Sport-Specific Training Targeting the Proximal Segments and Throwing Velocity in Collegiate Throwing Athletes

Science.gov (United States)

Palmer, Thomas; Uhl, Timothy L.; Howell, Dana; Hewett, Timothy E.; Viele, Kert; Mattacola, Carl G.

2015-01-01

Context The ability to generate, absorb, and transmit forces through the proximal segments of the pelvis, spine, and trunk has been proposed to influence sport performance, yet traditional training techniques targeting the proximal segments have had limited success improving sport-specific performance. Objective To investigate the effects of a traditional endurance-training program and a sport-specific power-training program targeting the muscles that support the proximal segments and throwing velocity. Design Randomized controlled clinical trial. Setting University research laboratory and gymnasium. Patients or Other Participants A total of 46 (age = 20 ± 1.3 years, height = 175.7 ± 8.7 cm) healthy National Collegiate Athletic Association Division III female softball (n = 17) and male baseball (n = 29) players. Intervention(s) Blocked stratification for sex and position was used to randomly assign participants to 1 of 2 training groups for 7 weeks: a traditional endurance-training group (ET group; n = 21) or a power-stability–training group (PS group; n = 25). Mean Outcome Measure(s) The change score in peak throwing velocity (km/h) normalized for body weight (BW; kilograms) and change score in tests that challenge the muscles of the proximal segments normalized for BW (kilograms). We used 2-tailed independent-samples t tests to compare differences between the change scores. Results The peak throwing velocity (ET group = 0.01 ± 0.1 km/h/kg of BW, PS group = 0.08 ± 0.03 km/h/kg of BW; P < .001) and muscle power outputs for the chop (ET group = 0.22 ± 0.91 W/kg of BW, PS group = 1.3 ± 0.91 W/kg of BW; P < .001) and lift (ET group = 0.59 ± 0.67 W/kg of BW, PS group = 1.4 ± 0.87 W/kg of BW; P < .001) tests were higher at postintervention in the PT than in the ET group. Conclusions An improvement in throwing velocity occurred simultaneously with measures of muscular endurance and power after a sport-specific training regimen targeting the proximal segments

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...

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...

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

Dynamic Parameter Identification of Subject-Specific Body Segment Parameters Using Robotics Formalism: Case Study Head Complex.

Science.gov (United States)

Díaz-Rodríguez, Miguel; Valera, Angel; Page, Alvaro; Besa, Antonio; Mata, Vicente

2016-05-01

Accurate knowledge of body segment inertia parameters (BSIP) improves the assessment of dynamic analysis based on biomechanical models, which is of paramount importance in fields such as sport activities or impact crash test. Early approaches for BSIP identification rely on the experiments conducted on cadavers or through imaging techniques conducted on living subjects. Recent approaches for BSIP identification rely on inverse dynamic modeling. However, most of the approaches are focused on the entire body, and verification of BSIP for dynamic analysis for distal segment or chain of segments, which has proven to be of significant importance in impact test studies, is rarely established. Previous studies have suggested that BSIP should be obtained by using subject-specific identification techniques. To this end, our paper develops a novel approach for estimating subject-specific BSIP based on static and dynamics identification models (SIM, DIM). We test the validity of SIM and DIM by comparing the results using parameters obtained from a regression model proposed by De Leva (1996, "Adjustments to Zatsiorsky-Seluyanov's Segment Inertia Parameters," J. Biomech., 29(9), pp. 1223-1230). Both SIM and DIM are developed considering robotics formalism. First, the static model allows the mass and center of gravity (COG) to be estimated. Second, the results from the static model are included in the dynamics equation allowing us to estimate the moment of inertia (MOI). As a case study, we applied the approach to evaluate the dynamics modeling of the head complex. Findings provide some insight into the validity not only of the proposed method but also of the application proposed by De Leva (1996, "Adjustments to Zatsiorsky-Seluyanov's Segment Inertia Parameters," J. Biomech., 29(9), pp. 1223-1230) for dynamic modeling of body segments.

Automatic segmentation of thoracic and pelvic CT images for radiotherapy planning using implicit anatomic knowledge and organ-specific segmentation strategies

International Nuclear Information System (INIS)

Haas, B; Coradi, T; Scholz, M; Kunz, P; Huber, M; Oppitz, U; Andre, L; Lengkeek, V; Huyskens, D; Esch, A van; Reddick, R

2008-01-01

structures on the scale 1-excellent (no corrections necessary, maximum time saving), 2-good (corrections necessary for up to 1/3 of slices), 3-acceptable (major corrections necessary, but still time saving), 4-not acceptable (manual redrawing more efficient, no time saving). A rating ≤ 3 indicates a time saving in the treatment planning process and was given for pelvis segmentation in 70% (I) and 68% (II) of the cases, with average ratings 2.9 (I) and 2.6 (II). For the thorax, a rating ≤ 3 was given in 94% and 91% of the cases, with average ratings 2.1 and 1.9, respectively. For quantitative validation, automatically generated structures were compared geometrically in 2D and 3D to manually drawn structures created by experts on seven randomly selected cases. The quantitative validation was limited to pelvis structures. The results indicate that the accuracy of the algorithms is within the bandwidth of manual segmentation by experts, except for specific erroneous situations. Even though manual review and corrections of automatically segmented structures are still mandatory, it can be expected that due to the speed of the presented software and the quality of its results, its introduction in the radiotherapy treatment planning process will lead to a considerable amount of time being saved

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.

What are Segments in Google Analytics

Science.gov (United States)

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

Computed tomography landmark-based semi-automated mesh morphing and mapping techniques: generation of patient specific models of the human pelvis without segmentation.

Science.gov (United States)

Salo, Zoryana; Beek, Maarten; Wright, David; Whyne, Cari Marisa

2015-04-13

Current methods for the development of pelvic finite element (FE) models generally are based upon specimen specific computed tomography (CT) data. This approach has traditionally required segmentation of CT data sets, which is time consuming and necessitates high levels of user intervention due to the complex pelvic anatomy. The purpose of this research was to develop and assess CT landmark-based semi-automated mesh morphing and mapping techniques to aid the generation and mechanical analysis of specimen-specific FE models of the pelvis without the need for segmentation. A specimen-specific pelvic FE model (source) was created using traditional segmentation methods and morphed onto a CT scan of a different (target) pelvis using a landmark-based method. The morphed model was then refined through mesh mapping by moving the nodes to the bone boundary. A second target model was created using traditional segmentation techniques. CT intensity based material properties were assigned to the morphed/mapped model and to the traditionally segmented target models. Models were analyzed to evaluate their geometric concurrency and strain patterns. Strains generated in a double-leg stance configuration were compared to experimental strain gauge data generated from the same target cadaver pelvis. CT landmark-based morphing and mapping techniques were efficiently applied to create a geometrically multifaceted specimen-specific pelvic FE model, which was similar to the traditionally segmented target model and better replicated the experimental strain results (R(2)=0.873). This study has shown that mesh morphing and mapping represents an efficient validated approach for pelvic FE model generation without the need for segmentation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Segmenting Chinese Tourists by the Expected Experience at Theme Parks

Directory of Open Access Journals (Sweden)

Shan Chen

2013-08-01

Full Text Available In this paper, we propose an experiential approach to tourist segmentation aimed at overcoming the limits of both socio-demographic and context-specific approaches widely adopted in the literature and in practice. In this study, segmentation is carried out based upon the expected experiences of Chinese tourists at the Shanghai World Exposition. The segmentation reveals four tourist clusters with different interests in relation to their experiences in visiting the World Exposition. The clusters showed insignificant differences in the demographics but proved to be powerfully discriminant in determining tourists’ satisfaction and loyalty, which affirms the potential of the tourist experience being a segmenting variable. Moreover, thanks to the analysis, an evaluation of the Shanghai World Exposition’s success in terms of visitors’ satisfaction is provided.

Host-Specific and Segment-Specific Evolutionary Dynamics of Avian and Human Influenza A Viruses: A Systematic Review

KAUST Repository

Kim, Kiyeon

2016-01-13

Understanding the evolutionary dynamics of influenza viruses is essential to control both avian and human influenza. Here, we analyze host-specific and segment-specific Tajima’s D trends of influenza A virus through a systematic review using viral sequences registered in the National Center for Biotechnology Information. To avoid bias from viral population subdivision, viral sequences were stratified according to their sampling locations and sampling years. As a result, we obtained a total of 580 datasets each of which consists of nucleotide sequences of influenza A viruses isolated from a single population of hosts at a single sampling site within a single year. By analyzing nucleotide sequences in the datasets, we found that Tajima’s D values of viral sequences were different depending on hosts and gene segments. Tajima’s D values of viruses isolated from chicken and human samples showed negative, suggesting purifying selection or a rapid population growth of the viruses. The negative Tajima’s D values in rapidly growing viral population were also observed in computer simulations. Tajima’s D values of PB2, PB1, PA, NP, and M genes of the viruses circulating in wild mallards were close to zero, suggesting that these genes have undergone neutral selection in constant-sized population. On the other hand, Tajima’s D values of HA and NA genes of these viruses were positive, indicating HA and NA have undergone balancing selection in wild mallards. Taken together, these results indicated the existence of unknown factors that maintain viral subtypes in wild mallards.

Host-Specific and Segment-Specific Evolutionary Dynamics of Avian and Human Influenza A Viruses: A Systematic Review

KAUST Repository

Kim, Kiyeon; Omori, Ryosuke; Ueno, Keisuke; Iida, Sayaka; Ito, Kimihito

2016-01-01

Understanding the evolutionary dynamics of influenza viruses is essential to control both avian and human influenza. Here, we analyze host-specific and segment-specific Tajima’s D trends of influenza A virus through a systematic review using viral sequences registered in the National Center for Biotechnology Information. To avoid bias from viral population subdivision, viral sequences were stratified according to their sampling locations and sampling years. As a result, we obtained a total of 580 datasets each of which consists of nucleotide sequences of influenza A viruses isolated from a single population of hosts at a single sampling site within a single year. By analyzing nucleotide sequences in the datasets, we found that Tajima’s D values of viral sequences were different depending on hosts and gene segments. Tajima’s D values of viruses isolated from chicken and human samples showed negative, suggesting purifying selection or a rapid population growth of the viruses. The negative Tajima’s D values in rapidly growing viral population were also observed in computer simulations. Tajima’s D values of PB2, PB1, PA, NP, and M genes of the viruses circulating in wild mallards were close to zero, suggesting that these genes have undergone neutral selection in constant-sized population. On the other hand, Tajima’s D values of HA and NA genes of these viruses were positive, indicating HA and NA have undergone balancing selection in wild mallards. Taken together, these results indicated the existence of unknown factors that maintain viral subtypes in wild mallards.

Segment-specific responses of intestinal epithelium transcriptome to in-feed antibiotics in pigs.

Science.gov (United States)

Yu, Kaifan; Mu, Chunlong; Yang, Yuxiang; Su, Yong; Zhu, Weiyun

2017-10-01

Despite widespread use of antibiotics for treatment of human diseases and promotion of growth of agricultural animals, our understanding of their effects on the host is still very limited. We used a model in which pigs were fed with or without a cocktail of antibiotics and found, based on the denaturing gradient gel electrophoresis (DGGE) patterns, that the fecal bacteria from the treatment and control animals were distinct. Furthermore, the total bacterial population in the feces tended to be decreased by the antibiotic treatment ( P = 0.07), and the counts of Lactobacillus and Clostridium XIVa were significantly reduced ( P epithelium, we assessed gene expression profiles of the jejunum and ileum and their response to antibiotic administration. The results indicate that in-feed antibiotics increased expression of genes involved in immune functions in both the jejunum and ileum, some of which were clustered in the coexpression network. Gene ontology terms of metabolic processes were altered predominantly in the jejunum but not in the ileum. Notably, antibiotics diminished intestinal segment-specific transcriptional changes, especially for genes associated with metabolic functions. This study reveals segment-specific responses of host intestinal epithelium to in-feed antibiotics, which can be a valuable resource for deciphering antibiotic-microbiota-host interactions. Copyright © 2017 the American Physiological Society.

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.

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

Automated segmentation and reconstruction of patient-specific cardiac anatomy and pathology from in vivo MRI

International Nuclear Information System (INIS)

Ringenberg, Jordan; Deo, Makarand; Devabhaktuni, Vijay; Filgueiras-Rama, David; Pizarro, Gonzalo; Ibañez, Borja; Berenfeld, Omer; Boyers, Pamela; Gold, Jeffrey

2012-01-01

This paper presents an automated method to segment left ventricle (LV) tissues from functional and delayed-enhancement (DE) cardiac magnetic resonance imaging (MRI) scans using a sequential multi-step approach. First, a region of interest (ROI) is computed to create a subvolume around the LV using morphological operations and image arithmetic. From the subvolume, the myocardial contours are automatically delineated using difference of Gaussians (DoG) filters and GSV snakes. These contours are used as a mask to identify pathological tissues, such as fibrosis or scar, within the DE-MRI. The presented automated technique is able to accurately delineate the myocardium and identify the pathological tissue in patient sets. The results were validated by two expert cardiologists, and in one set the automated results are quantitatively and qualitatively compared with expert manual delineation. Furthermore, the method is patient-specific, performed on an entire patient MRI series. Thus, in addition to providing a quick analysis of individual MRI scans, the fully automated segmentation method is used for effectively tagging regions in order to reconstruct computerized patient-specific 3D cardiac models. These models can then be used in electrophysiological studies and surgical strategy planning. (paper)

Segmentation of overweight Americans and opportunities for social marketing.

