lung function. The aim of this study is to develop and validate a new tool for automatic segmentation of lungs in ventilation and perfusion SPECT images and compare automatic and manual SPECT lung segmentations with reference computed tomography (CT) volumes. A total of 77 subjects (69 patients with obstructive lung disease, and 8 subjects without apparent perfusion of ventilation loss) performed low-dose CT followed by ventilation/perfusion (V/P) SPECT examination in a hybrid gamma camera system. In the training phase, lung shapes from the 57 anatomical low-dose CT images were used to construct two active shape models (right lung and left lung) which were then used for image segmentation. The algorithm was validated in 20 patients, comparing its results to reference delineation of corresponding CT images, and by comparing automatic segmentation to manual delineations in SPECT images. The Dice coefficient between automatic SPECT delineations and manual SPECT delineations were 0.83 ± 0.04% for the right and 0.82 ± 0.05% for the left lung. There was statistically significant difference between reference volumes from CT and automatic delineations for the right (R = 0.53, p = 0.02) and left lung (R = 0.69, p automatic quantification of wide range of measurements.

CT identification of bronchopulmonary segments: 50 normal subjects

International Nuclear Information System (INIS)

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

1984-01-01

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

Segmentation of liver tumors on CT images

International Nuclear Information System (INIS)

Pescia, D.

2011-01-01

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

SU-E-J-131: Augmenting Atlas-Based Segmentation by Incorporating Image Features Proximal to the Atlas Contours

International Nuclear Information System (INIS)

Li, Dengwang; Liu, Li; Kapp, Daniel S.; Xing, Lei

2015-01-01

Purpose: For facilitating the current automatic segmentation, in this work we propose a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. Methods: In setting up an atlas-based library, we include not only the coordinates of contour points, but also the image features adjacent to the contour. 139 planning CT scans with normal appearing livers obtained during their radiotherapy treatment planning were used to construct the library. The CT images within the library were registered each other using affine registration. A nonlinear narrow shell with the regional thickness determined by the distance between two vertices alongside the contour. The narrow shell was automatically constructed both inside and outside of the liver contours. The common image features within narrow shell between a new case and a library case were first selected by a Speed-up Robust Features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the images of the new patient by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy function within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by a physician. Results: Application of the technique to 30 liver cases suggested that the technique was capable of reliably segment organs such as the liver with little human intervention. Compared with the manual segmentation results by a physician, the average and discrepancies of the volumetric overlap percentage (VOP) was found to be 92.43%+2.14%. Conclusion: Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically

SU-E-J-131: Augmenting Atlas-Based Segmentation by Incorporating Image Features Proximal to the Atlas Contours

Energy Technology Data Exchange (ETDEWEB)

Li, Dengwang; Liu, Li [College of Physics and Electronics, Shandong Normal University, Jinan, Shandong (China); Kapp, Daniel S.; Xing, Lei [Department of Radiation Oncology, Stanford University, School of Medicine, Stanford, CA (United States)

2015-06-15

Purpose: For facilitating the current automatic segmentation, in this work we propose a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. Methods: In setting up an atlas-based library, we include not only the coordinates of contour points, but also the image features adjacent to the contour. 139 planning CT scans with normal appearing livers obtained during their radiotherapy treatment planning were used to construct the library. The CT images within the library were registered each other using affine registration. A nonlinear narrow shell with the regional thickness determined by the distance between two vertices alongside the contour. The narrow shell was automatically constructed both inside and outside of the liver contours. The common image features within narrow shell between a new case and a library case were first selected by a Speed-up Robust Features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the images of the new patient by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy function within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by a physician. Results: Application of the technique to 30 liver cases suggested that the technique was capable of reliably segment organs such as the liver with little human intervention. Compared with the manual segmentation results by a physician, the average and discrepancies of the volumetric overlap percentage (VOP) was found to be 92.43%+2.14%. Conclusion: Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically

Segmentation of knee injury swelling on infrared images

Science.gov (United States)

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

2011-03-01

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

Reliability of a Seven-Segment Foot Model with Medial and Lateral Midfoot and Forefoot Segments During Walking Gait.

Science.gov (United States)

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

2016-12-01

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

Market Segmentation: An Instructional Module.

Science.gov (United States)

Wright, Peter H.

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

Medical image segmentation using genetic algorithms.

Science.gov (United States)

Maulik, Ujjwal

2009-03-01

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

An automated segmentation methodology for quantifying immunoreactive puncta number and fluorescence intensity in tissue sections.

Science.gov (United States)

Fish, Kenneth N; Sweet, Robert A; Deo, Anthony J; Lewis, David A

2008-11-13

A number of human brain diseases have been associated with disturbances in the structure and function of cortical synapses. Answering fundamental questions about the synaptic machinery in these disease states requires the ability to image and quantify small synaptic structures in tissue sections and to evaluate protein levels at these major sites of function. We developed a new automated segmentation imaging method specifically to answer such fundamental questions. The method takes advantage of advances in spinning disk confocal microscopy, and combines information from multiple iterations of a fluorescence intensity/morphological segmentation protocol to construct three-dimensional object masks of immunoreactive (IR) puncta. This new methodology is unique in that high- and low-fluorescing IR puncta are equally masked, allowing for quantification of the number of fluorescently-labeled puncta in tissue sections. In addition, the shape of the final object masks highly represents their corresponding original data. Thus, the object masks can be used to extract information about the IR puncta (e.g., average fluorescence intensity of proteins of interest). Importantly, the segmentation method presented can be easily adapted for use with most existing microscopy analysis packages.

Remote sensing image segmentation based on Hadoop cloud platform

Science.gov (United States)

Li, Jie; Zhu, Lingling; Cao, Fubin

2018-01-01

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

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.

Segmental Bayesian estimation of gap-junctional and inhibitory conductance of inferior olive neurons from spike trains with complicated dynamics

Directory of Open Access Journals (Sweden)

Huu eHoang

2015-05-01

Full Text Available The inverse problem for estimating model parameters from brain spike data is an ill-posed problem because of a huge mismatch in the system complexity between the model and the brain as well as its non-stationary dynamics, and needs a stochastic approach that finds the most likely solution among many possible solutions. In the present study, we developed a segmental Bayesian method to estimate the two parameters of interest, the gap-junctional (gc and inhibitory conductance (gi from inferior olive spike data. Feature vectors were estimated for the spike data in a segment-wise fashion to compensate for the non-stationary firing dynamics. Hierarchical Bayesian estimation was conducted to estimate the gc and gi for every spike segment using a forward model constructed in the principal component analysis (PCA space of the feature vectors, and to merge the segmental estimates into single estimates for every neuron. The segmental Bayesian estimation gave smaller fitting errors than the conventional Bayesian inference, which finds the estimates once across the entire spike data, or the minimum error method, which directly finds the closest match in the PCA space. The segmental Bayesian inference has the potential to overcome the problem of non-stationary dynamics and resolve the ill-posedness of the inverse problem because of the mismatch between the model and the brain under the constraints based, and it is a useful tool to evaluate parameters of interest for neuroscience from experimental spike train data.

Incorporation of squalene into rod outer segments

International Nuclear Information System (INIS)

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

1990-01-01

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

Interactive segmentation techniques algorithms and performance evaluation

CERN Document Server

He, Jia; Kuo, C-C Jay

2013-01-01

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

Market segmentation using perceived constraints

Science.gov (United States)

Jinhee Jun; Gerard Kyle; Andrew Mowen

2008-01-01

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

Reduplication Facilitates Early Word Segmentation

Science.gov (United States)

Ota, Mitsuhiko; Skarabela, Barbora

2018-01-01

This study explores the possibility that early word segmentation is aided by infants' tendency to segment words with repeated syllables ("reduplication"). Twenty-four nine-month-olds were familiarized with passages containing one novel reduplicated word and one novel non-reduplicated word. Their central fixation times in response to…

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...

Common risks affecting time overrun in road construction projects in Palestine: Contractors’ perspective

Directory of Open Access Journals (Sweden)

Ibrahim Mahamid

2013-06-01

Full Text Available The construction sector is one of the key economic sectors and is the main force motivating the Palestinian national economy. However, it suffers from number of problems that affect time, cost and quality performances. This study aims at identifying the common risks affecting time overrun in road construction projects in the West Bank in Palestine from contractors’ viewpoint. 45 factors that might cause delays of road construction projects were defined through a detailed literature review. A questionnaire survey was performed to rank the considered factors in terms of severity and frequency. The analysis of the survey indicated that the top risks affecting time overrun in road construction projects in Palestine are: financial status of the contractors, payments delay by the owner, political situation, segmentation of the West Bank, poor communication between construction parties, lack of equipment efficiency, and high competition in bids.