Science.gov (United States)

Kolodinsky, Jane; Reynolds, Travis

2009-03-08

The food industry uses market segmentation to target products toward specific groups of consumers with similar attitudinal, demographic, or lifestyle characteristics. Our aims were to identify distinguishable segments within the US overweight population to be targeted with messages and media aimed at moving Americans toward more healthy weights. Cluster analysis was used to identify segments of consumers based on both food and lifestyle behaviors related to unhealthy weights. Drawing from Social Learning Theory, the Health Belief Model, and existing market segmentation literature, the study identified five distinct, recognizable market segments based on knowledge and behavioral and environmental factors. Implications for social marketing campaigns designed to move Americans toward more healthy weights were explored. The five clusters identified were: Highest Risk (19%); At Risk (22%); Right Behavior/Wrong Results (33%); Getting Best Results (13%); and Doing OK (12%). Ninety-nine percent of those in the Highest Risk cluster were overweight; members watched the most television and exercised the least. Fifty-five percent of those in the At Risk cluster were overweight; members logged the most computer time and almost half rarely or never read food labels. Sixty-six percent of those in the Right Behavior/Wrong Results cluster were overweight; however, 95% of them were familiar with the food pyramid. Members reported eating a low percentage of fast food meals (8%) compared to other groups but a higher percentage of other restaurant meals (15%). Less than six percent of those in the Getting Best Results cluster were overweight; every member read food labels and 75% of members' meals were "made from scratch." Eighteen percent of those in the Doing OK cluster were overweight; members watched the least television and reported eating 78% of their meals "made from scratch." This study demonstrated that five distinct market segments can be identified for social marketing

Segmentation of overweight Americans and opportunities for social marketing

Directory of Open Access Journals (Sweden)

Reynolds Travis

2009-03-01

Full Text Available Abstract Background The food industry uses market segmentation to target products toward specific groups of consumers with similar attitudinal, demographic, or lifestyle characteristics. Our aims were to identify distinguishable segments within the US overweight population to be targeted with messages and media aimed at moving Americans toward more healthy weights. Methods Cluster analysis was used to identify segments of consumers based on both food and lifestyle behaviors related to unhealthy weights. Drawing from Social Learning Theory, the Health Belief Model, and existing market segmentation literature, the study identified five distinct, recognizable market segments based on knowledge and behavioral and environmental factors. Implications for social marketing campaigns designed to move Americans toward more healthy weights were explored. Results The five clusters identified were: Highest Risk (19%; At Risk (22%; Right Behavior/Wrong Results (33%; Getting Best Results (13%; and Doing OK (12%. Ninety-nine percent of those in the Highest Risk cluster were overweight; members watched the most television and exercised the least. Fifty-five percent of those in the At Risk cluster were overweight; members logged the most computer time and almost half rarely or never read food labels. Sixty-six percent of those in the Right Behavior/Wrong Results cluster were overweight; however, 95% of them were familiar with the food pyramid. Members reported eating a low percentage of fast food meals (8% compared to other groups but a higher percentage of other restaurant meals (15%. Less than six percent of those in the Getting Best Results cluster were overweight; every member read food labels and 75% of members' meals were "made from scratch." Eighteen percent of those in the Doing OK cluster were overweight; members watched the least television and reported eating 78% of their meals "made from scratch." Conclusion This study demonstrated that five distinct

Diagnostic usefulness of segmental and linear enhancement in dynamic breast MRI

International Nuclear Information System (INIS)

Morakkabati-Spitz, N.; Leutner, C.; Schild, H.; Traeber, F.; Kuhl, C.

2005-01-01

The aim of this study was the evaluation of the diagnostic usefulness of ductal or segmental enhancement in dynamic breast MRI. Segmental and ductal enhancement have been established as the breast MRI hallmarks of intraductal breast cancer (DCIS); however, the positive predictive value of this imaging finding is still unknown. In our study, we analysed the overall prevalence of a segmental or a linear enhancement pattern on breast MRI for an unselected cohort of patients. The aim was to evaluate the diagnostic usefulness of segmental or linear enhancement. Second, we asked whether biopsy was necessary also in the absence of mammographic findings suggestive of DCIS. Prospective, consecutive evaluation of 1,003 patients undergoing bilateral dynamic breast MRI. Studies were interpreted by two experienced breast radiologists. A diagnostic or screening two-view mammogram was available for all patients. Biopsy or short-term breast MRI follow-up was recommended for patients showing a segmental or a linear enhancement pattern on breast MRI. The patients' final diagnoses were established by imaging guided excisional or core biopsy or by clinical plus conventional imaging follow-up for a period of 2 years. The prevalence of segmental or linear enhancement was determined for patients with a final diagnosis of benign breast disease compared with those with a diagnosis of breast cancer. One hundred twenty patients had invasive breast cancer, 24 patients had DCIS and 859 patients had unsuspicious breast MRI or benign breast disease. A segmental or a linear enhancement pattern was found for 50/1,003 (5%) patients (17 DCIS, 33 benign breast diseases). Accordingly, the positive predictive value of segmental and linear enhancement is 34% (17/50); the specificity of this criterion is 96% (826/859). For 4/24 (17%) patients, DCIS was visible as segmental or linear enhancement on dynamic breast MRI, whereas no abnormalities were visible on the corresponding mammogram. The overall

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.

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.

Locally specific measures for employment aimed at regional development

Directory of Open Access Journals (Sweden)

Vladimir Cini

2013-12-01

Full Text Available The oldest and largest sub-region in the world functioning on the principle of economic union is the European Union. The creation of a single market has initiated the process of conditional adjustment of markets in the EU member states, which has a significant impact on the social welfare of its citizens. It is necessary to tackle this issue by joint efforts within the European Union. As globalization processes push for economic integration and development of competitive advantage, the regions will have to make some challenging adjustments. The development tends to concentrate in highly competitive regions, while regions in the periphery lag behind. However, this pertains not only to the economic lag, but also to a potential negative political situation. Locally specific active employment policy measures are a continuation of the effort to make these measures more flexible. They refer to the Joint Assessment of Employment Policy Priorities and the IPA Human Resources Development Operational Programme - a regional policy instrument of the European Union. Both documents highlight the issue of disproportional development of regions, which requires special local measures and active labour market policy programmes. To reduce regional differences in development, it is necessary to invest more resources in the regions that lag behind. In this particular case, this means the counties in Croatia with high unemployment rates, a large number of registered unemployed persons and low employment rate. Consequently, this paper explains the importance of the adoption of locally specific measures for employment, which unfortunately did not take hold in the Republic of Croatia, and highlights the need for further decentralization of public services, with the aim of balancing regional development

Optimal Dynamic Advertising Strategy Under Age-Specific Market Segmentation

Science.gov (United States)

Krastev, Vladimir

2011-12-01

We consider the model proposed by Faggian and Grosset for determining the advertising efforts and goodwill in the long run of a company under age segmentation of consumers. Reducing this model to optimal control sub problems we find the optimal advertising strategy and goodwill.

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...

H-Ransac a Hybrid Point Cloud Segmentation Combining 2d and 3d Data

Science.gov (United States)

Adam, A.; Chatzilari, E.; Nikolopoulos, S.; Kompatsiaris, I.

2018-05-01

In this paper, we present a novel 3D segmentation approach operating on point clouds generated from overlapping images. The aim of the proposed hybrid approach is to effectively segment co-planar objects, by leveraging the structural information originating from the 3D point cloud and the visual information from the 2D images, without resorting to learning based procedures. More specifically, the proposed hybrid approach, H-RANSAC, is an extension of the well-known RANSAC plane-fitting algorithm, incorporating an additional consistency criterion based on the results of 2D segmentation. Our expectation that the integration of 2D data into 3D segmentation will achieve more accurate results, is validated experimentally in the domain of 3D city models. Results show that HRANSAC can successfully delineate building components like main facades and windows, and provide more accurate segmentation results compared to the typical RANSAC plane-fitting algorithm.

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

Multi-criteria media mix decision model for advertising multiple product with segment specific and mass media

Directory of Open Access Journals (Sweden)

Sugandha Aggarwal

2014-12-01

Full Text Available Judicious media planning decisions are crucial for successful advertising of products. Media planners extensively use mathematical models supplemented with market research and expert opinion to devise the media plans. Media planning models discussed in the literature largely focus on single products with limited studies related to the multi-product media planning. In this paper we propose a media planning model to allocate limited advertising budget among multiple products advertised in a segmented market and determine the number of advertisements to be given in different media. The proposed model is formulated considering both segment specific and mass media vehicles to maximize the total advertising reach for each product. The model also incorporates the cross product effect of advertising of one product on the other. The proposed formulation is a multi-objective linear integer programming model and interactive linear integer goal programming is discussed to solve the model. A real life case study is presented to illustrate the application of the proposed model.

Correlation of Leukocyte Count and Percentage of Segmented Neutrophils with Pathohistological Findings of Appendix in Children

Directory of Open Access Journals (Sweden)

Marko Baskovic

2018-01-01

Full Text Available BackgroundAppendicitis is the most common indication for an emergency operation in children's age. Although none of the laboratory values has not high sensitivity and specificity for the diagnosis of appendicitis, leukocyte count and the percentage of segmented neutrophils are most commonly used. The aim of this study was to determine whether there is a statistically significant correlation between leukocyte count and the percentage of segmented neutrophils compared to the pathohistological finding of appendix in children. Materials and MethodsWe retrospectively analyzed the data in the period from 1 January 2016 to 31 December 2016. The analysis was made on 211 patients. Spearman's correlation coefficient (rs was calculated. We determined the specificity and sensitivity of leukocyte count and the percentage of segmented neutrophils used in the calculation of Alvorado and Pediatric Appendicitis score.ResultsThe results of the research have shown that the correlation between leukocyte count and the pathohistological findings is weak (rs = 0.29, p = 3.61*10-8, while there is no correlation between the percentage of segmented neutrophils and pathohistological findings (rs = 0.18, p = 7.08 *10-5. The sensitivity of leukocyte count is 93% and the specificity is 30%, while the sensitivity to the percentage of segmented neutrophils is 71% and the specificity is 50%. ROC analysis for leukocytes shows area under the curve of 0.648, while for segmented neutrophils of 0.574.ConclusionGiven the correlation results obtained, the clinical experience of physicians will still have one of the leading roles in diagnosing acute appendicitis in children.

Scale selection for supervised image segmentation

DEFF Research Database (Denmark)

Li, Yan; Tax, David M J; Loog, Marco

2012-01-01

schemes are usually unsupervised, as they do not take into account the actual segmentation problem at hand. In this paper, we consider the problem of selecting scales, which aims at an optimal discrimination between user-defined classes in the segmentation. We show the deficiency of the classical...

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.

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.

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.

A JOINT FRAMEWORK FOR 4D SEGMENTATION AND ESTIMATION OF SMOOTH TEMPORAL APPEARANCE CHANGES.

Science.gov (United States)

Gao, Yang; Prastawa, Marcel; Styner, Martin; Piven, Joseph; Gerig, Guido

2014-04-01

Medical imaging studies increasingly use longitudinal images of individual subjects in order to follow-up changes due to development, degeneration, disease progression or efficacy of therapeutic intervention. Repeated image data of individuals are highly correlated, and the strong causality of information over time lead to the development of procedures for joint segmentation of the series of scans, called 4D segmentation. A main aim was improved consistency of quantitative analysis, most often solved via patient-specific atlases. Challenging open problems are contrast changes and occurance of subclasses within tissue as observed in multimodal MRI of infant development, neurodegeneration and disease. This paper proposes a new 4D segmentation framework that enforces continuous dynamic changes of tissue contrast patterns over time as observed in such data. Moreover, our model includes the capability to segment different contrast patterns within a specific tissue class, for example as seen in myelinated and unmyelinated white matter regions in early brain development. Proof of concept is shown with validation on synthetic image data and with 4D segmentation of longitudinal, multimodal pediatric MRI taken at 6, 12 and 24 months of age, but the methodology is generic w.r.t. different application domains using serial imaging.

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...

Smart markers for watershed-based cell segmentation.

Directory of Open Access Journals (Sweden)

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.

A systematic review of image segmentation methodology, used in the additive manufacture of patient-specific 3D printed models of the cardiovascular system

Directory of Open Access Journals (Sweden)

N Byrne

2016-04-01

Full Text Available Background Shortcomings in existing methods of image segmentation preclude the widespread adoption of patient-specific 3D printing as a routine decision-making tool in the care of those with congenital heart disease. We sought to determine the range of cardiovascular segmentation methods and how long each of these methods takes. Methods A systematic review of literature was undertaken. Medical imaging modality, segmentation methods, segmentation time, segmentation descriptive quality (SDQ and segmentation software were recorded. Results Totally 136 studies met the inclusion criteria (1 clinical trial; 80 journal articles; 55 conference, technical and case reports. The most frequently used image segmentation methods were brightness thresholding, region growing and manual editing, as supported by the most popular piece of proprietary software: Mimics (Materialise NV, Leuven, Belgium, 1992–2015. The use of bespoke software developed by individual authors was not uncommon. SDQ indicated that reporting of image segmentation methods was generally poor with only one in three accounts providing sufficient detail for their procedure to be reproduced. Conclusions and implication of key findings Predominantly anecdotal and case reporting precluded rigorous assessment of risk of bias and strength of evidence. This review finds a reliance on manual and semi-automated segmentation methods which demand a high level of expertise and a significant time commitment on the part of the operator. In light of the findings, we have made recommendations regarding reporting of 3D printing studies. We anticipate that these findings will encourage the development of advanced image segmentation methods.

Bayesian longitudinal segmentation of hippocampal substructures in brain MRI using subject-specific atlases.

Science.gov (United States)

Iglesias, Juan Eugenio; Van Leemput, Koen; Augustinack, Jean; Insausti, Ricardo; Fischl, Bruce; Reuter, Martin

2016-11-01

The hippocampal formation is a complex, heterogeneous structure that consists of a number of distinct, interacting subregions. Atrophy of these subregions is implied in a variety of neurodegenerative diseases, most prominently in Alzheimer's disease (AD). Thanks to the increasing resolution of MR images and computational atlases, automatic segmentation of hippocampal subregions is becoming feasible in MRI scans. Here we introduce a generative model for dedicated longitudinal segmentation that relies on subject-specific atlases. The segmentations of the scans at the different time points are jointly computed using Bayesian inference. All time points are treated the same to avoid processing bias. We evaluate this approach using over 4700 scans from two publicly available datasets (ADNI and MIRIAD). In test-retest reliability experiments, the proposed method yielded significantly lower volume differences and significantly higher Dice overlaps than the cross-sectional approach for nearly every subregion (average across subregions: 4.5% vs. 6.5%, Dice overlap: 81.8% vs. 75.4%). The longitudinal algorithm also demonstrated increased sensitivity to group differences: in MIRIAD (69 subjects: 46 with AD and 23 controls), it found differences in atrophy rates between AD and controls that the cross sectional method could not detect in a number of subregions: right parasubiculum, left and right presubiculum, right subiculum, left dentate gyrus, left CA4, left HATA and right tail. In ADNI (836 subjects: 369 with AD, 215 with early cognitive impairment - eMCI - and 252 controls), all methods found significant differences between AD and controls, but the proposed longitudinal algorithm detected differences between controls and eMCI and differences between eMCI and AD that the cross sectional method could not find: left presubiculum, right subiculum, left and right parasubiculum, left and right HATA. Moreover, many of the differences that the cross-sectional method already found

CONSUMER SEGMENTATION OF REFILLED DRINKING WATER IN PADANG

Directory of Open Access Journals (Sweden)

Awisal Fasyni

2015-05-01

Full Text Available The purposes of this study were to analyze consumer segmentation of refilled drinking water based on their behavior and to recommend strategies for increased sales of Salju depot. The study was conducted using a survey of family and non-family consumers in Nanggalo, North Padang, West and East Padang. The respondent selection technique is using a convenience sampling, which is based on the availability of elements and easiness of obtaining these samples. The analysis used for segmentation is cluster analysis and CHAID. The results showed that there were five segments in family consumer and four segments in non-family consumer. Each family segment was different in terms of usage and consumption level, while non-family segments differ in terms of consumption duration and consumption level. Salju depot could aim market segments that provide benefits, specifically segments with high consumption levels both in family and nonfamily consumers, maintain the price and quality of the product and show the best performance in serving customers, set the open hours and optimize the messaging services.Keywords: refilled drinking water, segmentation, Padang, CHAIDABSTRAKPenelitian ini bertujuan menganalisis segmentasi konsumen air minum isi ulang berdasarkan perilakunya dan merekomendasikan strategi peningkatan penjualan bagi depot Salju. Penelitian dilakukan dengan metode survei terhadap konsumen keluarga dan konsumen nonkeluarga di Kecamatan Nanggalo, Kecamatan Padang Utara, Kecamatan Padang Barat dan Kecamatan Padang Timur Kota Padang. Teknik pemilihan responden menggunakan convenience sampling, yaitu berdasarkan ketersediaan elemen dan kemudahan mendapatkan sampel tersebut. Analisis yang digunakan untuk segmentasi adalah analisis cluster dan CHAID Hasil penelitian menunjukkan terdapat lima segmen konsumen keluarga dan empat segmen konsumen nonkeluarga. Masing-masing segmen keluarga berbeda dalam hal penggunaan dan tingkat konsumsi, sedangkan segmen

Multi-segmental movement patterns reflect juggling complexity and skill level.

Science.gov (United States)

Zago, Matteo; Pacifici, Ilaria; Lovecchio, Nicola; Galli, Manuela; Federolf, Peter Andreas; Sforza, Chiarella

2017-08-01

The juggling action of six experts and six intermediates jugglers was recorded with a motion capture system and decomposed into its fundamental components through Principal Component Analysis. The aim was to quantify trends in movement dimensionality, multi-segmental patterns and rhythmicity as a function of proficiency level and task complexity. Dimensionality was quantified in terms of Residual Variance, while the Relative Amplitude was introduced to account for individual differences in movement components. We observed that: experience-related modifications in multi-segmental actions exist, such as the progressive reduction of error-correction movements, especially in complex task condition. The systematic identification of motor patterns sensitive to the acquisition of specific experience could accelerate the learning process. Copyright © 2017 Elsevier B.V. All rights reserved.

The Hierarchy of Segment Reports

Directory of Open Access Journals (Sweden)

Danilo Dorović

2015-05-01

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

Learning from Weak and Noisy Labels for Semantic Segmentation

KAUST Repository

Lu, Zhiwu

2016-04-08

A weakly supervised semantic segmentation (WSSS) method aims to learn a segmentation model from weak (image-level) as opposed to strong (pixel-level) labels. By avoiding the tedious pixel-level annotation process, it can exploit the unlimited supply of user-tagged images from media-sharing sites such as Flickr for large scale applications. However, these ‘free’ tags/labels are often noisy and few existing works address the problem of learning with both weak and noisy labels. In this work, we cast the WSSS problem into a label noise reduction problem. Specifically, after segmenting each image into a set of superpixels, the weak and potentially noisy image-level labels are propagated to the superpixel level resulting in highly noisy labels; the key to semantic segmentation is thus to identify and correct the superpixel noisy labels. To this end, a novel L1-optimisation based sparse learning model is formulated to directly and explicitly detect noisy labels. To solve the L1-optimisation problem, we further develop an efficient learning algorithm by introducing an intermediate labelling variable. Extensive experiments on three benchmark datasets show that our method yields state-of-the-art results given noise-free labels, whilst significantly outperforming the existing methods when the weak labels are also noisy.

Learning from Weak and Noisy Labels for Semantic Segmentation

KAUST Repository

Lu, Zhiwu; Fu, Zhenyong; Xiang, Tao; Han, Peng; Wang, Liwei; Gao, Xin

2016-01-01

A weakly supervised semantic segmentation (WSSS) method aims to learn a segmentation model from weak (image-level) as opposed to strong (pixel-level) labels. By avoiding the tedious pixel-level annotation process, it can exploit the unlimited supply of user-tagged images from media-sharing sites such as Flickr for large scale applications. However, these ‘free’ tags/labels are often noisy and few existing works address the problem of learning with both weak and noisy labels. In this work, we cast the WSSS problem into a label noise reduction problem. Specifically, after segmenting each image into a set of superpixels, the weak and potentially noisy image-level labels are propagated to the superpixel level resulting in highly noisy labels; the key to semantic segmentation is thus to identify and correct the superpixel noisy labels. To this end, a novel L1-optimisation based sparse learning model is formulated to directly and explicitly detect noisy labels. To solve the L1-optimisation problem, we further develop an efficient learning algorithm by introducing an intermediate labelling variable. Extensive experiments on three benchmark datasets show that our method yields state-of-the-art results given noise-free labels, whilst significantly outperforming the existing methods when the weak labels are also noisy.

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

Image segmentation with a novel regularized composite shape prior based on surrogate study

Energy Technology Data Exchange (ETDEWEB)

Zhao, Tingting, E-mail: tingtingzhao@mednet.ucla.edu; Ruan, Dan, E-mail: druan@mednet.ucla.edu [The Department of Radiation Oncology, University of California, Los Angeles, California 90095 (United States)

2016-05-15

Purpose: Incorporating training into image segmentation is a good approach to achieve additional robustness. This work aims to develop an effective strategy to utilize shape prior knowledge, so that the segmentation label evolution can be driven toward the desired global optimum. Methods: In the variational image segmentation framework, a regularization for the composite shape prior is designed to incorporate the geometric relevance of individual training data to the target, which is inferred by an image-based surrogate relevance metric. Specifically, this regularization is imposed on the linear weights of composite shapes and serves as a hyperprior. The overall problem is formulated in a unified optimization setting and a variational block-descent algorithm is derived. Results: The performance of the proposed scheme is assessed in both corpus callosum segmentation from an MR image set and clavicle segmentation based on CT images. The resulted shape composition provides a proper preference for the geometrically relevant training data. A paired Wilcoxon signed rank test demonstrates statistically significant improvement of image segmentation accuracy, when compared to multiatlas label fusion method and three other benchmark active contour schemes. Conclusions: This work has developed a novel composite shape prior regularization, which achieves superior segmentation performance than typical benchmark schemes.

Image segmentation with a novel regularized composite shape prior based on surrogate study

International Nuclear Information System (INIS)

Zhao, Tingting; Ruan, Dan

2016-01-01

Purpose: Incorporating training into image segmentation is a good approach to achieve additional robustness. This work aims to develop an effective strategy to utilize shape prior knowledge, so that the segmentation label evolution can be driven toward the desired global optimum. Methods: In the variational image segmentation framework, a regularization for the composite shape prior is designed to incorporate the geometric relevance of individual training data to the target, which is inferred by an image-based surrogate relevance metric. Specifically, this regularization is imposed on the linear weights of composite shapes and serves as a hyperprior. The overall problem is formulated in a unified optimization setting and a variational block-descent algorithm is derived. Results: The performance of the proposed scheme is assessed in both corpus callosum segmentation from an MR image set and clavicle segmentation based on CT images. The resulted shape composition provides a proper preference for the geometrically relevant training data. A paired Wilcoxon signed rank test demonstrates statistically significant improvement of image segmentation accuracy, when compared to multiatlas label fusion method and three other benchmark active contour schemes. Conclusions: This work has developed a novel composite shape prior regularization, which achieves superior segmentation performance than typical benchmark schemes.

Expression of Aleutian mink disease parvovirus capsid proteins in defined segments: localization of immunoreactive sites and neutralizing epitopes to specific regions.

Science.gov (United States)

Bloom, M E; Martin, D A; Oie, K L; Huhtanen, M E; Costello, F; Wolfinbarger, J B; Hayes, S F; Agbandje-McKenna, M

1997-01-01

The capsid proteins of the ADV-G isolate of Aleutian mink disease parvovirus (ADV) were expressed in 10 nonoverlapping segments as fusions with maltose-binding protein in pMAL-C2 (pVP1, pVP2a through pVP2i). The constructs were designed to capture the VP1 unique sequence and the portions analogous to the four variable surface loops of canine parvovirus (CPV) in individual fragments (pVP2b, pVP2d, pVP2e, and pVP2g, respectively). The panel of fusion proteins was immunoblotted with sera from mink infected with ADV. Seropositive mink infected with either ADV-TR, ADV-Utah, or ADV-Pullman reacted preferentially against certain segments, regardless of mink genotype or virus inoculum. The most consistently immunoreactive regions were pVP2g, pVP2e, and pVP2f, the segments that encompassed the analogs of CPV surface loops 3 and 4. The VP1 unique region was also consistently immunoreactive. These findings indicated that infected mink recognize linear epitopes that localized to certain regions of the capsid protein sequence. The segment containing the hypervariable region (pVP2d), corresponding to CPV loop 2, was also expressed from ADV-Utah. An anti-ADV-G monoclonal antibody and a rabbit anti-ADV-G capsid antibody reacted exclusively with the ADV-G pVP2d segment but not with the corresponding segment from ADV-Utah. Mink infected with ADV-TR or ADV-Utah also preferentially reacted with the pVP2d sequence characteristic of that virus. These results suggested that the loop 2 region may contain a type-specific linear epitope and that the epitope may also be specifically recognized by infected mink. Heterologous antisera were prepared against the VP1 unique region and the four segments capturing the variable surface loops of CPV. The antisera against the proteins containing loop 3 or loop 4, as well as the anticapsid antibody, neutralized ADV-G infectivity in vitro and bound to capsids in immune electron microscopy. These results suggested that regions of the ADV capsid proteins

Site-specific deletions of chromosomally located DNA segments with the multimer resolution system of broad-host-range plasmid RP4

DEFF Research Database (Denmark)

Sternberg, Claus; Eberl, Leo; Sanchezromero, Juan M.

1995-01-01

The multimer resolution system (mrs) of the broad-host-range plasmid RP4 has been exploited to develop a general method that permits the precise excision of chromosomal segments in a variety of gram-negative bacteria. The procedure is based on the site-specific recombination between two directly ...

Specific expression of the vacuolar iron transporter, TgVit, causes iron accumulation in blue-colored inner bottom segments of various tulip petals.

Science.gov (United States)

Momonoi, Kazumi; Tsuji, Toshiaki; Kazuma, Kohei; Yoshida, Kumi

2012-01-01

Several flowers of Tulipa gesneriana exhibit a blue color in the bottom segments of the inner perianth. We have previously reported the inner-bottom tissue-specific iron accumulation and expression of the vacuolar iron transporter, TgVit1, in tulip cv. Murasakizuisho. To clarify whether the TgVit1-dependent iron accumulation and blue-color development in tulip petals are universal, we analyzed anthocyanin, its co-pigment components, iron contents and the expression of TgVit1 mRNA in 13 cultivars which show a blue color in the bottom segments of the inner perianth accompanying yellow- and white-colored inner-bottom petals. All of the blue bottom segments contained the same anthocyanin component, delphinidin 3-rutinoside. The flavonol composition varied with cultivar and tissue part. The major flavonol in the bottom segments of the inner perianth was rutin. The iron content in the upper part was less than that in the bottom segments of the inner perianth. The iron content in the yellow and white petals was higher in the bottom segment of the inner perianth than in the upper tissues. TgVit1 mRNA expression was apparent in all of the bottom tissues of the inner perianth. The result of a reproduction experiment by mixing the constituents suggests that the blue coloration in tulip petals is generally caused by iron complexation to delphinidin 3-rutinoside and that the iron complex is solubilized and stabilized by flavonol glycosides. TgVit1-dependent iron accumulation in the bottom segments of the inner perianth might be controlled by an unknown system that differentiated the upper parts and bottom segments of the inner perianth.

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

Micro-segmental hair analysis for proving drug-facilitated crimes: Evidence that a victim ingested a sleeping aid, diphenhydramine, on a specific day.

Science.gov (United States)

Kuwayama, Kenji; Nariai, Maika; Miyaguchi, Hajime; Iwata, Yuko T; Kanamori, Tatsuyuki; Tsujikawa, Kenji; Yamamuro, Tadashi; Segawa, Hiroki; Abe, Hiroko; Iwase, Hirotaro; Inoue, Hiroyuki

2018-07-01

Sleeping aids are often abused in the commission of drug-facilitated crimes. Generally, there is little evidence that a victim ingested a spiked drink unknowingly because the unconscious victim cannot report the situation to the police immediately after the crime occurred. Although conventional segmental hair analysis can estimate the number of months since a targeted drug was ingested, this analysis cannot determine the specific day of ingestion. We recently developed a method of micro-segmental hair analysis using internal temporal markers (ITMs) to estimate the day of drug ingestion. This method was based on volunteer ingestion of ITMs to determine a timescale within individual hair strands, by segmenting a single hair strand at 0.4-mm intervals, corresponding to daily hair growth. This study assessed the ability of this method to estimate the day of ingestion of an over-the-counter sleeping aid, diphenhydramine, which can be easily abused. To model ingestion of a diphenhydramine-spiked drink unknowingly, each subject ingested a dose of diphenhydramine, followed by ingestion of two doses of the ITM, chlorpheniramine, 14days apart. Several hair strands were collected from each subject's scalp several weeks after the second ITM ingestion. Diphenhydramine and ITM were detected at specific regions within individual hair strands. The day of diphenhydramine ingestion was estimated from the distances between the regions and the days of ITM ingestion. The error between estimated and actual ingestion day ranged from -0.1 to 1.9days regardless of subjects and hair collection times. The total time required for micro-segmental analysis of 96 hair segments (hair length: 3.84cm) was approximately 2days and the cost was almost the same as in general drug analysis. This procedure may be applicable to the investigation of crimes facilitated by various drugs. Copyright © 2018 Elsevier B.V. All rights reserved.