Tracking fuzzy borders using geodesic curves with application to liver segmentation on planning CT

International Nuclear Information System (INIS)

Yuan, Yading; Chao, Ming; Sheu, Ren-Dih; Rosenzweig, Kenneth; Lo, Yeh-Chi

2015-01-01

Purpose: This work aims to develop a robust and efficient method to track the fuzzy borders between liver and the abutted organs where automatic liver segmentation usually suffers, and to investigate its applications in automatic liver segmentation on noncontrast-enhanced planning computed tomography (CT) images. Methods: In order to track the fuzzy liver–chestwall and liver–heart borders where oversegmentation is often found, a starting point and an ending point were first identified on the coronal view images; the fuzzy border was then determined as a geodesic curve constructed by minimizing the gradient-weighted path length between these two points near the fuzzy border. The minimization of path length was numerically solved by fast-marching method. The resultant fuzzy borders were incorporated into the authors’ automatic segmentation scheme, in which the liver was initially estimated by a patient-specific adaptive thresholding and then refined by a geodesic active contour model. By using planning CT images of 15 liver patients treated with stereotactic body radiation therapy, the liver contours extracted by the proposed computerized scheme were compared with those manually delineated by a radiation oncologist. Results: The proposed automatic liver segmentation method yielded an average Dice similarity coefficient of 0.930 ± 0.015, whereas it was 0.912 ± 0.020 if the fuzzy border tracking was not used. The application of fuzzy border tracking was found to significantly improve the segmentation performance. The mean liver volume obtained by the proposed method was 1727 cm 3 , whereas it was 1719 cm 3 for manual-outlined volumes. The computer-generated liver volumes achieved excellent agreement with manual-outlined volumes with correlation coefficient of 0.98. Conclusions: The proposed method was shown to provide accurate segmentation for liver in the planning CT images where contrast agent is not applied. The authors’ results also clearly demonstrated

Multifractal-based nuclei segmentation in fish images.

Science.gov (United States)

Reljin, Nikola; Slavkovic-Ilic, Marijeta; Tapia, Coya; Cihoric, Nikola; Stankovic, Srdjan

2017-09-01

The method for nuclei segmentation in fluorescence in-situ hybridization (FISH) images, based on the inverse multifractal analysis (IMFA) is proposed. From the blue channel of the FISH image in RGB format, the matrix of Holder exponents, with one-by-one correspondence with the image pixels, is determined first. The following semi-automatic procedure is proposed: initial nuclei segmentation is performed automatically from the matrix of Holder exponents by applying predefined hard thresholding; then the user evaluates the result and is able to refine the segmentation by changing the threshold, if necessary. After successful nuclei segmentation, the HER2 (human epidermal growth factor receptor 2) scoring can be determined in usual way: by counting red and green dots within segmented nuclei, and finding their ratio. The IMFA segmentation method is tested over 100 clinical cases, evaluated by skilled pathologist. Testing results show that the new method has advantages compared to already reported methods.

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…

Retinal vascular segmentation using superpixel-based line operator and its application to vascular topology estimation.

Science.gov (United States)

Na, Tong; Xie, Jianyang; Zhao, Yitian; Zhao, Yifan; Liu, Yue; Wang, Yongtian; Liu, Jiang

2018-05-09

Automatic methods of analyzing of retinal vascular networks, such as retinal blood vessel detection, vascular network topology estimation, and arteries/veins classification are of great assistance to the ophthalmologist in terms of diagnosis and treatment of a wide spectrum of diseases. We propose a new framework for precisely segmenting retinal vasculatures, constructing retinal vascular network topology, and separating the arteries and veins. A nonlocal total variation inspired Retinex model is employed to remove the image intensity inhomogeneities and relatively poor contrast. For better generalizability and segmentation performance, a superpixel-based line operator is proposed as to distinguish between lines and the edges, thus allowing more tolerance in the position of the respective contours. The concept of dominant sets clustering is adopted to estimate retinal vessel topology and classify the vessel network into arteries and veins. The proposed segmentation method yields competitive results on three public data sets (STARE, DRIVE, and IOSTAR), and it has superior performance when compared with unsupervised segmentation methods, with accuracy of 0.954, 0.957, and 0.964, respectively. The topology estimation approach has been applied to five public databases (DRIVE,STARE, INSPIRE, IOSTAR, and VICAVR) and achieved high accuracy of 0.830, 0.910, 0.915, 0.928, and 0.889, respectively. The accuracies of arteries/veins classification based on the estimated vascular topology on three public databases (INSPIRE, DRIVE and VICAVR) are 0.90.9, 0.910, and 0.907, respectively. The experimental results show that the proposed framework has effectively addressed crossover problem, a bottleneck issue in segmentation and vascular topology reconstruction. The vascular topology information significantly improves the accuracy on arteries/veins classification. © 2018 American Association of Physicists in Medicine.

Boundary segmentation for fluorescence microscopy using steerable filters

Science.gov (United States)

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

2017-02-01

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

Ancestral patterning of tergite formation in a centipede suggests derived mode of trunk segmentation in trilobites.

Directory of Open Access Journals (Sweden)

Javier Ortega-Hernández

Full Text Available Trilobites have a rich and abundant fossil record, but little is known about the intrinsic mechanisms that orchestrate their body organization. To date, there is disagreement regarding the correspondence, or lack thereof, of the segmental units that constitute the trilobite trunk and their associated exoskeletal elements. The phylogenetic position of trilobites within total-group Euarthropoda, however, allows inferences about the underlying organization in these extinct taxa to be made, as some of the fundamental genetic processes for constructing the trunk segments are remarkably conserved among living arthropods. One example is the expression of the segment polarity gene engrailed, which at embryonic and early postembryonic stages is expressed in extant panarthropods (i.e. tardigrades, onychophorans, euarthropods as transverse stripes that define the posteriormost region of each trunk segment. Due to its conservative morphology and allegedly primitive trunk tagmosis, we have utilized the centipede Strigamia maritima to study the correspondence between the expression of engrailed during late embryonic to postembryonic stages, and the development of the dorsal exoskeletal plates (i.e. tergites. The results corroborate the close correlation between the formation of the tergite borders and the dorsal expression of engrailed, and suggest that this association represents a symplesiomorphy within Euarthropoda. This correspondence between the genetic and phenetic levels enables making accurate inferences about the dorsoventral expression domains of engrailed in the trunk of exceptionally preserved trilobites and their close relatives, and is suggestive of the widespread occurrence of a distinct type of genetic segmental mismatch in these extinct arthropods. The metameric organization of the digestive tract in trilobites provides further support to this new interpretation. The wider evolutionary implications of these findings suggest the presence of a

Connecting textual segments

DEFF Research Database (Denmark)

Brügger, Niels

2017-01-01

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......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...

A comparative study on medical image segmentation methods

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Praylin Selva Blessy SELVARAJ ASSLEY

2014-03-01

Full Text Available Image segmentation plays an important role in medical images. It has been a relevant research area in computer vision and image analysis. Many segmentation algorithms have been proposed for medical images. This paper makes a review on segmentation methods for medical images. In this survey, segmentation methods are divided into five categories: region based, boundary based, model based, hybrid based and atlas based. The five different categories with their principle ideas, advantages and disadvantages in segmenting different medical images are discussed.

Distance measures for image segmentation evaluation

OpenAIRE

Monteiro, Fernando C.; Campilho, Aurélio

2012-01-01

In this paper we present a study of evaluation measures that enable the quantification of the quality of an image segmentation result. Despite significant advances in image segmentation techniques, evaluation of these techniques thus far has been largely subjective. Typically, the effectiveness of a new algorithm is demonstrated only by the presentation of a few segmented images and is otherwise left to subjective evaluation by the reader. Such an evaluation criterion can be useful for differ...

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%.

Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries

Science.gov (United States)

Davuluri, Pavani; Wu, Jie; Tang, Yang; Cockrell, Charles H.; Ward, Kevin R.; Najarian, Kayvan; Hargraves, Rosalyn H.

2012-01-01

Automated hemorrhage detection and segmentation in traumatic pelvic injuries is vital for fast and accurate treatment decision making. Hemorrhage is the main cause of deaths in patients within first 24 hours after the injury. It is very time consuming for physicians to analyze all Computed Tomography (CT) images manually. As time is crucial in emergence medicine, analyzing medical images manually delays the decision-making process. Automated hemorrhage detection and segmentation can significantly help physicians to analyze these images and make fast and accurate decisions. Hemorrhage segmentation is a crucial step in the accurate diagnosis and treatment decision-making process. This paper presents a novel rule-based hemorrhage segmentation technique that utilizes pelvic anatomical information to segment hemorrhage accurately. An evaluation measure is used to quantify the accuracy of hemorrhage segmentation. The results show that the proposed method is able to segment hemorrhage very well, and the results are promising. PMID:22919433

SALIENCY BASED SEGMENTATION OF SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

A. Sharma

2015-03-01

Full Text Available Saliency gives the way as humans see any image and saliency based segmentation can be eventually helpful in Psychovisual image interpretation. Keeping this in view few saliency models are used along with segmentation algorithm and only the salient segments from image have been extracted. The work is carried out for terrestrial images as well as for satellite images. The methodology used in this work extracts those segments from segmented image which are having higher or equal saliency value than a threshold value. Salient and non salient regions of image become foreground and background respectively and thus image gets separated. For carrying out this work a dataset of terrestrial images and Worldview 2 satellite images (sample data are used. Results show that those saliency models which works better for terrestrial images are not good enough for satellite image in terms of foreground and background separation. Foreground and background separation in terrestrial images is based on salient objects visible on the images whereas in satellite images this separation is based on salient area rather than salient objects.