White matter hyperintensity and stroke lesion segmentation and differentiation using convolutional neural networks

Directory of Open Access Journals (Sweden)

R. Guerrero

2018-01-01

Full Text Available White matter hyperintensities (WMH are a feature of sporadic small vessel disease also frequently observed in magnetic resonance images (MRI of healthy elderly subjects. The accurate assessment of WMH burden is of crucial importance for epidemiological studies to determine association between WMHs, cognitive and clinical data; their causes, and the effects of new treatments in randomized trials. The manual delineation of WMHs is a very tedious, costly and time consuming process, that needs to be carried out by an expert annotator (e.g. a trained image analyst or radiologist. The problem of WMH delineation is further complicated by the fact that other pathological features (i.e. stroke lesions often also appear as hyperintense regions. Recently, several automated methods aiming to tackle the challenges of WMH segmentation have been proposed. Most of these methods have been specifically developed to segment WMH in MRI but cannot differentiate between WMHs and strokes. Other methods, capable of distinguishing between different pathologies in brain MRI, are not designed with simultaneous WMH and stroke segmentation in mind. Therefore, a task specific, reliable, fully automated method that can segment and differentiate between these two pathological manifestations on MRI has not yet been fully identified. In this work we propose to use a convolutional neural network (CNN that is able to segment hyperintensities and differentiate between WMHs and stroke lesions. Specifically, we aim to distinguish between WMH pathologies from those caused by stroke lesions due to either cortical, large or small subcortical infarcts. The proposed fully convolutional CNN architecture, called uResNet, that comprised an analysis path, that gradually learns low and high level features, followed by a synthesis path, that gradually combines and up-samples the low and high level features into a class likelihood semantic segmentation. Quantitatively, the proposed CNN

An Algorithm to Automate Yeast Segmentation and Tracking

Science.gov (United States)

Doncic, Andreas; Eser, Umut; Atay, Oguzhan; Skotheim, Jan M.

2013-01-01

Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation. PMID:23520484

Balancing the fit and logistics costs of market segmentations

NARCIS (Netherlands)

Turkensteen, M.; Sierksma, G.; Wieringa, J.E.

2011-01-01

Segments are typically formed to serve distinct groups of consumers with differentiated marketing mixes, that better fit their specific needs and wants. However, buyers in a segment are not necessarily geographically closely located. Serving a geographically dispersed segment with one marketing mix

Sphingosine-1-Phosphate Evokes Unique Segment-Specific Vasoconstriction of the Renal Microvasculature

Science.gov (United States)

Singletary, Sean T.; Cook, Anthony K.; Hobbs, Janet L.; Pollock, Jennifer S.; Inscho, Edward W.

2014-01-01

Sphingosine-1-phosphate (S1P), a bioactive sphingolipid metabolite, has been implicated in regulating vascular tone and participating in chronic and acute kidney injury. However, little is known about the role of S1P in the renal microcirculation. Here, we directly assessed the vasoresponsiveness of preglomerular and postglomerular microvascular segments to exogenous S1P using the in vitro blood-perfused juxtamedullary nephron preparation. Superfusion of S1P (0.001–10 μM) evoked concentration-dependent vasoconstriction in preglomerular microvessels, predominantly afferent arterioles. After administration of 10 μM S1P, the diameter of afferent arterioles decreased to 35%±5% of the control diameter, whereas the diameters of interlobular and arcuate arteries declined to 50%±12% and 68%±6% of the control diameter, respectively. Notably, efferent arterioles did not respond to S1P. The S1P receptor agonists FTY720 and FTY720-phosphate and the specific S1P1 receptor agonist SEW2871 each evoked modest afferent arteriolar vasoconstriction. Conversely, S1P2 receptor inhibition with JTE-013 significantly attenuated S1P-mediated afferent arteriolar vasoconstriction. Moreover, blockade of L-type voltage-dependent calcium channels with diltiazem or nifedipine attenuated S1P-mediated vasoconstriction. Intravenous injection of S1P in anesthetized rats reduced renal blood flow dose dependently. Western blotting and immunofluorescence revealed S1P1 and S1P2 receptor expression in isolated preglomerular microvessels and microvascular smooth muscle cells. These data demonstrate that S1P evokes segmentally distinct preglomerular vasoconstriction via activation of S1P1 and/or S1P2 receptors, partially via L-type voltage-dependent calcium channels. Accordingly, S1P may have a novel function in regulating afferent arteriolar resistance under physiologic conditions. PMID:24578134

Adaptation of the Maracas algorithm for carotid artery segmentation and stenosis quantification on CT images

International Nuclear Information System (INIS)

Maria A Zuluaga; Maciej Orkisz; Edgar J F Delgado; Vincent Dore; Alfredo Morales Pinzon; Marcela Hernandez Hoyos

2010-01-01

This paper describes the adaptations of Maracas algorithm to the segmentation and quantification of vascular structures in CTA images of the carotid artery. The maracas algorithm, which is based on an elastic model and on a multi-scale Eigen-analysis of the inertia matrix, was originally designed to segment a single artery in MRA images. The modifications are primarily aimed at addressing the specificities of CT images and the bifurcations. The algorithms implemented in this new version are classified into two levels. 1. The low-level processing (filtering of noise and directional artifacts, enhancement and pre-segmentation) to improve the quality of the image and to pre-segment it. These techniques are based on a priori information about noise, artifacts and typical gray levels ranges of lumen, background and calcifications. 2. The high-level processing to extract the centerline of the artery, to segment the lumen and to quantify the stenosis. At this level, we apply a priori knowledge of shape and anatomy of vascular structures. The method was evaluated on 31 datasets from the carotid lumen segmentation and stenosis grading grand challenge 2009. The segmentation results obtained an average of 80:4% dice similarity score, compared to reference segmentation, and the mean stenosis quantification error was 14.4%.

An algorithm to automate yeast segmentation and tracking.

Directory of Open Access Journals (Sweden)

Andreas Doncic

Full Text Available Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation.

Twelve automated thresholding methods for segmentation of PET images: a phantom study

International Nuclear Information System (INIS)

Prieto, Elena; Peñuelas, Iván; Martí-Climent, Josep M; Lecumberri, Pablo; Gómez, Marisol; Pagola, Miguel; Bilbao, Izaskun; Ecay, Margarita

2012-01-01

Tumor volume delineation over positron emission tomography (PET) images is of great interest for proper diagnosis and therapy planning. However, standard segmentation techniques (manual or semi-automated) are operator dependent and time consuming while fully automated procedures are cumbersome or require complex mathematical development. The aim of this study was to segment PET images in a fully automated way by implementing a set of 12 automated thresholding algorithms, classical in the fields of optical character recognition, tissue engineering or non-destructive testing images in high-tech structures. Automated thresholding algorithms select a specific threshold for each image without any a priori spatial information of the segmented object or any special calibration of the tomograph, as opposed to usual thresholding methods for PET. Spherical 18 F-filled objects of different volumes were acquired on clinical PET/CT and on a small animal PET scanner, with three different signal-to-background ratios. Images were segmented with 12 automatic thresholding algorithms and results were compared with the standard segmentation reference, a threshold at 42% of the maximum uptake. Ridler and Ramesh thresholding algorithms based on clustering and histogram-shape information, respectively, provided better results that the classical 42%-based threshold (p < 0.05). We have herein demonstrated that fully automated thresholding algorithms can provide better results than classical PET segmentation tools. (paper)

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...

METHODOLOGICAL CONSIDERATIONS REGARDING THE SEGMENTATION OF HOUSEHOLD ENERGY CONSUMERS

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Maxim Alexandru

2013-07-01

Full Text Available Over the last decade, the World has shown increased concern for climate change and energy security. The emergence of these issues has pushed many nations to pursue the development of clean domestic electricity production via renewable energy (RE technologies. However, RE also comes with a higher production and investment cost, compared to most conventional fossil fuel based technologies. In order to analyse exactly how Romanian electricity consumers feel about the advantages and the disadvantages of RE, we have decided to perform a comprehensive study, which will constitute the core of a doctoral thesis regarding the Romanian energy sector and household consumers’ willingness to pay for the positive attributes of RE. The current paper represents one step toward achieving the objectives of the above mentioned research, specifically dealing with the issue of segmenting household energy consumers given the context of the Romanian energy sector. It is an argumentative literature review, which seeks to critically assess the methodology used for customer segmentation in general and for household energy users in particular. Building on the experience of previous studies, the paper aims to determine the most adequate segmentation procedure given the context and the objectives of the overall doctoral research. After assessing the advantages and disadvantages of various methodologies, a psychographic segmentation of household consumers based on general life practices is chosen, mainly because it provides more insights into consumers compared to traditional socio-demographic segmentation by focusing on lifestyles and not external characteristics, but it is also realistically implementable compared to more complex procedures such as the standard AIO. However, the life practice scale developed by Axsen et al. (2012 will need to be properly adapted to the specific objectives of the study and to the context of the Romanian energy sector. All modifications

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

CLG for Automatic Image Segmentation

OpenAIRE

Christo Ananth; S.Santhana Priya; S.Manisha; T.Ezhil Jothi; M.S.Ramasubhaeswari

2017-01-01

This paper proposes an automatic segmentation method which effectively combines Active Contour Model, Live Wire method and Graph Cut approach (CLG). The aim of Live wire method is to provide control to the user on segmentation process during execution. Active Contour Model provides a statistical model of object shape and appearance to a new image which are built during a training phase. In the graph cut technique, each pixel is represented as a node and the distance between those nodes is rep...

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.

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.

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.

The Regional MBA: Distinct Segments, Wants, and Needs

Science.gov (United States)

Passyn, Kirsten; Diriker, Memo

2011-01-01

MBA Programs in top-tier school differ greatly from those in regional schools. A survey that aimed at assessing segmentation, pedagogy, and satisfaction in regional MBA programs was developed and administered in three universities of the Mid Atlantic, Midwest, and Southern regions. The results show four clearly distinguished segments that…

Relations between segmental and motor variability in prosodically complex nonword sequences.

Science.gov (United States)

Goffman, Lisa; Gerken, Louann; Lucchesi, Julie

2007-04-01

To assess how prosodic prominence and hierarchical foot structure influence segmental and articulatory aspects of speech production, specifically segmental accuracy and variability, and oral movement trajectory variability. Thirty individuals participated: 10 young adults, 10 children who are normally developing, and 10 children diagnosed with specific language impairment. Segmental error and segmental variability and movement trajectory variability were compared in low and high prosodic prominence conditions (i.e., strong and weak syllables) and in different prosodic foot structures. Between-participants findings were that both groups of children showed more segmental error and segmental variability and more movement trajectory variability than did adults. A similar within-participant pattern of results was observed for all 3 groups. Prosodic prominence influenced both segmental and motor levels of analysis, with weak syllables produced less accurately and with more lip and jaw movement trajectory variability than strong syllables. However, hierarchical foot structure affected segmental but not motor measures of speech production accuracy and variability. Motor and segmental variables were not consistently aligned. This pattern of results has clinical implications because inferences about motor variability may not directly follow from observations of segmental variability.

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.

Genetic variation of the Borrelia burgdorferi gene vlsE involves cassette-specific, segmental gene conversion.

Science.gov (United States)

Zhang, J R; Norris, S J

1998-08-01

The Lyme disease spirochete Borrelia burgdorferi possesses 15 silent vls cassettes and a vls expression site (vlsE) encoding a surface-exposed lipoprotein. Segments of the silent vls cassettes have been shown to recombine with the vlsE cassette region in the mammalian host, resulting in combinatorial antigenic variation. Despite promiscuous recombination within the vlsE cassette region, the 5' and 3' coding sequences of vlsE that flank the cassette region are not subject to sequence variation during these recombination events. The segments of the silent vls cassettes recombine in the vlsE cassette region through a unidirectional process such that the sequence and organization of the silent vls loci are not affected. As a result of recombination, the previously expressed segments are replaced by incoming segments and apparently degraded. These results provide evidence for a gene conversion mechanism in VlsE antigenic variation.

Automated bone segmentation from dental CBCT images using patch-based sparse representation and convex optimization

Energy Technology Data Exchange (ETDEWEB)

Wang, Li; Gao, Yaozong; Shi, Feng; Liao, Shu; Li, Gang [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 (United States); Chen, Ken Chung [Department of Oral and Maxillofacial Surgery, Houston Methodist Hospital Research Institute, Houston, Texas 77030 and Department of Stomatology, National Cheng Kung University Medical College and Hospital, Tainan, Taiwan 70403 (China); Shen, Steve G. F.; Yan, Jin [Department of Oral and Craniomaxillofacial Surgery and Science, Shanghai Ninth People' s Hospital, Shanghai Jiao Tong University College of Medicine, Shanghai, China 200011 (China); Lee, Philip K. M.; Chow, Ben [Hong Kong Dental Implant and Maxillofacial Centre, Hong Kong, China 999077 (China); Liu, Nancy X. [Department of Oral and Maxillofacial Surgery, Houston Methodist Hospital Research Institute, Houston, Texas 77030 and Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology, Beijing, China 100050 (China); Xia, James J. [Department of Oral and Maxillofacial Surgery, Houston Methodist Hospital Research Institute, Houston, Texas 77030 (United States); Department of Surgery (Oral and Maxillofacial Surgery), Weill Medical College, Cornell University, New York, New York 10065 (United States); Department of Oral and Craniomaxillofacial Surgery and Science, Shanghai Ninth People' s Hospital, Shanghai Jiao Tong University College of Medicine, Shanghai, China 200011 (China); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul, 136701 (Korea, Republic of)

2014-04-15

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate three-dimensional (3D) models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the poor image quality, including very low signal-to-noise ratio and the widespread image artifacts such as noise, beam hardening, and inhomogeneity, it is challenging to segment the CBCT images. In this paper, the authors present a new automatic segmentation method to address these problems. Methods: To segment CBCT images, the authors propose a new method for fully automated CBCT segmentation by using patch-based sparse representation to (1) segment bony structures from the soft tissues and (2) further separate the mandible from the maxilla. Specifically, a region-specific registration strategy is first proposed to warp all the atlases to the current testing subject and then a sparse-based label propagation strategy is employed to estimate a patient-specific atlas from all aligned atlases. Finally, the patient-specific atlas is integrated into amaximum a posteriori probability-based convex segmentation framework for accurate segmentation. Results: The proposed method has been evaluated on a dataset with 15 CBCT images. The effectiveness of the proposed region-specific registration strategy and patient-specific atlas has been validated by comparing with the traditional registration strategy and population-based atlas. The experimental results show that the proposed method achieves the best segmentation accuracy by comparison with other state-of-the-art segmentation methods. Conclusions: The authors have proposed a new CBCT segmentation method by using patch-based sparse representation and convex optimization, which can achieve considerably accurate segmentation results in CBCT

Automated bone segmentation from dental CBCT images using patch-based sparse representation and convex optimization

International Nuclear Information System (INIS)

Wang, Li; Gao, Yaozong; Shi, Feng; Liao, Shu; Li, Gang; Chen, Ken Chung; Shen, Steve G. F.; Yan, Jin; Lee, Philip K. M.; Chow, Ben; Liu, Nancy X.; Xia, James J.; Shen, Dinggang

2014-01-01

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate three-dimensional (3D) models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the poor image quality, including very low signal-to-noise ratio and the widespread image artifacts such as noise, beam hardening, and inhomogeneity, it is challenging to segment the CBCT images. In this paper, the authors present a new automatic segmentation method to address these problems. Methods: To segment CBCT images, the authors propose a new method for fully automated CBCT segmentation by using patch-based sparse representation to (1) segment bony structures from the soft tissues and (2) further separate the mandible from the maxilla. Specifically, a region-specific registration strategy is first proposed to warp all the atlases to the current testing subject and then a sparse-based label propagation strategy is employed to estimate a patient-specific atlas from all aligned atlases. Finally, the patient-specific atlas is integrated into amaximum a posteriori probability-based convex segmentation framework for accurate segmentation. Results: The proposed method has been evaluated on a dataset with 15 CBCT images. The effectiveness of the proposed region-specific registration strategy and patient-specific atlas has been validated by comparing with the traditional registration strategy and population-based atlas. The experimental results show that the proposed method achieves the best segmentation accuracy by comparison with other state-of-the-art segmentation methods. Conclusions: The authors have proposed a new CBCT segmentation method by using patch-based sparse representation and convex optimization, which can achieve considerably accurate segmentation results in CBCT

An unsupervised strategy for biomedical image segmentation

Directory of Open Access Journals (Sweden)

Roberto Rodríguez

2010-09-01

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

Segmentation of radiologic images with self-organizing maps: the segmentation problem transformed into a classification task

Science.gov (United States)

Pelikan, Erich; Vogelsang, Frank; Tolxdorff, Thomas

1996-04-01

The texture-based segmentation of x-ray images of focal bone lesions using topological maps is introduced. Texture characteristics are described by image-point correlation of feature images to feature vectors. For the segmentation, the topological map is labeled using an improved labeling strategy. Results of the technique are demonstrated on original and synthetic x-ray images and quantified with the aid of quality measures. In addition, a classifier-specific contribution analysis is applied for assessing the feature space.