Mathematical Tools for Geomagnetic Data Monitoring and the Intermagnet Russian Segment

Directory of Open Access Journals (Sweden)

Anatoly Soloviev

2013-02-01

Full Text Available In this paper, a new approach to the detection of anomalies in geophysical records is connected with a fuzzy mathematics application. The theory of discrete mathematical analysis and collection of algorithms for time series processing constructed on its basis represents the results of this research direction. These algorithms are the consequence of fuzzy modeling of the logic of an interpreter who visually recognizes anomalies in records. They allow analyzing large data sets that are not subjected to manual processing. The efficiency of these algorithms is demonstrated in several important geophysical applications. Plans for an extension of the Russian INTERMAGNET segment are presented.

Segmentation precedes face categorization under suboptimal conditions

Directory of Open Access Journals (Sweden)

Carlijn eVan Den Boomen

2015-05-01

Full Text Available Both categorization and segmentation processes play a crucial role in face perception. However, the functional relation between these subprocesses is currently unclear. The present study investigates the temporal relation between segmentation-related and category-selective responses in the brain, using electroencephalography (EEG. Surface segmentation and category content were both manipulated using texture-defined objects, including faces. This allowed us to study brain activity related to segmentation and to categorization. In the main experiment, participants viewed texture-defined objects for a duration of 800 ms. EEG results revealed that segmentation-related responses precede category-selective responses. Three additional experiments revealed that the presence and timing of categorization depends on stimulus properties and presentation duration. Photographic objects were presented for a long and short (92 ms duration and evoked fast category-selective responses in both cases. On the other hand, presentation of texture-defined objects for a short duration only evoked segmentation-related but no category-selective responses. Category-selective responses were much slower when evoked by texture-defined than by photographic objects. We suggest that in case of categorization of objects under suboptimal conditions, such as when low-level stimulus properties are not sufficient for fast object categorization, segmentation facilitates the slower categorization process.

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

Segmentation precedes face categorization under suboptimal conditions.

Science.gov (United States)

Van Den Boomen, Carlijn; Fahrenfort, Johannes J; Snijders, Tineke M; Kemner, Chantal

2015-01-01

Both categorization and segmentation processes play a crucial role in face perception. However, the functional relation between these subprocesses is currently unclear. The present study investigates the temporal relation between segmentation-related and category-selective responses in the brain, using electroencephalography (EEG). Surface segmentation and category content were both manipulated using texture-defined objects, including faces. This allowed us to study brain activity related to segmentation and to categorization. In the main experiment, participants viewed texture-defined objects for a duration of 800 ms. EEG results revealed that segmentation-related responses precede category-selective responses. Three additional experiments revealed that the presence and timing of categorization depends on stimulus properties and presentation duration. Photographic objects were presented for a long and short (92 ms) duration and evoked fast category-selective responses in both cases. On the other hand, presentation of texture-defined objects for a short duration only evoked segmentation-related but no category-selective responses. Category-selective responses were much slower when evoked by texture-defined than by photographic objects. We suggest that in case of categorization of objects under suboptimal conditions, such as when low-level stimulus properties are not sufficient for fast object categorization, segmentation facilitates the slower categorization process.

Improved document image segmentation algorithm using multiresolution morphology

Science.gov (United States)

Bukhari, Syed Saqib; Shafait, Faisal; Breuel, Thomas M.

2011-01-01

Page segmentation into text and non-text elements is an essential preprocessing step before optical character recognition (OCR) operation. In case of poor segmentation, an OCR classification engine produces garbage characters due to the presence of non-text elements. This paper describes modifications to the text/non-text segmentation algorithm presented by Bloomberg,1 which is also available in his open-source Leptonica library.2The modifications result in significant improvements and achieved better segmentation accuracy than the original algorithm for UW-III, UNLV, ICDAR 2009 page segmentation competition test images and circuit diagram datasets.

Apparatus For Laminating Segmented Core For Electric Machine

Science.gov (United States)

Lawrence, Robert Anthony; Stabel, Gerald R

2003-06-17

A segmented core for an electric machine includes segments stamped from coated electric steel. The segments each have a first end, a second end, and winding openings. A predetermined number of segments are placed end-to-end to form layers. The layers are stacked such that each of the layers is staggered from adjacent layers by a predetermined rotation angle. The winding openings of each of the layers are in vertical alignment with the winding openings of the adjacent layers. The stack of layers is secured to form the segmented core.

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

Bilingual Phonological Awareness: Multilevel Construct Validation among Spanish-Speaking Kindergarteners in Transitional Bilingual Education Classrooms

Science.gov (United States)

Branum-Martin, Lee; Mehta, Paras D.; Fletcher, Jack M.; Carlson, Coleen D.; Ortiz, Alba; Carlo, Maria; Francis, David J.

2006-01-01

The construct validity of English and Spanish phonological awareness (PA) tasks was examined with a sample of 812 kindergarten children from 71 transitional bilingual education program classrooms located in 3 different types of geographic regions in California and Texas. Tasks of PA, including blending nonwords, segmenting words, and phoneme…

Metrology requirements for the serial production of ELT primary mirror segments

Science.gov (United States)

Rees, Paul C. T.; Gray, Caroline

2015-08-01

The manufacture of the next generation of large astronomical telescopes, the extremely large telescopes (ELT), requires the rapid manufacture of greater than 500 1.44m hexagonal segments for the primary mirror of each telescope. Both leading projects, the Thirty Meter Telescope (TMT) and the European Extremely Large Telescope (E-ELT), have set highly demanding technical requirements for each fabricated segment. These technical requirements, when combined with the anticipated construction schedule for each telescope, suggest that more than one optical fabricator will be involved in the delivery of the primary mirror segments in order to meet the project schedule. For one supplier, the technical specification is challenging and requires highly consistent control of metrology in close coordination with the polishing technologies used in order to optimize production rates. For production using multiple suppliers, however the supply chain is structured, consistent control of metrology along the supply chain will be required. This requires a broader pattern of independent verification than is the case of a single supplier. This paper outlines the metrology requirements for a single supplier throughout all stages of the fabrication process. We identify and outline those areas where metrology accuracy and duration have a significant impact on production efficiency. We use the challenging ESO E-ELT technical specification as an example of our treatment, including actual process data. We further develop this model for the case of a supply chain consisting of multiple suppliers. Here, we emphasize the need to control metrology throughout the supply chain in order to optimize net production efficiency.

A proposal for laminated pie mechanical construction of a toroidal magnet for the far detector for the MINOS experiment

International Nuclear Information System (INIS)

Fields, T.; Guarino, V.; Petereit, E.; Schoessow, P.; Thompson, K.

1996-01-01

This proposal describes an alternative to the reference design for the construction of the toroidal magnet for the detector for the MINOS experiment. This design proposes to construct the steel planes from several steel sheets and laminate them into the required thickness of four centimeters. The 8 meter planes are constructed by cutting all of the steel plates to the same size, which is pie a pie shaped segment of either 30 or 22.5 degrees each. All of the plates in the construction are identical, which is conducive to rapid production and lower cost. The advantages of the proposed laminated construction over the reference design are listed in this paper

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.

Slurry walls and slurry trenches - construction quality control

International Nuclear Information System (INIS)

Poletto, R.J.; Good, D.R.

1997-01-01

Slurry (panel) walls and slurry trenches have become conventional methods for construction of deep underground structures, interceptor trenches and hydraulic (cutoff) barriers. More recently polymers mixed with water are used to stabilize the excavation instead of bentonite slurry. Slurry walls are typically excavated in short panel segments, 2 to 7 m (7 to 23 ft) long, and backfilled with structural materials; whereas slurry trenches are fairly continuous excavations with concurrent backfilling of blended soils, or cement-bentonite mixtures. Slurry trench techniques have also been used to construct interceptor trenches. Currently no national standards exist for the design and/or construction of slurry walls/trenches. Government agencies, private consultants, contractors and trade groups have published specifications for construction of slurry walls/trenches. These specifications vary in complexity and quality of standards. Some place excessive emphasis on the preparation and control of bentonite or polymer slurry used for excavation, with insufficient emphasis placed on quality control of bottom cleaning, tremie concrete, backfill placement or requirements for the finished product. This has led to numerous quality problems, particularly with regard to identification of key depths, bottom sediments and proper backfill placement. This paper will discuss the inspection of slurry wall/trench construction process, identifying those areas which require special scrutiny. New approaches to inspection of slurry stabilized excavations are discussed

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.

Large photonic band gaps and strong attenuations of two-segment-connected Peano derivative networks

International Nuclear Information System (INIS)

Lu, Jian; Yang, Xiangbo; Zhang, Guogang; Cai, Lianzhang

2011-01-01

In this Letter, based on ancient Peano curves we construct four kinds of interesting Peano derivative networks composed of one-dimensional (1D) waveguides and investigate the optical transmission spectra and photonic attenuation behavior of electromagnetic (EM) waves in one- and two-segment-connected networks. It is found that for some two-segment-connected networks large photonic band gaps (PBGs) can be created and the widths of large PBGs can be controlled by adjusting the matching ratio of waveguide length and are insensitive to generation number. Diamond- and hexagon-Peano networks are good selectable structures for the designing of optical devices with large PBG(s) and strong attenuation(s). -- Highlights: → Peano and Peano derivative networks composed of 1D waveguides are designed. → Large PBGs with strong attenuations have been created by these fractal networks. → New approach for designing optical devices with large PBGs is proposed. → Diamond- and hexagon-Peano networks with d2:d1=2:1 are good selectable structures.