COMPARISON OF DIFFERENT SEGMENTATION ALGORITHMS FOR DERMOSCOPIC IMAGES

Directory of Open Access Journals (Sweden)

A.A. Haseena Thasneem

2015-05-01

Full Text Available This paper compares different algorithms for the segmentation of skin lesions in dermoscopic images. The basic segmentation algorithms compared are Thresholding techniques (Global and Adaptive, Region based techniques (K-means, Fuzzy C means, Expectation Maximization and Statistical Region Merging, Contour models (Active Contour Model and Chan - Vese Model and Spectral Clustering. Accuracy, sensitivity, specificity, Border error, Hammoude distance, Hausdorff distance, MSE, PSNR and elapsed time metrices were used to evaluate various segmentation techniques.

Joint Segmentation of Multiple Thoracic Organs in CT Images with Two Collaborative Deep Architectures.

Science.gov (United States)

Trullo, Roger; Petitjean, Caroline; Nie, Dong; Shen, Dinggang; Ruan, Su

2017-09-01

Computed Tomography (CT) is the standard imaging technique for radiotherapy planning. The delineation of Organs at Risk (OAR) in thoracic CT images is a necessary step before radiotherapy, for preventing irradiation of healthy organs. However, due to low contrast, multi-organ segmentation is a challenge. In this paper, we focus on developing a novel framework for automatic delineation of OARs. Different from previous works in OAR segmentation where each organ is segmented separately, we propose two collaborative deep architectures to jointly segment all organs, including esophagus, heart, aorta and trachea. Since most of the organ borders are ill-defined, we believe spatial relationships must be taken into account to overcome the lack of contrast. The aim of combining two networks is to learn anatomical constraints with the first network, which will be used in the second network, when each OAR is segmented in turn. Specifically, we use the first deep architecture, a deep SharpMask architecture, for providing an effective combination of low-level representations with deep high-level features, and then take into account the spatial relationships between organs by the use of Conditional Random Fields (CRF). Next, the second deep architecture is employed to refine the segmentation of each organ by using the maps obtained on the first deep architecture to learn anatomical constraints for guiding and refining the segmentations. Experimental results show superior performance on 30 CT scans, comparing with other state-of-the-art methods.

Segmentation of medical images using explicit anatomical knowledge

Science.gov (United States)

Wilson, Laurie S.; Brown, Stephen; Brown, Matthew S.; Young, Jeanne; Li, Rongxin; Luo, Suhuai; Brandt, Lee

1999-07-01

Knowledge-based image segmentation is defined in terms of the separation of image analysis procedures and representation of knowledge. Such architecture is particularly suitable for medical image segmentation, because of the large amount of structured domain knowledge. A general methodology for the application of knowledge-based methods to medical image segmentation is described. This includes frames for knowledge representation, fuzzy logic for anatomical variations, and a strategy for determining the order of segmentation from the modal specification. This method has been applied to three separate problems, 3D thoracic CT, chest X-rays and CT angiography. The application of the same methodology to such a range of applications suggests a major role in medical imaging for segmentation methods incorporating representation of anatomical knowledge.

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

Automated segmentation of murine lung tumors in x-ray micro-CT images

Science.gov (United States)

Swee, Joshua K. Y.; Sheridan, Clare; de Bruin, Elza; Downward, Julian; Lassailly, Francois; Pizarro, Luis

2014-03-01

Recent years have seen micro-CT emerge as a means of providing imaging analysis in pre-clinical study, with in-vivo micro-CT having been shown to be particularly applicable to the examination of murine lung tumors. Despite this, existing studies have involved substantial human intervention during the image analysis process, with the use of fully-automated aids found to be almost non-existent. We present a new approach to automate the segmentation of murine lung tumors designed specifically for in-vivo micro-CT-based pre-clinical lung cancer studies that addresses the specific requirements of such study, as well as the limitations human-centric segmentation approaches experience when applied to such micro-CT data. Our approach consists of three distinct stages, and begins by utilizing edge enhancing and vessel enhancing non-linear anisotropic diffusion filters to extract anatomy masks (lung/vessel structure) in a pre-processing stage. Initial candidate detection is then performed through ROI reduction utilizing obtained masks and a two-step automated segmentation approach that aims to extract all disconnected objects within the ROI, and consists of Otsu thresholding, mathematical morphology and marker-driven watershed. False positive reduction is finally performed on initial candidates through random-forest-driven classification using the shape, intensity, and spatial features of candidates. We provide validation of our approach using data from an associated lung cancer study, showing favorable results both in terms of detection (sensitivity=86%, specificity=89%) and structural recovery (Dice Similarity=0.88) when compared against manual specialist annotation.

An LG-graph-based early evaluation of segmented images

International Nuclear Information System (INIS)

Tsitsoulis, Athanasios; Bourbakis, Nikolaos

2012-01-01

Image segmentation is one of the first important parts of image analysis and understanding. Evaluation of image segmentation, however, is a very difficult task, mainly because it requires human intervention and interpretation. In this work, we propose a blind reference evaluation scheme based on regional local–global (RLG) graphs, which aims at measuring the amount and distribution of detail in images produced by segmentation algorithms. The main idea derives from the field of image understanding, where image segmentation is often used as a tool for scene interpretation and object recognition. Evaluation here derives from summarization of the structural information content and not from the assessment of performance after comparisons with a golden standard. Results show measurements for segmented images acquired from three segmentation algorithms, applied on different types of images (human faces/bodies, natural environments and structures (buildings)). (paper)

Interactive vs. automatic ultrasound image segmentation methods for staging hepatic lipidosis.

Science.gov (United States)

Weijers, Gert; Starke, Alexander; Haudum, Alois; Thijssen, Johan M; Rehage, Jürgen; De Korte, Chris L

2010-07-01

The aim of this study was to test the hypothesis that automatic segmentation of vessels in ultrasound (US) images can produce similar or better results in grading fatty livers than interactive segmentation. A study was performed in postpartum dairy cows (N=151), as an animal model of human fatty liver disease, to test this hypothesis. Five transcutaneous and five intraoperative US liver images were acquired in each animal and a liverbiopsy was taken. In liver tissue samples, triacylglycerol (TAG) was measured by biochemical analysis and hepatic diseases other than hepatic lipidosis were excluded by histopathologic examination. Ultrasonic tissue characterization (UTC) parameters--Mean echo level, standard deviation (SD) of echo level, signal-to-noise ratio (SNR), residual attenuation coefficient (ResAtt) and axial and lateral speckle size--were derived using a computer-aided US (CAUS) protocol and software package. First, the liver tissue was interactively segmented by two observers. With increasing fat content, fewer hepatic vessels were visible in the ultrasound images and, therefore, a smaller proportion of the liver needed to be excluded from these images. Automatic-segmentation algorithms were implemented and it was investigated whether better results could be achieved than with the subjective and time-consuming interactive-segmentation procedure. The automatic-segmentation algorithms were based on both fixed and adaptive thresholding techniques in combination with a 'speckle'-shaped moving-window exclusion technique. All data were analyzed with and without postprocessing as contained in CAUS and with different automated-segmentation techniques. This enabled us to study the effect of the applied postprocessing steps on single and multiple linear regressions ofthe various UTC parameters with TAG. Improved correlations for all US parameters were found by using automatic-segmentation techniques. Stepwise multiple linear-regression formulas where derived and used

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

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...

Which perceived characteristics make product innovations appealing to the consumer? A study on the acceptance of fruit innovations using cross-cultural consumer segmentation.

Science.gov (United States)

Onwezen, Marleen C; Bartels, Jos

2011-08-01

In general, fruit consumption in the EU does not meet governments' recommended levels, and innovations in the fruit industry are thought to be useful for increasing fruit consumption. Despite the enormous number of product innovations, the majority of new products in the market fail within the first two years, due to a lack of consumer acceptance. Consumer segmentation may be a useful research tool to increase the success rates of new fruit products. The current study aims to identify consumer segments based on individual importance rankings of fruit choice motives. We conducted a cross-national, online panel survey on fresh fruit innovations in four European countries: the Netherlands (n=251), Greece (n=246), Poland (n=250), and Spain (n=250). Our cluster analysis revealed three homogeneous consumer segments: Average Joe, the Naturally conscious consumer, and the Health-oriented consumer. These consumer segments differed with respect to their importance ratings for fruit choice motives. Furthermore, the willingness to buy specific fruit innovations (i.e., genetically modified, functional food and convenience innovation) and the perceived product characteristics that influence this willingness differed across the segments. Our study could lead to more tailored marketing strategies aimed at increasing consumer acceptance of fruit product innovations based on consumer segmentation. Copyright © 2011 Elsevier Ltd. All rights reserved.

Segmentation of British Sign Language (BSL): Mind the gap!

OpenAIRE

Orfanidou, E.; McQueen, J.; Adam, R.; Morgan, G.

2015-01-01

This study asks how users of British Sign Language (BSL) recognize individual signs in connected sign sequences. We examined whether this is achieved through modality-specific or modality-general segmentation procedures. A modality-specific feature of signed languages is that, during continuous signing, there are salient transitions between sign locations. We used the sign-spotting task to ask if and how BSL signers use these transitions in segmentation. A total of 96 real BSL signs were prec...

Auto-Segmentation of Head and Neck Cancer using Textural features

DEFF Research Database (Denmark)

Hollensen, Christian; Jørgensen, Peter Stanley; Højgaard, Liselotte

- and intra observer variability. Several automatic segmentation methods have been developed using positron emission tomography (PET) and/or computerised tomography (CT). The aim of the present study is to develop a model for 3-dimensional auto-segmentation, the level set method, to contour gross tumour...

Interactive segmentation for geographic atrophy in retinal fundus images.

Science.gov (United States)

Lee, Noah; Smith, R Theodore; Laine, Andrew F

2008-10-01

Fundus auto-fluorescence (FAF) imaging is a non-invasive technique for in vivo ophthalmoscopic inspection of age-related macular degeneration (AMD), the most common cause of blindness in developed countries. Geographic atrophy (GA) is an advanced form of AMD and accounts for 12-21% of severe visual loss in this disorder [3]. Automatic quantification of GA is important for determining disease progression and facilitating clinical diagnosis of AMD. The problem of automatic segmentation of pathological images still remains an unsolved problem. In this paper we leverage the watershed transform and generalized non-linear gradient operators for interactive segmentation and present an intuitive and simple approach for geographic atrophy segmentation. We compare our approach with the state of the art random walker [5] algorithm for interactive segmentation using ROC statistics. Quantitative evaluation experiments on 100 FAF images show a mean sensitivity/specificity of 98.3/97.7% for our approach and a mean sensitivity/specificity of 88.2/96.6% for the random walker algorithm.

Stochastic Modelling as a Tool for Seismic Signals Segmentation

Directory of Open Access Journals (Sweden)

Daniel Kucharczyk

2016-01-01

Full Text Available In order to model nonstationary real-world processes one can find appropriate theoretical model with properties following the analyzed data. However in this case many trajectories of the analyzed process are required. Alternatively, one can extract parts of the signal that have homogenous structure via segmentation. The proper segmentation can lead to extraction of important features of analyzed phenomena that cannot be described without the segmentation. There is no one universal method that can be applied for all of the phenomena; thus novel methods should be invented for specific cases. They might address specific character of the signal in different domains (time, frequency, time-frequency, etc.. In this paper we propose two novel segmentation methods that take under consideration the stochastic properties of the analyzed signals in time domain. Our research is motivated by the analysis of vibration signals acquired in an underground mine. In such signals we observe seismic events which appear after the mining activity, like blasting, provoked relaxation of rock, and some unexpected events, like natural rock burst. The proposed segmentation procedures allow for extraction of such parts of the analyzed signals which are related to mentioned events.

Cochlea Segmentation using Iterated Random Walks with Shape Prior

DEFF Research Database (Denmark)

Ruiz Pujadas, Esmeralda; Kjer, Hans Martin; Vera, Sergio

2016-01-01

Cochlear implants can restore hearing to deaf or partially deaf patients. In order to plan the intervention, a model from high resolution μCT images is to be built from accurate cochlea segmentations and then, adapted to a patient-specific model. Thus, a precise segmentation is required to build...

Figure-ground segmentation based on class-independent shape priors

Science.gov (United States)

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

2018-01-01

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

Fetal endoscopic myelomeningocele closure preserves segmental neurological function

NARCIS (Netherlands)

Verbeek, Renate J.; Heep, Axel; Maurits, Natalia M.; Cremer, Reinhold; Hoving, Eelco W.; Brouwer, Oebele F.; Van der Hoeven, Johannes H.; Sival, Deborah A.

AIM:   Our aim was to compare the effect of prenatal endoscopic with postnatal myelomeningocele closure (fetally operated spina bifida aperta [fSBA]) versus neonatally operated spina bifida aperta [nSBA]) on segmental neurological leg condition. METHOD:   Between 2003 and 2009, the fetal surgical

Social discourses of healthy eating. A market segmentation approach.