Constructs for the expression of repeating triple-helical protein domains

International Nuclear Information System (INIS)

Peng, Yong Y; Werkmeister, Jerome A; Vaughan, Paul R; Ramshaw, John A M

2009-01-01

The development of novel scaffolds will be an important aspect in future success of tissue engineering. Scaffolds will preferably contain information that directs the cellular content of constructs so that the new tissue that is formed is closely aligned in structure, composition and function to the target natural tissue. One way of approaching this will be the development of novel protein-based constructs that contain one or more repeats of functional elements derived from various proteins. In the present case, we describe a strategy to make synthetic, recombinant triple-helical constructs that contain repeat segments of biologically relevant domains. Copies of a DNA fragment prepared by PCR from human type III collagen have been inserted in a co-linear contiguous fashion into the yeast expression vector YEpFlag-1, using sequential addition between selected restriction sites. Constructs containing 1, 2 and 3 repeats were designed to maintain the (Gly-X-Y) repeat, which is essential for the formation of an extended triple helix. All constructs gave expressed protein, with the best being the 3-repeat construct which was readily secreted. This material had the expected composition and N-terminal sequence. Incubation of the product at low temperature led to triple-helix formation, shown by reaction with a conformation dependent monoclonal antibody.

Constructs for the expression of repeating triple-helical protein domains

Energy Technology Data Exchange (ETDEWEB)

Peng, Yong Y; Werkmeister, Jerome A; Vaughan, Paul R; Ramshaw, John A M, E-mail: jerome.werkmeister@csiro.a [CSIRO Molecular and Health Technologies, Bag 10, Clayton South, VIC 3169 (Australia)

2009-02-15

The development of novel scaffolds will be an important aspect in future success of tissue engineering. Scaffolds will preferably contain information that directs the cellular content of constructs so that the new tissue that is formed is closely aligned in structure, composition and function to the target natural tissue. One way of approaching this will be the development of novel protein-based constructs that contain one or more repeats of functional elements derived from various proteins. In the present case, we describe a strategy to make synthetic, recombinant triple-helical constructs that contain repeat segments of biologically relevant domains. Copies of a DNA fragment prepared by PCR from human type III collagen have been inserted in a co-linear contiguous fashion into the yeast expression vector YEpFlag-1, using sequential addition between selected restriction sites. Constructs containing 1, 2 and 3 repeats were designed to maintain the (Gly-X-Y) repeat, which is essential for the formation of an extended triple helix. All constructs gave expressed protein, with the best being the 3-repeat construct which was readily secreted. This material had the expected composition and N-terminal sequence. Incubation of the product at low temperature led to triple-helix formation, shown by reaction with a conformation dependent monoclonal antibody.

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.

Possibilities of segmentation variables in relation with advertising

OpenAIRE

Erbanová, Nela

2011-01-01

The aim of this thesis is to capture significant segmentation variables that shape marketing communication with an emphasis on advertising. The theoretical part deals with the concepts of market segmentation, segmentation variables, marketing communication, advertising and research. The practical part is focused on the realization of the actual research using a questionnaire survey and the evaluation of questions from Market Media Lifestyle. Only traditional descriptive segmentation variables...

Modal Damping Ratio and Optimal Elastic Moduli of Human Body Segments for Anthropometric Vibratory Model of Standing Subjects.

Science.gov (United States)

Gupta, Manoj; Gupta, T C

2017-10-01

The present study aims to accurately estimate inertial, physical, and dynamic parameters of human body vibratory model consistent with physical structure of the human body that also replicates its dynamic response. A 13 degree-of-freedom (DOF) lumped parameter model for standing person subjected to support excitation is established. Model parameters are determined from anthropometric measurements, uniform mass density, elastic modulus of individual body segments, and modal damping ratios. Elastic moduli of ellipsoidal body segments are initially estimated by comparing stiffness of spring elements, calculated from a detailed scheme, and values available in literature for same. These values are further optimized by minimizing difference between theoretically calculated platform-to-head transmissibility ratio (TR) and experimental measurements. Modal damping ratios are estimated from experimental transmissibility response using two dominant peaks in the frequency range of 0-25 Hz. From comparison between dynamic response determined form modal analysis and experimental results, a set of elastic moduli for different segments of human body and a novel scheme to determine modal damping ratios from TR plots, are established. Acceptable match between transmissibility values calculated from the vibratory model and experimental measurements for 50th percentile U.S. male, except at very low frequencies, establishes the human body model developed. Also, reasonable agreement obtained between theoretical response curve and experimental response envelop for average Indian male, affirms the technique used for constructing vibratory model of a standing person. Present work attempts to develop effective technique for constructing subject specific damped vibratory model based on its physical measurements.

Open-source software platform for medical image segmentation applications

Science.gov (United States)

Namías, R.; D'Amato, J. P.; del Fresno, M.

2017-11-01

Segmenting 2D and 3D images is a crucial and challenging problem in medical image analysis. Although several image segmentation algorithms have been proposed for different applications, no universal method currently exists. Moreover, their use is usually limited when detection of complex and multiple adjacent objects of interest is needed. In addition, the continually increasing volumes of medical imaging scans require more efficient segmentation software design and highly usable applications. In this context, we present an extension of our previous segmentation framework which allows the combination of existing explicit deformable models in an efficient and transparent way, handling simultaneously different segmentation strategies and interacting with a graphic user interface (GUI). We present the object-oriented design and the general architecture which consist of two layers: the GUI at the top layer, and the processing core filters at the bottom layer. We apply the framework for segmenting different real-case medical image scenarios on public available datasets including bladder and prostate segmentation from 2D MRI, and heart segmentation in 3D CT. Our experiments on these concrete problems show that this framework facilitates complex and multi-object segmentation goals while providing a fast prototyping open-source segmentation tool.

Detecting the changes in rural communities in Taiwan by applying multiphase segmentation on FORMOSA-2 satellite imagery

Science.gov (United States)

Huang, Yishuo

2015-09-01

Agricultural activities mainly occur in rural areas; recently, ecological conservation and biological diversity are being emphasized in rural communities to promote sustainable development for rural communities, especially for rural communities in Taiwan. Therefore, since 2005, many rural communities in Taiwan have compiled their own development strategies in order to create their own unique characteristics to attract people to visit and stay in rural communities. By implementing these strategies, young people can stay in their own rural communities and the rural communities are rejuvenated. However, some rural communities introduce artificial construction into the community such that the ecological and biological environments are significantly degraded. The strategies need to be efficiently monitored because up to 67 rural communities have proposed rejuvenation projects. In 2015, up to 440 rural communities were estimated to be involved in rural community rejuvenations. How to monitor the changes occurring in those rural communities participating in rural community rejuvenation such that ecological conservation and ecological diversity can be satisfied is an important issue in rural community management. Remote sensing provides an efficient and rapid method to achieve this issue. Segmentation plays a fundamental role in human perception. In this respect, segmentation can be used as the process of transforming the collection of pixels of an image into a group of regions or objects with meaning. This paper proposed an algorithm based on the multiphase approach to segment the normalized difference vegetation index, NDVI, of the rural communities into several sub-regions, and to have the NDVI distribution in each sub-region be homogeneous. Those regions whose values of NDVI are close will be merged into the same class. In doing so, a complex NDVI map can be simplified into two groups: the high and low values of NDVI. The class with low NDVI values corresponds to those

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.

Moving Segmentation Up the Supply-Chain: Supply Chain Segmentation and Artificial Neural Networks

OpenAIRE

Erevelles, Sunil; Fukawa, Nobuyuki

2008-01-01

This paper explained the concept of supply-side segmentation and transvectional alignment, and applies these concepts in the artificial neural network (ANN). To the best of our knowledge, no research has applied ANN in explaining the heterogeneity of both the supply-side and demand-side of a market in forming relational entity that consists of firms at all levels of the supply chain and the demand chain. The ANN offers a way of operationalizing the concept of supply-side segmentation. In toda...

CT-based manual segmentation and evaluation of paranasal sinuses.

Science.gov (United States)

Pirner, S; Tingelhoff, K; Wagner, I; Westphal, R; Rilk, M; Wahl, F M; Bootz, F; Eichhorn, Klaus W G

2009-04-01

Manual segmentation of computed tomography (CT) datasets was performed for robot-assisted endoscope movement during functional endoscopic sinus surgery (FESS). Segmented 3D models are needed for the robots' workspace definition. A total of 50 preselected CT datasets were each segmented in 150-200 coronal slices with 24 landmarks being set. Three different colors for segmentation represent diverse risk areas. Extension and volumetric measurements were performed. Three-dimensional reconstruction was generated after segmentation. Manual segmentation took 8-10 h for each CT dataset. The mean volumes were: right maxillary sinus 17.4 cm(3), left side 17.9 cm(3), right frontal sinus 4.2 cm(3), left side 4.0 cm(3), total frontal sinuses 7.9 cm(3), sphenoid sinus right side 5.3 cm(3), left side 5.5 cm(3), total sphenoid sinus volume 11.2 cm(3). Our manually segmented 3D-models present the patient's individual anatomy with a special focus on structures in danger according to the diverse colored risk areas. For safe robot assistance, the high-accuracy models represent an average of the population for anatomical variations, extension and volumetric measurements. They can be used as a database for automatic model-based segmentation. None of the segmentation methods so far described provide risk segmentation. The robot's maximum distance to the segmented border can be adjusted according to the differently colored areas.