Science.gov (United States)

Chrysochou, Polymeros; Askegaard, Søren; Grunert, Klaus G; Kristensen, Dorthe Brogård

2010-10-01

This paper proposes a framework of discourses regarding consumers' healthy eating as a useful conceptual scheme for market segmentation purposes. The objectives are: (a) to identify the appropriate number of health-related segments based on the underlying discursive subject positions of the framework, (b) to validate and further describe the segments based on their socio-demographic characteristics and attitudes towards healthy eating, and (c) to explore differences across segments in types of associations with food and health, as well as perceptions of food healthfulness.316 Danish consumers participated in a survey that included measures of the underlying subject positions of the proposed framework, followed by a word association task that aimed to explore types of associations with food and health, and perceptions of food healthfulness. A latent class clustering approach revealed three consumer segments: the Common, the Idealists and the Pragmatists. Based on the addressed objectives, differences across the segments are described and implications of findings are discussed.

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.

Fuzzy clustering-based segmented attenuation correction in whole-body PET

CERN Document Server

Zaidi, H; Boudraa, A; Slosman, DO

2001-01-01

Segmented-based attenuation correction is now a widely accepted technique to reduce noise contribution of measured attenuation correction. In this paper, we present a new method for segmenting transmission images in positron emission tomography. This reduces the noise on the correction maps while still correcting for differing attenuation coefficients of specific tissues. Based on the Fuzzy C-Means (FCM) algorithm, the method segments the PET transmission images into a given number of clusters to extract specific areas of differing attenuation such as air, the lungs and soft tissue, preceded by a median filtering procedure. The reconstructed transmission image voxels are therefore segmented into populations of uniform attenuation based on the human anatomy. The clustering procedure starts with an over-specified number of clusters followed by a merging process to group clusters with similar properties and remove some undesired substructures using anatomical knowledge. The method is unsupervised, adaptive and a...

The Monte Carlo performance benchmark test - AIMS, specifications and first results

Energy Technology Data Exchange (ETDEWEB)

Hoogenboom, J. Eduard, E-mail: j.e.hoogenboom@tudelft.nl [Faculty of Applied Sciences, Delft University of Technology (Netherlands); Martin, William R., E-mail: wrm@umich.edu [Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI (United States); Petrovic, Bojan, E-mail: Bojan.Petrovic@gatech.edu [Nuclear and Radiological Engineering, Georgia Institute of Technology, Atlanta, GA (United States)

2011-07-01

The Monte Carlo performance benchmark for detailed power density calculation in a full-size reactor core is organized under the auspices of the OECD NEA Data Bank. It aims at monitoring over a range of years the increase in performance, measured in terms of standard deviation and computer time, of Monte Carlo calculation of the power density in small volumes. A short description of the reactor geometry and composition is discussed. One of the unique features of the benchmark exercise is the possibility to upload results from participants at a web site of the NEA Data Bank which enables online analysis of results and to graphically display how near we are at the goal of doing a detailed power distribution calculation with acceptable statistical uncertainty in an acceptable computing time. First results are discussed which show that 10 to 100 billion histories must be simulated to reach a standard deviation of a few percent in the estimated power of most of the requested the fuel zones. Even when using a large supercomputer, a considerable speedup is still needed to reach the target of 1 hour computer time. An outlook is given of what to expect from this benchmark exercise over the years. Possible extensions of the benchmark for specific issues relevant in current Monte Carlo calculation for nuclear reactors are also discussed. (author)

The Monte Carlo performance benchmark test - AIMS, specifications and first results

International Nuclear Information System (INIS)

Hoogenboom, J. Eduard; Martin, William R.; Petrovic, Bojan

2011-01-01

The Monte Carlo performance benchmark for detailed power density calculation in a full-size reactor core is organized under the auspices of the OECD NEA Data Bank. It aims at monitoring over a range of years the increase in performance, measured in terms of standard deviation and computer time, of Monte Carlo calculation of the power density in small volumes. A short description of the reactor geometry and composition is discussed. One of the unique features of the benchmark exercise is the possibility to upload results from participants at a web site of the NEA Data Bank which enables online analysis of results and to graphically display how near we are at the goal of doing a detailed power distribution calculation with acceptable statistical uncertainty in an acceptable computing time. First results are discussed which show that 10 to 100 billion histories must be simulated to reach a standard deviation of a few percent in the estimated power of most of the requested the fuel zones. Even when using a large supercomputer, a considerable speedup is still needed to reach the target of 1 hour computer time. An outlook is given of what to expect from this benchmark exercise over the years. Possible extensions of the benchmark for specific issues relevant in current Monte Carlo calculation for nuclear reactors are also discussed. (author)

Two-stage atlas subset selection in multi-atlas based image segmentation

Energy Technology Data Exchange (ETDEWEB)

Zhao, Tingting, E-mail: tingtingzhao@mednet.ucla.edu; Ruan, Dan, E-mail: druan@mednet.ucla.edu [The Department of Radiation Oncology, University of California, Los Angeles, California 90095 (United States)

2015-06-15

Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors

Two-stage atlas subset selection in multi-atlas based image segmentation.

Science.gov (United States)

Zhao, Tingting; Ruan, Dan

2015-06-01

Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. The authors have developed a novel two-stage atlas

Two-stage atlas subset selection in multi-atlas based image segmentation

International Nuclear Information System (INIS)

Zhao, Tingting; Ruan, Dan

2015-01-01

Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors

Measuring tourist satisfaction: a factor-cluster segmentation approach

OpenAIRE

Andriotis, Konstantinos; Agiomirgianakis, George; Mihiotis, Athanasios

2008-01-01

Tourist satisfaction has been considered as a tool for increasing destination competitiveness. In an attempt to gain a better understanding of tourists’ satisfaction in an island mass destination this study has taken Crete as a case with the aim to identify the underlying dimensions of tourists’ satisfaction, to investigate whether tourists could be grouped into distinct segments and to examine the significant difference between the segments and sociodemographic and travel arrangement charact...

Market segmentation of mobile communications in SEE region

Directory of Open Access Journals (Sweden)

Domazet Anto

2006-01-01

Full Text Available In the focus of all activities are customers of mobile services on mobile communications market. As the basis of telecommunication network and services development, as also for creating an optimal marketing-mix from mobile operators' side, we have investigated the needs, motivations and customer behavior and have made analysis mobile communication customers on the SEE Region market. The aim of this analysis is identification of the regional segments and following their growth, size and profitability. At the end, we have contributed the suggestions for creating the marketing-mix using a strategy of marketing differentiation, which implicit optimal combination of all marketing-mix elements for each regional segment separately. For identified segments we have set up an estimation model of significant key factors on the particular segments, because of more efficient creation of marketing instruments.

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

Science.gov (United States)

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

Medical image segmentation using improved FCM

Institute of Scientific and Technical Information of China (English)

ZHANG XiaoFeng; ZHANG CaiMing; TANG WenJing; WEI ZhenWen

2012-01-01

Image segmentation is one of the most important problems in medical image processing,and the existence of partial volume effect and other phenomena makes the problem much more complex. Fuzzy Cmeans,as an effective tool to deal with PVE,however,is faced with great challenges in efficiency.Aiming at this,this paper proposes one improved FCM algorithm based on the histogram of the given image,which will be denoted as HisFCM and divided into two phases.The first phase will retrieve several intervals on which to compute cluster centroids,and the second one will perform image segmentation based on improved FCM algorithm.Compared with FCM and other improved algorithms,HisFCM is of much higher efficiency with satisfying results.Experiments on medical images show that HisFCM can achieve good segmentation results in less than 0.1 second,and can satisfy real-time requirements of medical image processing.

Segmentation in sport services: a typology of fitness customers

Directory of Open Access Journals (Sweden)

Josef Voráček

2016-02-01

Full Text Available This article considers customer typology in fitness centres. The main aim of our survey is to state the basic segments of fitness customers and create their typology. A survey was conducted on a sample of 1004 respondents from 48 fitness centres. We used questionnaires and latent class analysis for the assessment and interpretation of data. The results of our research are as follows: we identified 6 segments of typical customers, of which three are male (we called them student, shark, mature and three are female (manager, hunter, and student. Each segment is influenced primarily by the age of customers, from which we can develop further characteristics, such as education, income, marital status, etc. Male segments use the main workout area above all, whilst female segments use a much wider range of services offered, for example group exercises, personal training, and cardio theatres.

Formation Features of the Customer Segments for the Network Organizations in the Smart Era

Directory of Open Access Journals (Sweden)

Elena V. Yaroshenko

2017-01-01

Full Text Available Modern network society is based on the advances of information era of Smart, connecting information and communication technologies, intellectual resources and new forms of managing in the global electronic space. It leads to domination of network forms of the organization of economic activity. Many experts prove the importance of segmentation process of consumers when developing competitive strategy of the organization. Every company needs a competent segmentation of the customer base, allowing to concentrate the attention on satisfaction of requirements of the most perspective client segments. The network organizations have specific characteristics; therefore, it is important to understand how they can influence on the formation of client profiles. It causes the necessity of the network organizations’ research in terms of management of high-profitable client segments.The aim of this study is to determine the characteristics of the market segmentation and to choose the key customers for the network organizations. This purpose has defined the statement and the solution of the following tasks: to explore characteristic features of the network forms of the organization of economic activity of the companies, their prospects, Smart technologies’ influence on them; to reveal the work importance with different client profiles; to explore the existing methods and tools of formation of key customer segments; to define criteria for selection of key groups; to reveal the characteristics of customer segments’ formation for the network organizations.In the research process, methods of the system analysis, a method of analogies, methods of generalizations, a method of the expert evaluations, methods of classification and clustering were applied.This paper explores the characteristics and principles of functioning of network organizations, the appearance of which is directly linked with the development of Smart society. It shows the influence on the

Name segmentation using hidden Markov models and its application in record linkage

Directory of Open Access Journals (Sweden)

Rita de Cassia Braga Gonçalves

2014-10-01

Full Text Available This study aimed to evaluate the use of hidden Markov models (HMM for the segmentation of person names and its influence on record linkage. A HMM was applied to the segmentation of patient’s and mother’s names in the databases of the Mortality Information System (SIM, Information Subsystem for High Complexity Procedures (APAC, and Hospital Information System (AIH. A sample of 200 patients from each database was segmented via HMM, and the results were compared to those from segmentation by the authors. The APAC-SIM and APAC-AIH databases were linked using three different segmentation strategies, one of which used HMM. Conformity of segmentation via HMM varied from 90.5% to 92.5%. The different segmentation strategies yielded similar results in the record linkage process. This study suggests that segmentation of Brazilian names via HMM is no more effective than traditional segmentation approaches in the linkage process.

Variational segmentation problems using prior knowledge in imaging and vision

DEFF Research Database (Denmark)

Fundana, Ketut

This dissertation addresses variational formulation of segmentation problems using prior knowledge. Variational models are among the most successful approaches for solving many Computer Vision and Image Processing problems. The models aim at finding the solution to a given energy functional defined......, prior knowledge is needed to obtain the desired solution. The introduction of shape priors in particular, has proven to be an effective way to segment objects of interests. Firstly, we propose a prior-based variational segmentation model to segment objects of interest in image sequences, that can deal....... Many objects have high variability in shape and orientation. This often leads to unsatisfactory results, when using a segmentation model with single shape template. One way to solve this is by using more sophisticated shape models. We propose to incorporate shape priors from a shape sub...

Validating PET segmentation of thoracic lesions-is 4D PET necessary?

DEFF Research Database (Denmark)

Nielsen, M. S.; Carl, J.

2017-01-01

Respiratory-induced motions are prone to degrade the positron emission tomography (PET) signal with the consequent loss of image information and unreliable segmentations. This phantom study aims to assess the discrepancies relative to stationary PET segmentations, of widely used semiautomatic PET...... segmentation methods on heterogeneous target lesions influenced by motion during image acquisition. Three target lesions included dual F-18 Fluoro-deoxy-glucose (FDG) tracer concentrations as high-and low tracer activities relative to the background. Four different tracer concentration arrangements were...... segmented using three SUV threshold methods (Max40%, SUV40% and 2.5SUV) and a gradient based method (GradientSeg). Segmentations in static 3D-PET scans (PETsta) specified the reference conditions for the individual segmentation methods, target lesions and tracer concentrations. The motion included PET...

Who puts the most energy into energy conservation? A segmentation of energy consumers based on energy-related behavioral characteristics

International Nuclear Information System (INIS)

Sütterlin, Bernadette; Brunner, Thomas A.; Siegrist, Michael

2011-01-01

The present paper aims to identify and describe different types of energy consumers in a more comprehensive way than previous segmentation studies using cluster analysis. Energy consumers were segmented based on their energy-related behavioral characteristics. In addition to purchase- and curtailment-related energy-saving behavior, consumer classification was also based on acceptance of policy measures and energy-related psychosocial factors, so the used behavioral segmentation base was more comprehensive compared to other studies. Furthermore, differentiation between the energy-saving purchase of daily products, such as food, and of energy efficient appliances allowed a more differentiated characterization of the energy consumer segments. The cluster analysis revealed six energy consumer segments: the idealistic, the selfless inconsequent, the thrifty, the materialistic, the convenience-oriented indifferent, and the problem-aware well-being-oriented energy consumer. Findings emphasize that using a broader and more distinct behavioral base is crucial for an adequate and differentiated description of energy consumer types. The paper concludes by highlighting the most promising energy consumer segments and discussing possible segment-specific marketing and policy strategies. - Highlights: ► By applying a cluster-analytic approach, new energy consumer segments are identified. ► A comprehensive, differentiated description of the different energy consumer types is provided. ► A distinction between purchase of daily products and energy efficient appliances is essential. ► Behavioral variables are a more suitable base for segmentation than general characteristics.

Segmental volvulus in the neonate: A particular clinical entity.

Science.gov (United States)

Khen-Dunlop, Naziha; Beaudoin, Sylvie; Marion, Blandine; Rousseau, Véronique; Giuseppi, Agnes; Nicloux, Muriel; Grevent, David; Salomon, Laurent J; Aigrain, Yves; Lapillonne, Alexandre; Sarnacki, Sabine

2017-03-01

Complete intestinal volvulus is mainly related to congenital anomalies of the so-called intestinal malrotation, whereas segmental volvulus appears as a distinct entity, mostly observed during the perinatal period. Because these two situations are still lumped together, the aim of this study was to describe the particular condition of neonatal segmental volvulus. We analyzed the circumstances of diagnosis and management of 17 consecutives neonates operated for segmental volvulus more than a 10-year period in a single institution. During the same period, 19 cases of neonatal complete midgut volvulus were operated. Prenatal US exam anomalies were observed in 16/17 (94%) of segmental volvulus, significantly more frequently than in complete volvulus (p=0.003). Intestinal malposition was described peroperatively in all cases of complete volvulus, but also in 4/17 segmental volvulus (23%). Intestinal resection was performed in 88% of segmental volvulus when only one extensive intestinal necrosis was observed in complete volvulus. Parenteral nutrition was required in all patients with segmental volvulus with a median duration of 50days (range 5-251). Segmental volvulus occurs mainly prenatally and leads to fetal ultrasound anomalies. This situation, despite a limited length of intestinal loss, is associated to significant postnatal morbidity. Treatment study. Level IV. Copyright © 2016 Elsevier Inc. All rights reserved.