Modeling of market segmentation for new IT product development

Science.gov (United States)

Nasiopoulos, Dimitrios K.; Sakas, Damianos P.; Vlachos, D. S.; Mavrogianni, Amanda

2015-02-01

Businesses from all Information Technology sectors use market segmentation[1] in their product development[2] and strategic planning[3]. Many studies have concluded that market segmentation is considered as the norm of modern marketing. With the rapid development of technology, customer needs are becoming increasingly diverse. These needs can no longer be satisfied by a mass marketing approach and follow one rule. IT Businesses can face with this diversity by pooling customers[4] with similar requirements and buying behavior and strength into segments. The result of the best choices about which segments are the most appropriate to serve can then be made, thus making the best of finite resources. Despite the attention which segmentation gathers and the resources that are invested in it, growing evidence suggests that businesses have problems operationalizing segmentation[5]. These problems take various forms. There may have been a rule that the segmentation process necessarily results in homogeneous groups of customers for whom appropriate marketing programs and procedures for dealing with them can be developed. Then the segmentation process, that a company follows, can fail. This increases concerns about what causes segmentation failure and how it might be overcome. To prevent the failure, we created a dynamic simulation model of market segmentation[6] based on the basic factors leading to this segmentation.

Skin Segmentation Based on Graph Cuts

Institute of Scientific and Technical Information of China (English)

HU Zhilan; WANG Guijin; LIN Xinggang; YAN Hong

2009-01-01

Skin segmentation is widely used in many computer vision tasks to improve automated visualiza-tion. This paper presents a graph cuts algorithm to segment arbitrary skin regions from images. The detected face is used to determine the foreground skin seeds and the background non-skin seeds with the color probability distributions for the foreground represented by a single Gaussian model and for the background by a Gaussian mixture model. The probability distribution of the image is used for noise suppression to alle-viate the influence of the background regions having skin-like colors. Finally, the skin is segmented by graph cuts, with the regional parameter y optimally selected to adapt to different images. Tests of the algorithm on many real wodd photographs show that the scheme accurately segments skin regions and is robust against illumination variations, individual skin variations, and cluttered backgrounds.

Mixed segmentation

DEFF Research Database (Denmark)

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

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...

Review methods for image segmentation from computed tomography images

International Nuclear Information System (INIS)

Mamat, Nurwahidah; Rahman, Wan Eny Zarina Wan Abdul; Soh, Shaharuddin Cik; Mahmud, Rozi

2014-01-01

Image segmentation is a challenging process in order to get the accuracy of segmentation, automation and robustness especially in medical images. There exist many segmentation methods that can be implemented to medical images but not all methods are suitable. For the medical purposes, the aims of image segmentation are to study the anatomical structure, identify the region of interest, measure tissue volume to measure growth of tumor and help in treatment planning prior to radiation therapy. In this paper, we present a review method for segmentation purposes using Computed Tomography (CT) images. CT images has their own characteristics that affect the ability to visualize anatomic structures and pathologic features such as blurring of the image and visual noise. The details about the methods, the goodness and the problem incurred in the methods will be defined and explained. It is necessary to know the suitable segmentation method in order to get accurate segmentation. This paper can be a guide to researcher to choose the suitable segmentation method especially in segmenting the images from CT scan

Dynamics in international market segmentation of new product growth

NARCIS (Netherlands)

Lemmens, A.; Croux, C.; Stremersch, S.

2012-01-01

Prior international segmentation studies have been static in that they have identified segments that remain stable over time. This paper shows that country segments in new product growth are intrinsically dynamic. We propose a semiparametric hidden Markov model to dynamically segment countries based

Region segmentation along image sequence

International Nuclear Information System (INIS)

Monchal, L.; Aubry, P.

1995-01-01

A method to extract regions in sequence of images is proposed. Regions are not matched from one image to the following one. The result of a region segmentation is used as an initialization to segment the following and image to track the region along the sequence. The image sequence is exploited as a spatio-temporal event. (authors). 12 refs., 8 figs

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.

Polarimetric Segmentation Using Wishart Test Statistic

DEFF Research Database (Denmark)

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

2002-01-01

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......) 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...

Technical report on semiautomatic segmentation using the Adobe Photoshop.

Science.gov (United States)

Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae; Lee, Yong Sook; Har, Dong-Hwan

2005-12-01

The purpose of this research is to enable users to semiautomatically segment the anatomical structures in magnetic resonance images (MRIs), computerized tomographs (CTs), and other medical images on a personal computer. The segmented images are used for making 3D images, which are helpful to medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was scanned to make 557 MRIs. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL and manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a similar manner, 13 anatomical structures in 8,590 anatomical images were segmented. Proper segmentation was verified by making 3D images from the segmented images. Semiautomatic segmentation using Adobe Photoshop is expected to be widely used for segmentation of anatomical structures in various medical images.

Intestinal myoelectric activity and contractile motility in dogs with a reversed jejunal segment after extensive small bowel resection.

Science.gov (United States)

Uchiyama, M; Iwafuchi, M; Ohsawa, Y; Yagi, M; Iinuma, Y; Ohtani, S

1992-06-01

To evaluate the functioning and effectiveness of a reversed jejunal segment after extensive small bowel resection, we continuously measured the postoperative bowel motility (using bipolar electrodes and/or contractile strain gage force transducers) in interdigestive and postprandial conscious dogs at 2 to 5 weeks after surgery. The fasting duodenal migrating myoelectric (or motor) complex (MMC) occurred at markedly longer intervals in dogs with a 20-cm reversed jejunal segment created after 75% to 80% extensive small bowel resection (group 3) than in dogs that received extensive resection alone (group 2) or dogs that underwent construction of a reversed jejunal segment without bowel resection (group 1). The MMC arising from the duodenum was often interrupted at the jejunum above the proximal anastomosis and did not migrate smoothly to the reversed segment or terminal ileum in group 3. In addition, brief small discordant contractions were frequent in the reversed segment and the jejunum above the proximal anastomosis in group 3. The duration of the postprandial period without duodenal MMC activity was significantly prolonged in groups 2 and 3. These results suggest that the transit time and passage of intestinal contents were delayed and that the periodical MMC was disturbed in group 3. The delay of transit time was due to prolongation of the interval between duodenal MMCs, the interruption of MMC propagation at the jejunum above the proximal anastomosis, the dominance of MMCs that followed the inherent anatomical continuity of the bowel, and discordant movements across the proximal anastomosis. Functional obstruction could be a potential problem in a 20-cm reversed jejunal segment inserted after extensive small bowel resection.

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...

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.

Image segmentation evaluation for very-large datasets

Science.gov (United States)

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

2016-03-01

With the advent of modern machine learning methods and fully automated image analysis there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. Current approaches of visual inspection and manual markings do not scale well to big data. We present a new approach that depends on fully automated algorithm outcomes for segmentation documentation, requires no manual marking, and provides quantitative evaluation for computer algorithms. The documentation of new image segmentations and new algorithm outcomes are achieved by visual inspection. The burden of visual inspection on large datasets is minimized by (a) customized visualizations for rapid review and (b) reducing the number of cases to be reviewed through analysis of quantitative segmentation evaluation. This method has been applied to a dataset of 7,440 whole-lung CT images for 6 different segmentation algorithms designed to fully automatically facilitate the measurement of a number of very important quantitative image biomarkers. The results indicate that we could achieve 93% to 99% successful segmentation for these algorithms on this relatively large image database. The presented evaluation method may be scaled to much larger image databases.

Automated 3D closed surface segmentation: application to vertebral body segmentation in CT images.

Science.gov (United States)

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

2016-05-01

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

Fast Segmentation of Colour Apple Image under All-Weather Natural Conditions for Vision Recognition of Picking Robots

Directory of Open Access Journals (Sweden)

Wei Ji

2016-02-01

Full Text Available In order to resolve the poor real-time performance problem of the normalized cut (Ncut method in apple vision recognition of picking robots, a fast segmentation method of colour apple images based on the adaptive mean-shift and Ncut methods is proposed in this paper. Firstly, the traditional Ncut method based on pixels is changed into the Ncut method based on regions by the adaptive mean-shift initial segmenting. In this way, the number of peaks and edges in the image is dramatically reduced and the computation speed is improved. Secondly, the image is divided into regional maps by extracting the R-B colour feature, which not only reduces the quantity of regions, but also to some extent overcomes the effect on illumination. On this basis, every region map is expressed by a region point, so the undirected graph of the R-B colour grey-level feature is attained. Finally, regarding the undirected graph as the input of Ncut, we construct the weight matrix W by region points and determine the number of clusters based on the decision-theoretic rough set. The adaptive clustering segmentation can be implemented by an Ncut algorithm. Experimental results show that the maximum segmentation error is 3% and the average recognition time is less than 0.7s, which can meet the requirements of a real-time picking robot.