Document flow segmentation for business applications

Science.gov (United States)

Daher, Hani; Belaïd, Abdel

2013-12-01

The aim of this paper is to propose a document flow supervised segmentation approach applied to real world heterogeneous documents. Our algorithm treats the flow of documents as couples of consecutive pages and studies the relationship that exists between them. At first, sets of features are extracted from the pages where we propose an approach to model the couple of pages into a single feature vector representation. This representation will be provided to a binary classifier which classifies the relationship as either segmentation or continuity. In case of segmentation, we consider that we have a complete document and the analysis of the flow continues by starting a new document. In case of continuity, the couple of pages are assimilated to the same document and the analysis continues on the flow. If there is an uncertainty on whether the relationship between the couple of pages should be classified as a continuity or segmentation, a rejection is decided and the pages analyzed until this point are considered as a "fragment". The first classification already provides good results approaching 90% on certain documents, which is high at this level of the system.

Head segmentation in vertebrates

OpenAIRE

Kuratani, Shigeru; Schilling, Thomas

2008-01-01

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

Segmentation of electric energy customers by specific niches; Segmentacao de clientes de energia eletrica por nichos especiais

Energy Technology Data Exchange (ETDEWEB)

Silva, Ana Lucia Rodrigues da; Jannuzzi, Gilberto de Martino [Universidade Estadual de Campinas (UNICAMP), SP (Brazil)], E-mail: jannuzzi@fen.unicamp.br

2009-04-15

The article presents the classic segmentation used in electric energy industry for large customers. The paper argues the limitations of this classification, as well as, the potentialities to classify customers for specific niches, the example of that already occurs in other competitive sectors of the economy. Twelve potential forms for classifying large customers in electricity industry are presented: geographic localization; value of the invoice; sector of productive activity; types of share holding composition and enterprise management; forms and characteristics of the use of the electric energy in the final units; degree of technological sophistication; client relation cost benefit; common factors in energy process of purchase; brand associated with the customer; extraordinary factors, such as, urgency, application and volume of energy; personal characteristics of the purchaser in charge of the operation; former-customers who moved from the captive market to the free market and vice versa. The article concludes proposing a new methodology to identify the specific niches of customers in the electric sector, as well as the inductive and restrictive factors of this methodology. (author)

Lung tumor segmentation in PET images using graph cuts.

Science.gov (United States)

Ballangan, Cherry; Wang, Xiuying; Fulham, Michael; Eberl, Stefan; Feng, David Dagan

2013-03-01

The aim of segmentation of tumor regions in positron emission tomography (PET) is to provide more accurate measurements of tumor size and extension into adjacent structures, than is possible with visual assessment alone and hence improve patient management decisions. We propose a segmentation energy function for the graph cuts technique to improve lung tumor segmentation with PET. Our segmentation energy is based on an analysis of the tumor voxels in PET images combined with a standardized uptake value (SUV) cost function and a monotonic downhill SUV feature. The monotonic downhill feature avoids segmentation leakage into surrounding tissues with similar or higher PET tracer uptake than the tumor and the SUV cost function improves the boundary definition and also addresses situations where the lung tumor is heterogeneous. We evaluated the method in 42 clinical PET volumes from patients with non-small cell lung cancer (NSCLC). Our method improves segmentation and performs better than region growing approaches, the watershed technique, fuzzy-c-means, region-based active contour and tumor customized downhill. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Design of segmented thermoelectric generator based on cost-effective and light-weight thermoelectric alloys

International Nuclear Information System (INIS)

Kim, Hee Seok; Kikuchi, Keiko; Itoh, Takashi; Iida, Tsutomu; Taya, Minoru

2014-01-01

Highlights: • Segmented thermoelectric (TE) module operating at 500 °C for combustion engine system. • Si based light-weight TE generator increases the specific power density [W/kg]. • Study of contact resistance at the bonding interfaces maximizing output power. • Accurate agreement of the theoretical predictions with experimental results. - Abstract: A segmented thermoelectric (TE) generator was designed with higher temperature segments composed of n-type Mg 2 Si and p-type higher manganese silicide (HMS) and lower temperature segments composed of n- and p-type Bi–Te based compounds. Since magnesium and silicon based TE alloys have low densities, they produce a TE module with a high specific power density that is suitable for airborne applications. A two-pair segmented π-shaped TE generator was assembled with low contact resistance materials across bonding interfaces. The peak specific power density of this generator was measured at 42.9 W/kg under a 498 °C temperature difference, which has a good agreement with analytical predictions

Interactive vs. automatic ultrasound image segmentation methods for staging hepatic lipidosis.

NARCIS (Netherlands)

Weijers, G.; Starke, A.; Haudum, A.; Thijssen, J.M.; Rehage, J.; Korte, C.L. de

2010-01-01

The aim of this study was to test the hypothesis that automatic segmentation of vessels in ultrasound (US) images can produce similar or better results in grading fatty livers than interactive segmentation. A study was performed in postpartum dairy cows (N=151), as an animal model of human fatty

EFFECTS OF PARENT ARTERY SEGMENTATION AND ANEURISMALWALL ELASTICITY ON PATIENT-SPECIFIC HEMODYNAMIC SIMULATIONS

Institute of Scientific and Technical Information of China (English)

CHEN Jia-liang; DING Guang-hong; YANG Xin-jian; LI Hai-yun

2011-01-01

It is well known that hemodynamics and wall tension play an important role in the formation,growth and rupture of aneurysms.In the present study,the authors investigated the influence of parent artery segmentation and aneurismal-wall elasticity on patient-specific hemodynamic simulations with two patient-specific eases of cerebral aneurysms.Realistic models of the aneurysms were constructed from 3-D angiography images and blood flow dynamics was studied under physiologically representative waveform of inflow.For each aneurysm three computational models were constructed:Model 1 with more extensive upstream parent artery with the rigid arterial and aneurismal wall,Model 2 with the partial upstream parent artery with the elastic arterial and aneurismal wall,Model 3 with more extensive upstream parent artery with the rigid wall for arterial wall far from the aneurysm and the elastic wall for arterial wall near the aneurysm.The results show that Model 1 could predict complex intra-aneurismal flow patterns and wall shear stress distribution in the aneurysm,but is unable to give aneurismal wall deformation and tension,Model 2 demonstrates aneurismal wall deformation and tension,but fails to properly model inflow pattern contributed by the upstream parent artery,resulting in local misunderstanding Wall Shear Stress (WSS) distribution,Model 3 can overcome limitations of the former two models,and give an overall and accurate analysis on intra-aneurismal flow patterns,wall shear stress distribution,aneurismal-wall deformation and tension.Therefore we suggest that the proper length of extensive upstream parent artery and aneuri-smal-wall elasticity should be considered carefully in establishing computational model to predict the intra-aneurismal hemodynamic and wall tension.

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.

Language-universal constraints on speech segmentation

NARCIS (Netherlands)

Norris, D.; McQueen, J.M.; Cutler, A.; Butterfield, S.; Kearns, R.K.

2001-01-01

Two word-spotting experiments are reported that examine whether the Possible-Word Constraint (PWC; Norris, McQueen, Cutler & Butterfield, 1997) is a language-specific or language-universal strategy for the segmentation of continuous speech. The PWC disfavors parses which leave an impossible residue

Supply chain segmentation in the sporting goods industry

OpenAIRE

Roscoe, S.; Baker, P.

2014-01-01

The purpose of this paper is to explore the factors that influence supply chain segmentation when selling to consumers through retail chains. The initial research is based on a review of supply chain segmentation literature and the application of relevant parameters to a specific case study, comprising two major brands in the sporting goods industry. The empirical research itself comprises semi-structured interviews, covering demand planning, sales, marketing and supply chain managers, suppor...

MARKET SEGMENTATION PRACTICES OF RETAIL CROP INPUT FIRMS

OpenAIRE

Jay Akridge; Mike Boehlje; Allan Gray; Aaron Reimer

2007-01-01

While market segmentation and the associated idea of target marketing are not new, there are questions about how the strategy of market segmentation and target marketing is being used in retail agribusiness firms. Previous research has demonstrated that distinct groups of farmers/customers exist (Alexander). However, retail crop input firms tend to be of modest size and are geographically bound. Both lack of resources and confinement to a specific geographic market present challenges for succ...

Purchase decision involvement: Event management segments and related event behavior

Science.gov (United States)

Rodney B. Warnick; David C. Bojanic

2012-01-01

The goal of this research was to examine the relationships between different levels of event purchase decision involvement (PDI) segments and their respective event behaviors (e.g., expenditures, travel behavior, event consumption and satisfaction). The specific purpose was to answer two major research questions: 1) Can PDI identify different levels or segments of...

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

Fluid region segmentation in OCT images based on convolution neural network

Science.gov (United States)

Liu, Dong; Liu, Xiaoming; Fu, Tianyu; Yang, Zhou

2017-07-01

In the retinal image, characteristics of fluid have great significance for diagnosis in eye disease. In the clinical, the segmentation of fluid is usually conducted manually, but is time-consuming and the accuracy is highly depend on the expert's experience. In this paper, we proposed a segmentation method based on convolution neural network (CNN) for segmenting the fluid from fundus image. The B-scans of OCT are segmented into layers, and patches from specific region with annotation are used for training. After the data set being divided into training set and test set, network training is performed and a good segmentation result is obtained, which has a significant advantage over traditional methods such as threshold method.

Side chain requirements for affinity and specificity in D5, an HIV-1 antibody derived from the VH1-69 germline segment.

Science.gov (United States)

Stewart, Alex; Harrison, Joseph S; Regula, Lauren K; Lai, Jonathan R

2013-04-08

Analysis of factors contributing to high affinity antibody-protein interactions provides insight into natural antibody evolution, and guides the design of antibodies with new or enhanced function. We previously studied the interaction between antibody D5 and its target, a designed protein based on HIV-1 gp41 known as 5-Helix, as a model system [Da Silva, G. F.; Harrison, J. S.; Lai, J. R., Biochemistry, 2010, 49, 5464-5472]. Antibody D5 represents an interesting case study because it is derived from the VH1-69 germline segment; this germline segment is characterized by a hydrophobic second heavy chain complementarity determining region (HCDR2) that constitutes the major functional paratope in D5 and several antibodies derived from the same progenitor. Here we explore side chain requirements for affinity and specificity in D5 using phage display. Two D5-based libraries were prepared that contained diversity in all three light chain complementarity determining regions (LCDRs 1-3), and in the third HCDR (HCDR3). The first library allowed residues to vary among a restricted set of six amino acids (Tyr/Ala/Asp/Ser/His/Pro; D5-Lib-I). The second library was designed based on a survey of existing VH1-69 antibody structures (D5-Lib-II). Both libraries were subjected to multiple rounds of selection against 5-Helix, and individual clones characterized. We found that selectants from D5-Lib-I generally had moderate affinity and specificity, while many clones from D5-Lib-II exhibited D5-like properties. Additional analysis of the D5-Lib-II functional population revealed position-specific biases for particular amino acids, many that differed from the identity of those side chains in D5. Together these results suggest that there is some permissiveness for alternative side chains in the LCDRs and HCDR3 of D5, but that replacement with a minimal set of residues is not tolerated in this scaffold for 5-Helix recognition. This work provides novel information about this high

Strategies for regular segmented reductions on GPU

DEFF Research Database (Denmark)

Larsen, Rasmus Wriedt; Henriksen, Troels

2017-01-01

We present and evaluate an implementation technique for regular segmented reductions on GPUs. Existing techniques tend to be either consistent in performance but relatively inefficient in absolute terms, or optimised for specific workloads and thereby exhibiting bad performance for certain input...... is in the context of the Futhark compiler, the implementation technique is applicable to any library or language that has a need for segmented reductions. We evaluate the technique on four microbenchmarks, two of which we also compare to implementations in the CUB library for GPU programming, as well as on two...

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.

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.

Intracranial aneurysm segmentation in 3D CT angiography: Method and quantitative validation with and without prior noise filtering

International Nuclear Information System (INIS)

Firouzian, Azadeh; Manniesing, Rashindra; Flach, Zwenneke H.; Risselada, Roelof; Kooten, Fop van; Sturkenboom, Miriam C.J.M.; Lugt, Aad van der; Niessen, Wiro J.

2011-01-01

Intracranial aneurysm volume and shape are important factors for predicting rupture risk, for pre-surgical planning and for follow-up studies. To obtain these parameters, manual segmentation can be employed; however, this is a tedious procedure, which is prone to inter- and intra-observer variability. Therefore there is a need for an automated method, which is accurate, reproducible and reliable. This study aims to develop and validate an automated method for segmenting intracranial aneurysms in Computed Tomography Angiography (CTA) data. Also, it is investigated whether prior smoothing improves segmentation robustness and accuracy. The proposed segmentation method is implemented in the level set framework, more specifically Geodesic Active Surfaces, in which a surface is evolved to capture the aneurysmal wall via an energy minimization approach. The energy term is composed of three different image features, namely; intensity, gradient magnitude and intensity variance. The method requires minimal user interaction, i.e. a single seed point inside the aneurysm needs to be placed, based on which image intensity statistics of the aneurysm are derived and used in defining the energy term. The method has been evaluated on 15 aneurysms in 11 CTA data sets by comparing the results to manual segmentations performed by two expert radiologists. Evaluation measures were Similarity Index, Average Surface Distance and Volume Difference. The results show that the automated aneurysm segmentation method is reproducible, and performs in the range of inter-observer variability in terms of accuracy. Smoothing by nonlinear diffusion with appropriate parameter settings prior to segmentation, slightly improves segmentation accuracy.

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.

ASSESSING INTERNATIONAL MARKET SEGMENTATION APPROACHES: RELATED LITERATURE AT A GLANCE AND SUGGESSTIONS FOR GLOBAL COMPANIES

OpenAIRE

Nacar, Ramazan; Uray, Nimet

2015-01-01

With the increasing role of globalization, international market segmentation has become a critical success factor for global companies, which aim for international market expansion. Despite the practice of numerous methods and bases for international market segmentation, international market segmentation is still a complex and an under-researched area. By considering all these issues, underdeveloped and under-researched international market segmentation bases such as social, cultural, psychol...