Market segmentation by motivation: The case of Switzerland

OpenAIRE

Bieger, Thomas; Laesser, Christian

2002-01-01

This contribution is about the segmentation of mature travel markets, as exemplified by Switzerland. Based on an extensive and representative travel survey covering 2,000 households and more than 11,000 trips, a situational, motivation-based travel market segmentation is proposed. The clustering of motivations proves to be a valuable means to segment markets. The results reveal a diminishing role of socio-demographic segment descriptors. It is more the (anticipated) travel profile and the att...

Algorithms for Cytoplasm Segmentation of Fluorescence Labelled Cells

OpenAIRE

Carolina Wählby; Joakim Lindblad; Mikael Vondrus; Ewert Bengtsson; Lennart Björkesten

2002-01-01

Automatic cell segmentation has various applications in cytometry, and while the nucleus is often very distinct and easy to identify, the cytoplasm provides a lot more challenge. A new combination of image analysis algorithms for segmentation of cells imaged by fluorescence microscopy is presented. The algorithm consists of an image pre?processing step, a general segmentation and merging step followed by a segmentation quality measurement. The quality measurement consists of a statistical ana...

Interactive segmentation: a scalable superpixel-based method

Science.gov (United States)

Mathieu, Bérengère; Crouzil, Alain; Puel, Jean-Baptiste

2017-11-01

This paper addresses the problem of interactive multiclass segmentation of images. We propose a fast and efficient new interactive segmentation method called superpixel α fusion (SαF). From a few strokes drawn by a user over an image, this method extracts relevant semantic objects. To get a fast calculation and an accurate segmentation, SαF uses superpixel oversegmentation and support vector machine classification. We compare SαF with competing algorithms by evaluating its performances on reference benchmarks. We also suggest four new datasets to evaluate the scalability of interactive segmentation methods, using images from some thousand to several million pixels. We conclude with two applications of SαF.

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...

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).

An interactive medical image segmentation framework using iterative refinement.

Science.gov (United States)

Kalshetti, Pratik; Bundele, Manas; Rahangdale, Parag; Jangra, Dinesh; Chattopadhyay, Chiranjoy; Harit, Gaurav; Elhence, Abhay

2017-04-01

Segmentation is often performed on medical images for identifying diseases in clinical evaluation. Hence it has become one of the major research areas. Conventional image segmentation techniques are unable to provide satisfactory segmentation results for medical images as they contain irregularities. They need to be pre-processed before segmentation. In order to obtain the most suitable method for medical image segmentation, we propose MIST (Medical Image Segmentation Tool), a two stage algorithm. The first stage automatically generates a binary marker image of the region of interest using mathematical morphology. This marker serves as the mask image for the second stage which uses GrabCut to yield an efficient segmented result. The obtained result can be further refined by user interaction, which can be done using the proposed Graphical User Interface (GUI). Experimental results show that the proposed method is accurate and provides satisfactory segmentation results with minimum user interaction on medical as well as natural images. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automatic lung segmentation in the presence of alveolar collapse

Directory of Open Access Journals (Sweden)

Noshadi Areg

2017-09-01

Full Text Available Lung ventilation and perfusion analyses using chest imaging methods require a correct segmentation of the lung to offer anatomical landmarks for the physiological data. An automatic segmentation approach simplifies and accelerates the analysis. However, the segmentation of the lungs has shown to be difficult if collapsed areas are present that tend to share similar gray values with surrounding non-pulmonary tissue. Our goal was to develop an automatic segmentation algorithm that is able to approximate dorsal lung boundaries even if alveolar collapse is present in the dependent lung areas adjacent to the pleura. Computed tomography data acquired in five supine pigs with injured lungs were used for this purpose. First, healthy lung tissue was segmented using a standard 3D region growing algorithm. Further, the bones in the chest wall surrounding the lungs were segmented to find the contact points of ribs and pleura. Artificial boundaries of the dorsal lung were set by spline interpolation through these contact points. Segmentation masks of the entire lung including the collapsed regions were created by combining the splines with the segmentation masks of the healthy lung tissue through multiple morphological operations. The automatically segmented images were then evaluated by comparing them to manual segmentations and determining the Dice similarity coefficients (DSC as a similarity measure. The developed method was able to accurately segment the lungs including the collapsed regions (DSCs over 0.96.

OASIS is Automated Statistical Inference for Segmentation, with applications to multiple sclerosis lesion segmentation in MRI.

Science.gov (United States)

Sweeney, Elizabeth M; Shinohara, Russell T; Shiee, Navid; Mateen, Farrah J; Chudgar, Avni A; Cuzzocreo, Jennifer L; Calabresi, Peter A; Pham, Dzung L; Reich, Daniel S; Crainiceanu, Ciprian M

2013-01-01

Magnetic resonance imaging (MRI) can be used to detect lesions in the brains of multiple sclerosis (MS) patients and is essential for diagnosing the disease and monitoring its progression. In practice, lesion load is often quantified by either manual or semi-automated segmentation of MRI, which is time-consuming, costly, and associated with large inter- and intra-observer variability. We propose OASIS is Automated Statistical Inference for Segmentation (OASIS), an automated statistical method for segmenting MS lesions in MRI studies. We use logistic regression models incorporating multiple MRI modalities to estimate voxel-level probabilities of lesion presence. Intensity-normalized T1-weighted, T2-weighted, fluid-attenuated inversion recovery and proton density volumes from 131 MRI studies (98 MS subjects, 33 healthy subjects) with manual lesion segmentations were used to train and validate our model. Within this set, OASIS detected lesions with a partial area under the receiver operating characteristic curve for clinically relevant false positive rates of 1% and below of 0.59% (95% CI; [0.50%, 0.67%]) at the voxel level. An experienced MS neuroradiologist compared these segmentations to those produced by LesionTOADS, an image segmentation software that provides segmentation of both lesions and normal brain structures. For lesions, OASIS out-performed LesionTOADS in 74% (95% CI: [65%, 82%]) of cases for the 98 MS subjects. To further validate the method, we applied OASIS to 169 MRI studies acquired at a separate center. The neuroradiologist again compared the OASIS segmentations to those from LesionTOADS. For lesions, OASIS ranked higher than LesionTOADS in 77% (95% CI: [71%, 83%]) of cases. For a randomly selected subset of 50 of these studies, one additional radiologist and one neurologist also scored the images. Within this set, the neuroradiologist ranked OASIS higher than LesionTOADS in 76% (95% CI: [64%, 88%]) of cases, the neurologist 66% (95% CI: [52%, 78

Automated analysis of high-throughput B-cell sequencing data reveals a high frequency of novel immunoglobulin V gene segment alleles.

Science.gov (United States)

Gadala-Maria, Daniel; Yaari, Gur; Uduman, Mohamed; Kleinstein, Steven H

2015-02-24

Individual variation in germline and expressed B-cell immunoglobulin (Ig) repertoires has been associated with aging, disease susceptibility, and differential response to infection and vaccination. Repertoire properties can now be studied at large-scale through next-generation sequencing of rearranged Ig genes. Accurate analysis of these repertoire-sequencing (Rep-Seq) data requires identifying the germline variable (V), diversity (D), and joining (J) gene segments used by each Ig sequence. Current V(D)J assignment methods work by aligning sequences to a database of known germline V(D)J segment alleles. However, existing databases are likely to be incomplete and novel polymorphisms are hard to differentiate from the frequent occurrence of somatic hypermutations in Ig sequences. Here we develop a Tool for Ig Genotype Elucidation via Rep-Seq (TIgGER). TIgGER analyzes mutation patterns in Rep-Seq data to identify novel V segment alleles, and also constructs a personalized germline database containing the specific set of alleles carried by a subject. This information is then used to improve the initial V segment assignments from existing tools, like IMGT/HighV-QUEST. The application of TIgGER to Rep-Seq data from seven subjects identified 11 novel V segment alleles, including at least one in every subject examined. These novel alleles constituted 13% of the total number of unique alleles in these subjects, and impacted 3% of V(D)J segment assignments. These results reinforce the highly polymorphic nature of human Ig V genes, and suggest that many novel alleles remain to be discovered. The integration of TIgGER into Rep-Seq processing pipelines will increase the accuracy of V segment assignments, thus improving B-cell repertoire analyses.

Marketing ambulatory care to women: a segmentation approach.

Science.gov (United States)

Harrell, G D; Fors, M F

1985-01-01

Although significant changes are occurring in health care delivery, in many instances the new offerings are not based on a clear understanding of market segments being served. This exploratory study suggests that important differences may exist among women with regard to health care selection. Five major women's segments are identified for consideration by health care executives in developing marketing strategies. Additional research is suggested to confirm this segmentation hypothesis, validate segmental differences and quantify the findings.

Brain MR image segmentation using NAMS in pseudo-color.

Science.gov (United States)

Li, Hua; Chen, Chuanbo; Fang, Shaohong; Zhao, Shengrong

2017-12-01

Image segmentation plays a crucial role in various biomedical applications. In general, the segmentation of brain Magnetic Resonance (MR) images is mainly used to represent the image with several homogeneous regions instead of pixels for surgical analyzing and planning. This paper proposes a new approach for segmenting MR brain images by using pseudo-color based segmentation with Non-symmetry and Anti-packing Model with Squares (NAMS). First of all, the NAMS model is presented. The model can represent the image with sub-patterns to keep the image content and largely reduce the data redundancy. Second, the key idea is proposed that convert the original gray-scale brain MR image into a pseudo-colored image and then segment the pseudo-colored image with NAMS model. The pseudo-colored image can enhance the color contrast in different tissues in brain MR images, which can improve the precision of segmentation as well as directly visual perceptional distinction. Experimental results indicate that compared with other brain MR image segmentation methods, the proposed NAMS based pseudo-color segmentation method performs more excellent in not only segmenting precisely but also saving storage.

Automated Multi-Atlas Segmentation of Hippocampal and Extrahippocampal Subregions in Alzheimer's Disease at 3T and 7T: What Atlas Composition Works Best?

Science.gov (United States)

Xie, Long; Shinohara, Russell T; Ittyerah, Ranjit; Kuijf, Hugo J; Pluta, John B; Blom, Kim; Kooistra, Minke; Reijmer, Yael D; Koek, Huiberdina L; Zwanenburg, Jaco J M; Wang, Hongzhi; Luijten, Peter R; Geerlings, Mirjam I; Das, Sandhitsu R; Biessels, Geert Jan; Wolk, David A; Yushkevich, Paul A; Wisse, Laura E M

2018-01-01

Multi-atlas segmentation, a popular technique implemented in the Automated Segmentation of Hippocampal Subfields (ASHS) software, utilizes multiple expert-labelled images ("atlases") to delineate medial temporal lobe substructures. This multi-atlas method is increasingly being employed in early Alzheimer's disease (AD) research, it is therefore becoming important to know how the construction of the atlas set in terms of proportions of controls and patients with mild cognitive impairment (MCI) and/or AD affects segmentation accuracy. To evaluate whether the proportion of controls in the training sets affects the segmentation accuracy of both controls and patients with MCI and/or early AD at 3T and 7T. We performed cross-validation experiments varying the proportion of control subjects in the training set, ranging from a patient-only to a control-only set. Segmentation accuracy of the test set was evaluated by the Dice similarity coeffiecient (DSC). A two-stage statistical analysis was applied to determine whether atlas composition is linked to segmentation accuracy in control subjects and patients, for 3T and 7T. The different atlas compositions did not significantly affect segmentation accuracy at 3T and for patients at 7T. For controls at 7T, including more control subjects in the training set significantly improves the segmentation accuracy, but only marginally, with the maximum of 0.0003 DSC improvement per percent increment of control subject in the training set. ASHS is robust in this study, and the results indicate that future studies investigating hippocampal subfields in early AD populations can be flexible in the selection of their atlas compositions.

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.

Aging and the segmentation of narrative film.

Science.gov (United States)

Kurby, Christopher A; Asiala, Lillian K E; Mills, Steven R

2014-01-01

The perception of event structure in continuous activity is important for everyday comprehension. Although the segmentation of experience into events is a normal concomitant of perceptual processing, previous research has shown age differences in the ability to perceive structure in naturalistic activity, such as a movie of someone washing a car. However, past research has also shown that older adults have a preserved ability to comprehend events in narrative text, which suggests that narrative may improve the event processing of older adults. This study tested whether there are age differences in event segmentation at the intersection of continuous activity and narrative: narrative film. Younger and older adults watched and segmented a narrative film, The Red Balloon, into coarse and fine events. Changes in situational features, such as changes in characters, goals, and objects predicted segmentation. Analyses revealed little age-difference in segmentation behavior. This suggests the possibility that narrative structure supports event understanding for older adults.

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.

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

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...

Speaker Segmentation and Clustering Using Gender Information

Science.gov (United States)

2006-02-01

used in the first stages of segmentation forder information in the clustering of the opposite-gender speaker diarization of news broadcasts. files, the...AFRL-HE-WP-TP-2006-0026 AIR FORCE RESEARCH LABORATORY Speaker Segmentation and Clustering Using Gender Information Brian M. Ore General Dynamics...COVERED (From - To) February 2006 ProceedinLgs 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Speaker Segmentation and Clustering Using Gender Information 5b

Automated vessel shadow segmentation of fovea-centered spectral-domain images from multiple OCT devices

Science.gov (United States)

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

2014-03-01

Spectral-domain Optical Coherence Tomography (SD-OCT) is a non-invasive modality for acquiring high reso- lution, three-dimensional (3D) cross sectional volumetric images of the retina and the subretinal layers. SD-OCT also allows the detailed imaging of retinal pathology, aiding clinicians in the diagnosis of sight degrading diseases such as age-related macular degeneration (AMD) and glaucoma.1 Disease diagnosis, assessment, and treatment requires a patient to undergo multiple OCT scans, possibly using different scanning devices, to accurately and precisely gauge disease activity, progression and treatment success. However, the use of OCT imaging devices from different vendors, combined with patient movement may result in poor scan spatial correlation, potentially leading to incorrect patient diagnosis or treatment analysis. Image registration can be used to precisely compare disease states by registering differing 3D scans to one another. In order to align 3D scans from different time- points and vendors using registration, landmarks are required, the most obvious being the retinal vasculature. Presented here is a fully automated cross-vendor method to acquire retina vessel locations for OCT registration from fovea centred 3D SD-OCT scans based on vessel shadows. Noise filtered OCT scans are flattened based on vendor retinal layer segmentation, to extract the retinal pigment epithelium (RPE) layer of the retina. Voxel based layer profile analysis and k-means clustering is used to extract candidate vessel shadow regions from the RPE layer. In conjunction, the extracted RPE layers are combined to generate a projection image featuring all candidate vessel shadows. Image processing methods for vessel segmentation of the OCT constructed projection image are then applied to optimize the accuracy of OCT vessel shadow segmentation through the removal of false positive shadow regions such as those caused by exudates and cysts. Validation of segmented vessel shadows uses

ONE SEGMENT OF THE BULGARIAN-ENGLISH PAREMIOLOGICAL CORE

Directory of Open Access Journals (Sweden)

KOTOVA M.Y.

2015-12-01

Full Text Available The English proverbial parallels of the Russian-Bulgarian paremiological core are analysed in the article. The comparison of current Bulgarian proverbs and their English proverbial parallels is based upon the material of the author’s multi-lingual dictionary and her collection of Bulgarian-Russian proverbial parallels published as a result of her sociolinguistic paremiological experiment from 2003 (on the basis of 100 questionnaires filled by 100 Bulgarian respondents and supported in 2013 with the current Bulgarian contexts from the Bulgarian Internet. The number of 'alive' Bulgarian-English proverbial parallels, constructed from the paremiological questionnaires (pointed out by 70 % - 100 % respondents is 62, the biggest part of which belongs to the proverbial parallels with a similar inner form (35, i.e. the biggest part of the segment of the current Bulgarian-English paremiological core (reflecting the Russian paremiological minimum contains proverbial parallels with a similar inner form.

Analysis of the Word-Initial Segment with Reference to Lemmatising Zulu Nasal Nouns

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M.H. Mpungose

2012-09-01

Full Text Available

The process of lemmatising nasal nouns in the Zulu lexicon is problematic. The traditional method is to lemmatise a Zulu lexical noun by etymological noun-stem. This practice creates difficulties in harmonising lexical nouns with their syntactic application. Most authors and dictionary-makers are inconsistent in identifying the word-initial segment which determines the letter of the alphabet under which the lexical noun should be included. Consequently, dictionary users do not find Zulu dictionaries user-friendly. This article therefore proposes the principle of "a noun without initial vowel" as a method for lemmatising Zulu nasal nouns. It concludes that it is not necessary to delve into the derivational history of a lexical noun, but rather to focus on the product of the operation of morphophonological rules. The article also suggests the need to identify the distinctiveness of the segments of a syllable and to acknowledge that identical forms of a segment do occur at different segmental positions (initial, medial and final. Finally it is argued that the Zulu nasal noun class prefix is constructed according to an open syllable pattern defined by a general CV-formula based on a VCV noun prefix open syllable pattern.

Keywords: adjoined letter; compound; composite; consonant; element; etymological; evolutionary; homorganic; initial; intravowel; lemma; lemmatise; lexical; morphophonological; nasal; noun class prefix; segment; syllable; vowel

Identifying food-related life style segments by a cross-culturally valid scaling device

DEFF Research Database (Denmark)

Brunsø, Karen; Grunert, Klaus G.

1994-01-01

-related life style in a cross-culturally valid way. To this end, we have col-lected a pool of 202 items, collected data in three countries, and have con-structed scales based on cross-culturally stable patterns. These scales have then been subjected to a number of tests of reliability and vali-dity. We have...... then applied the set of scales to a fourth country, Germany, based on a representative sample of 1000 respondents. The scales had, with a fe exceptions, moderately good reliabilities. A cluster ana-ly-sis led to the identification of 5 segments, which differed on all 23 scales....

Segmentation and Quantification for Angle-Closure Glaucoma Assessment in Anterior Segment OCT.

Science.gov (United States)

Fu, Huazhu; Xu, Yanwu; Lin, Stephen; Zhang, Xiaoqin; Wong, Damon Wing Kee; Liu, Jiang; Frangi, Alejandro F; Baskaran, Mani; Aung, Tin

2017-09-01

Angle-closure glaucoma is a major cause of irreversible visual impairment and can be identified by measuring the anterior chamber angle (ACA) of the eye. The ACA can be viewed clearly through anterior segment optical coherence tomography (AS-OCT), but the imaging characteristics and the shapes and locations of major ocular structures can vary significantly among different AS-OCT modalities, thus complicating image analysis. To address this problem, we propose a data-driven approach for automatic AS-OCT structure segmentation, measurement, and screening. Our technique first estimates initial markers in the eye through label transfer from a hand-labeled exemplar data set, whose images are collected over different patients and AS-OCT modalities. These initial markers are then refined by using a graph-based smoothing method that is guided by AS-OCT structural information. These markers facilitate segmentation of major clinical structures, which are used to recover standard clinical parameters. These parameters can be used not only to support clinicians in making anatomical assessments, but also to serve as features for detecting anterior angle closure in automatic glaucoma screening algorithms. Experiments on Visante AS-OCT and Cirrus high-definition-OCT data sets demonstrate the effectiveness of our approach.

New developments in segment ancillary logic for FASTBUS

International Nuclear Information System (INIS)

Walz, H.V.; Bertolucci, B.

1983-01-01

Segment Ancillary Logic hardware for FASTBUS systems provides logical functions required in common by all devices attached to a segment. It controls the execution of arbitration cycles, and geographical address cycles, and generates the system handshake responses for broadcast operations. The mandatory requirements for Segment Ancillary Logic in the FASTBUS specifications are reviewed. A detailed implementation based on ECL logic is described, and the hardware to be used on an ECL cable segment for an experimental FASTBUS system at SLAC is shown

(A new application in segment reporting: IFRS 8)

OpenAIRE

Arsoy, Aylin Poroy

2008-01-01

IFRS 8 Operating Segments issued by the International Accounting Standards Board (IASB) on December 30th, 2006, changes the requirements of segment reporting. IAS 14 will cease to be effective when IFRS 8 will become effective from the beginning of 2009. After then, companies will be required to follow IFRS 8 for their segment reporting purposes. The main difference between IFRS 8 and IAS 14 is the approach that is adopted while determining the reportable segments. Also, it should be mentione...

Video segmentation using keywords

Science.gov (United States)

Ton-That, Vinh; Vong, Chi-Tai; Nguyen-Dao, Xuan-Truong; Tran, Minh-Triet

2018-04-01

At DAVIS-2016 Challenge, many state-of-art video segmentation methods achieve potential results, but they still much depend on annotated frames to distinguish between background and foreground. It takes a lot of time and efforts to create these frames exactly. In this paper, we introduce a method to segment objects from video based on keywords given by user. First, we use a real-time object detection system - YOLOv2 to identify regions containing objects that have labels match with the given keywords in the first frame. Then, for each region identified from the previous step, we use Pyramid Scene Parsing Network to assign each pixel as foreground or background. These frames can be used as input frames for Object Flow algorithm to perform segmentation on entire video. We conduct experiments on a subset of DAVIS-2016 dataset in half the size of its original size, which shows that our method can handle many popular classes in PASCAL VOC 2012 dataset with acceptable accuracy, about 75.03%. We suggest widely testing by combining other methods to improve this result in the future.

Segmenting patients and physicians using preferences from discrete choice experiments.

Science.gov (United States)

Deal, Ken

2014-01-01

People often form groups or segments that have similar interests and needs and seek similar benefits from health providers. Health organizations need to understand whether the same health treatments, prevention programs, services, and products should be applied to everyone in the relevant population or whether different treatments need to be provided to each of several segments that are relatively homogeneous internally but heterogeneous among segments. Our objective was to explain the purposes, benefits, and methods of segmentation for health organizations, and to illustrate the process of segmenting health populations based on preference coefficients from a discrete choice conjoint experiment (DCE) using an example study of prevention of cyberbullying among university students. We followed a two-level procedure for investigating segmentation incorporating several methods for forming segments in Level 1 using DCE preference coefficients and testing their quality, reproducibility, and usability by health decision makers. Covariates (demographic, behavioral, lifestyle, and health state variables) were included in Level 2 to further evaluate quality and to support the scoring of large databases and developing typing tools for assigning those in the relevant population, but not in the sample, to the segments. Several segmentation solution candidates were found during the Level 1 analysis, and the relationship of the preference coefficients to the segments was investigated using predictive methods. Those segmentations were tested for their quality and reproducibility and three were found to be very close in quality. While one seemed better than others in the Level 1 analysis, another was very similar in quality and proved ultimately better in predicting segment membership using covariates in Level 2. The two segments in the final solution were profiled for attributes that would support the development and acceptance of cyberbullying prevention programs among university

Short segment search method for phylogenetic analysis using nested sliding windows

Science.gov (United States)

Iskandar, A. A.; Bustamam, A.; Trimarsanto, H.

2017-10-01

To analyze phylogenetics in Bioinformatics, coding DNA sequences (CDS) segment is needed for maximal accuracy. However, analysis by CDS cost a lot of time and money, so a short representative segment by CDS, which is envelope protein segment or non-structural 3 (NS3) segment is necessary. After sliding window is implemented, a better short segment than envelope protein segment and NS3 is found. This paper will discuss a mathematical method to analyze sequences using nested sliding window to find a short segment which is representative for the whole genome. The result shows that our method can find a short segment which more representative about 6.57% in topological view to CDS segment than an Envelope segment or NS3 segment.

Simultaneous tomographic reconstruction and segmentation with class priors

DEFF Research Database (Denmark)

Romanov, Mikhail; Dahl, Anders Bjorholm; Dong, Yiqiu

2015-01-01

are combined to produce a reconstruction that is identical to the segmentation. We consider instead a hybrid approach that simultaneously produces both a reconstructed image and segmentation. We incorporate priors about the desired classes of the segmentation through a Hidden Markov Measure Field Model, and we...

SVM Pixel Classification on Colour Image Segmentation

Science.gov (United States)

Barui, Subhrajit; Latha, S.; Samiappan, Dhanalakshmi; Muthu, P.

2018-04-01

The aim of image segmentation is to simplify the representation of an image with the help of cluster pixels into something meaningful to analyze. Segmentation is typically used to locate boundaries and curves in an image, precisely to label every pixel in an image to give each pixel an independent identity. SVM pixel classification on colour image segmentation is the topic highlighted in this paper. It holds useful application in the field of concept based image retrieval, machine vision, medical imaging and object detection. The process is accomplished step by step. At first we need to recognize the type of colour and the texture used as an input to the SVM classifier. These inputs are extracted via local spatial similarity measure model and Steerable filter also known as Gabon Filter. It is then trained by using FCM (Fuzzy C-Means). Both the pixel level information of the image and the ability of the SVM Classifier undergoes some sophisticated algorithm to form the final image. The method has a well developed segmented image and efficiency with respect to increased quality and faster processing of the segmented image compared with the other segmentation methods proposed earlier. One of the latest application result is the Light L16 camera.

Classifier Directed Data Hybridization for Geographic Sample Supervised Segment Generation

Directory of Open Access Journals (Sweden)

Christoff Fourie

2014-11-01

Full Text Available Quality segment generation is a well-known challenge and research objective within Geographic Object-based Image Analysis (GEOBIA. Although methodological avenues within GEOBIA are diverse, segmentation commonly plays a central role in most approaches, influencing and being influenced by surrounding processes. A general approach using supervised quality measures, specifically user provided reference segments, suggest casting the parameters of a given segmentation algorithm as a multidimensional search problem. In such a sample supervised segment generation approach, spatial metrics observing the user provided reference segments may drive the search process. The search is commonly performed by metaheuristics. A novel sample supervised segment generation approach is presented in this work, where the spectral content of provided reference segments is queried. A one-class classification process using spectral information from inside the provided reference segments is used to generate a probability image, which in turn is employed to direct a hybridization of the original input imagery. Segmentation is performed on such a hybrid image. These processes are adjustable, interdependent and form a part of the search problem. Results are presented detailing the performances of four method variants compared to the generic sample supervised segment generation approach, under various conditions in terms of resultant segment quality, required computing time and search process characteristics. Multiple metrics, metaheuristics and segmentation algorithms are tested with this approach. Using the spectral data contained within user provided reference segments to tailor the output generally improves the results in the investigated problem contexts, but at the expense of additional required computing time.

Methods for recognition and segmentation of active fault

International Nuclear Information System (INIS)

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

2000-03-01

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

Portuguese Consumers’ Green Purchase Behavior: An Analysis of its Antecedents and a Proposal of Segmentation

Directory of Open Access Journals (Sweden)

Paulo Ribeiro Cardoso

2017-06-01

Full Text Available This study analyzes how “Knowledge about environmental problems,” "Perceived consumer effectiveness,” and "Recycling behavior” can predict “Reported purchase of green products in general,” and “Reported purchase of specific green products.”  Another objective of this study is to identify different consumer segments based on antecedents of green purchasing behavior, observing demographic profiles and willingness to buy this type of products.  The data was collected in Portugal with the use of an online survey and the instrument was composed of five scales, adapted from previous studies.  The results confirm the existence of a positive relationship between the constructs.  It is also possible to identify three segments of consumers: “Less involved,” “Moderate,” and “Ecologists.”  This study has some practical implications, showing that consumption of green products can be stimulated if consumers are more aware of environmental problems and understand the importance of their individual behavior to prevent them.

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

LIMB-SEGMENT SELECTION IN DRAWING BEHAVIOR

NARCIS (Netherlands)

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