Intravascular ultrasound assessment of remodelling and reference segment plaque burden in type-2 diabetic patients

DEFF Research Database (Denmark)

Jensen, Lisette Okkels; Thayssen, Per; Mintz, Gary S

2007-01-01

AIMS: Intravascular ultrasound (IVUS) assesses arterial remodelling by comparing the lesion external elastic membrane (EEM) with the reference segments; however, reference segments are rarely disease-free. The aim was to assess lesion and reference segment remodelling and plaque burden in patients...... with type-2 diabetes mellitus. METHODS AND RESULTS: We used pre-intervention IVUS to study 62 de novo lesions in 43 patients with type-2 diabetes mellitus. The lesion site was the image slice with the smallest lumen cross-sectional area (CSA). The proximal and distal reference segments were the most normal...... size [slope = -0.12 (95% CI -0.17 to -0.07); P type-2 diabetes mellitus. CONCLUSION: Lesions in type-2 diabetic patients are different from previous reports in non-diabetics. Lesions in type-2 diabetics are characterized by a large reference segment plaque burden...

HealthStyles: a new psychographic segmentation system for health care marketers.

Science.gov (United States)

Endresen, K W; Wintz, J C

1988-01-01

HealthStyles is a new psychographic segmentation system specifically designed for the health care industry. This segmentation system goes beyond traditional geographic and demographic analysis and examines health-related consumer attitudes and behaviors. Four statistically distinct "styles" of consumer health care preferences have been identified. The profiles of the four groups have substantial marketing implications in terms of design and promotion of products and services. Each segment of consumers also has differing expectations of physician behavior.

Automatic liver volume segmentation and fibrosis classification

Science.gov (United States)

Bal, Evgeny; Klang, Eyal; Amitai, Michal; Greenspan, Hayit

2018-02-01

In this work, we present an automatic method for liver segmentation and fibrosis classification in liver computed-tomography (CT) portal phase scans. The input is a full abdomen CT scan with an unknown number of slices, and the output is a liver volume segmentation mask and a fibrosis grade. A multi-stage analysis scheme is applied to each scan, including: volume segmentation, texture features extraction and SVM based classification. Data contains portal phase CT examinations from 80 patients, taken with different scanners. Each examination has a matching Fibroscan grade. The dataset was subdivided into two groups: first group contains healthy cases and mild fibrosis, second group contains moderate fibrosis, severe fibrosis and cirrhosis. Using our automated algorithm, we achieved an average dice index of 0.93 ± 0.05 for segmentation and a sensitivity of 0.92 and specificity of 0.81for classification. To the best of our knowledge, this is a first end to end automatic framework for liver fibrosis classification; an approach that, once validated, can have a great potential value in the clinic.

Segmentation of British Sign Language (BSL): Mind the gap!

NARCIS (Netherlands)

Orfanidou, E.; McQueen, J.M.; Adam, R.; Morgan, G.

2015-01-01

This study asks how users of British Sign Language (BSL) recognize individual signs in connected sign sequences. We examined whether this is achieved through modality-specific or modality-general segmentation procedures. A modality-specific feature of signed languages is that, during continuous

Fully automatic segmentation of left atrium and pulmonary veins in late gadolinium-enhanced MRI: Towards objective atrial scar assessment.

Science.gov (United States)

Tao, Qian; Ipek, Esra Gucuk; Shahzad, Rahil; Berendsen, Floris F; Nazarian, Saman; van der Geest, Rob J

2016-08-01

To realize objective atrial scar assessment, this study aimed to develop a fully automatic method to segment the left atrium (LA) and pulmonary veins (PV) from late gadolinium-enhanced (LGE) magnetic resonance imaging (MRI). The extent and distribution of atrial scar, visualized by LGE-MRI, provides important information for clinical treatment of atrial fibrillation (AF) patients. Forty-six AF patients (age 62 ± 8, 14 female) who underwent cardiac MRI prior to RF ablation were included. A contrast-enhanced MR angiography (MRA) sequence was acquired for anatomy assessment followed by an LGE sequence for LA scar assessment. A fully automatic segmentation method was proposed consisting of two stages: 1) global segmentation by multiatlas registration; and 2) local refinement by 3D level-set. These automatic segmentation results were compared with manual segmentation. The LA and PVs were automatically segmented in all subjects. Compared with manual segmentation, the method yielded a surface-to-surface distance of 1.49 ± 0.65 mm in the LA region when using both MRA and LGE, and 1.80 ± 0.93 mm when using LGE alone (P automatic and manual segmentation was comparable to the interobserver difference (P = 0.8 in LA region and P = 0.7 in PV region). We developed a fully automatic method for LA and PV segmentation from LGE-MRI, with comparable performance to a human observer. Inclusion of an MRA sequence further improves the segmentation accuracy. The method leads to automatic generation of a patient-specific model, and potentially enables objective atrial scar assessment for AF patients. J. Magn. Reson. Imaging 2016;44:346-354. © 2016 Wiley Periodicals, Inc.

Multi-atlas Based Segmentation Editing with Interaction-Guided Constraints

OpenAIRE

Park, Sang Hyun; Gao, Yaozong; Shen, Dinggang

2015-01-01

We propose a novel multi-atlas based segmentation method to address the editing scenario, when given an incomplete segmentation along with a set of training label images. Unlike previous multi-atlas based methods, which depend solely on appearance features, we incorporate interaction-guided constraints to find appropriate training labels and derive their voting weights. Specifically, we divide user interactions, provided on erroneous parts, into multiple local interaction combinations, and th...

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

STRATEGI SEGMENTING, TARGETING, POSITIONING SERTA STRATEGI HARGA PADA PERUSAHAAN KECAP BLEKOK DI CILACAP

OpenAIRE

Wijaya, Hari; Sirine, Hani

2017-01-01

To win the market competition, companies must have segmenting, targeting, positioning strategy and pricing strategy. This study aims to determine segmenting, targeting, positioning strategy as well as the company's pricing strategies on Kecap Blekok Company in Cilacap. Methods of data collection in this study using interviews and documentation. The analysis technique used is descriptive analysis techniques. The results showed market segment of Kecap Blekok Company is the lower middle class, t...

SAAS-CNV: A Joint Segmentation Approach on Aggregated and Allele Specific Signals for the Identification of Somatic Copy Number Alterations with Next-Generation Sequencing Data.

Science.gov (United States)

Zhang, Zhongyang; Hao, Ke

2015-11-01

Cancer genomes exhibit profound somatic copy number alterations (SCNAs). Studying tumor SCNAs using massively parallel sequencing provides unprecedented resolution and meanwhile gives rise to new challenges in data analysis, complicated by tumor aneuploidy and heterogeneity as well as normal cell contamination. While the majority of read depth based methods utilize total sequencing depth alone for SCNA inference, the allele specific signals are undervalued. We proposed a joint segmentation and inference approach using both signals to meet some of the challenges. Our method consists of four major steps: 1) extracting read depth supporting reference and alternative alleles at each SNP/Indel locus and comparing the total read depth and alternative allele proportion between tumor and matched normal sample; 2) performing joint segmentation on the two signal dimensions; 3) correcting the copy number baseline from which the SCNA state is determined; 4) calling SCNA state for each segment based on both signal dimensions. The method is applicable to whole exome/genome sequencing (WES/WGS) as well as SNP array data in a tumor-control study. We applied the method to a dataset containing no SCNAs to test the specificity, created by pairing sequencing replicates of a single HapMap sample as normal/tumor pairs, as well as a large-scale WGS dataset consisting of 88 liver tumors along with adjacent normal tissues. Compared with representative methods, our method demonstrated improved accuracy, scalability to large cancer studies, capability in handling both sequencing and SNP array data, and the potential to improve the estimation of tumor ploidy and purity.

Cyanide sulphur transferase from the gut and body segments of ...

African Journals Online (AJOL)

Our results show total rhodanese activities of 1434.50 RU and 2274.28 RU and specific activities of 108.01 RUmg-1 and 83.1901 RUmg-1 in the gut and body segments of H. africanus respectively. The optimum temperature of 25 °C and optimum pH of 10.5 were obtained for both the gut and body segments enzymes.

Summation and Cancellation Effects on QRS and ST-Segment Changes Induced by Simultaneous Regional Myocardial Ischemia.

Science.gov (United States)

Vives-Borrás, Miquel; Jorge, Esther; Amorós-Figueras, Gerard; Millán, Xavier; Arzamendi, Dabit; Cinca, Juan

2018-01-01

Simultaneous ischemia in two myocardial regions is a potentially lethal clinical condition often unrecognized whose corresponding electrocardiographic (ECG) patterns have not yet been characterized. Thus, this study aimed to determine the QRS complex and ST-segment changes induced by concurrent ischemia in different myocardial regions elicited by combined double occlusion of the three main coronary arteries. For this purpose, 12 swine were randomized to combination of 5-min single and double coronary artery occlusion: Group 1: left Circumflex (LCX) and right (RCA) coronary arteries ( n = 4); Group 2: left anterior descending artery (LAD) and LCX ( n = 4) and; Group 3: LAD and RCA ( n = 4). QRS duration and ST-segment displacement were measured in 15-lead ECG. As compared with single occlusion, double LCX+RCA blockade induced significant QRS widening of about 40 ms in nearly all ECG leads and magnification of the ST-segment depression in leads V1-V3 (maximal 228% in lead V3, p ST-segment elevation in precordial leads (maximal attenuation of 60% in lead V3 in LAD+LCX and 86% in lead V5 in LAD+RCA, p ST-segment elevation in leads V7-V9 was a specific sign of single LCX occlusion. In conclusion, concurrent infero-lateral ischemia was associated with a marked summation effect of the ECG changes previously elicited by each single ischemic region. By contrast, a cancellation effect on ST-segment changes with no QRS widening was observed when the left anterior descending artery was involved.

TOURISM SEGMENTATION BASED ON TOURISTS PREFERENCES: A MULTIVARIATE APPROACH

Directory of Open Access Journals (Sweden)

Sérgio Dominique Ferreira

2010-11-01

Full Text Available Over the last decades, tourism became one of the most important sectors of the international economy. Specifically in Portugal and Brazil, its contribution to Gross Domestic Product (GDP and job creation is quite relevant. In this sense, to follow a strong marketing approach on the management of tourism resources of a country comes to be paramount. Such an approach should be based on innovations which help unveil the preferences of tourists with accuracy, turning it into a competitive advantage. In this context, the main objective of the present study is to illustrate the importance and benefits associated with the use of multivariate methodologies for market segmentation. Another objective of this work is to illustrate on the importance of a post hoc segmentation. In this work, the authors applied a Cluster Analysis, with a hierarchical method followed by an  optimization method. The main results of this study allow the identification of five clusters that are distinguished by assigning special importance to certain tourism attributes at the moment of choosing a specific destination. Thus, the authors present the advantages of post hoc segmentation based on tourists’ preferences, in opposition to an a priori segmentation based on socio-demographic characteristics.

biomvRhsmm: Genomic Segmentation with Hidden Semi-Markov Model

Directory of Open Access Journals (Sweden)

Yang Du

2014-01-01

Full Text Available High-throughput technologies like tiling array and next-generation sequencing (NGS generate continuous homogeneous segments or signal peaks in the genome that represent transcripts and transcript variants (transcript mapping and quantification, regions of deletion and amplification (copy number variation, or regions characterized by particular common features like chromatin state or DNA methylation ratio (epigenetic modifications. However, the volume and output of data produced by these technologies present challenges in analysis. Here, a hidden semi-Markov model (HSMM is implemented and tailored to handle multiple genomic profile, to better facilitate genome annotation by assisting in the detection of transcripts, regulatory regions, and copy number variation by holistic microarray or NGS. With support for various data distributions, instead of limiting itself to one specific application, the proposed hidden semi-Markov model is designed to allow modeling options to accommodate different types of genomic data and to serve as a general segmentation engine. By incorporating genomic positions into the sojourn distribution of HSMM, with optional prior learning using annotation or previous studies, the modeling output is more biologically sensible. The proposed model has been compared with several other state-of-the-art segmentation models through simulation benchmarking, which shows that our efficient implementation achieves comparable or better sensitivity and specificity in genomic segmentation.

Technical Safety Requirements for the B695 Segment

Energy Technology Data Exchange (ETDEWEB)

Laycak, D

2008-09-11

This document contains Technical Safety Requirements (TSRs) for the Radioactive and Hazardous Waste Management (RHWM) Division's B695 Segment of the Decontamination and Waste Treatment Facility (DWTF) at Lawrence Livermore National Laboratory (LLNL). The TSRs constitute requirements regarding the safe operation of the B695 Segment. The TSRs are derived from the Documented Safety Analysis (DSA) for the B695 Segment (LLNL 2007). The analysis presented there determined that the B695 Segment is a low-chemical hazard, Hazard Category 3, nonreactor nuclear facility. The TSRs consist primarily of inventory limits as well as controls to preserve the underlying assumptions in the hazard analyses. Furthermore, appropriate commitments to safety programs are presented in the administrative controls section of the TSRs. The B695 Segment (B695 and the west portion of B696) is a waste treatment and storage facility located in the northeast quadrant of the LLNL main site. The approximate area and boundary of the B695 Segment are shown in the B695 Segment DSA. Activities typically conducted in the B695 Segment include container storage, lab-packing, repacking, overpacking, bulking, sampling, waste transfer, and waste treatment. B695 is used to store and treat radioactive, mixed, and hazardous waste, and it also contains equipment used in conjunction with waste processing operations to treat various liquid and solid wastes. The portion of the building called Building 696 Solid Waste Processing Area (SWPA), also referred to as B696S in this report, is used primarily to manage solid radioactive, mixed, and hazardous waste. Operations specific to the SWPA include sorting and segregating waste, lab-packing, sampling, and crushing empty drums that previously contained waste. Furthermore, a Waste Packaging Unit will be permitted to treat hazardous and mixed waste. RHWM generally processes LLW with no, or extremely low, concentrations of transuranics (i.e., much less than 100 n

Technical Safety Requirements for the B695 Segment

International Nuclear Information System (INIS)

Laycak, D.

2008-01-01

This document contains Technical Safety Requirements (TSRs) for the Radioactive and Hazardous Waste Management (RHWM) Division's B695 Segment of the Decontamination and Waste Treatment Facility (DWTF) at Lawrence Livermore National Laboratory (LLNL). The TSRs constitute requirements regarding the safe operation of the B695 Segment. The TSRs are derived from the Documented Safety Analysis (DSA) for the B695 Segment (LLNL 2007). The analysis presented there determined that the B695 Segment is a low-chemical hazard, Hazard Category 3, nonreactor nuclear facility. The TSRs consist primarily of inventory limits as well as controls to preserve the underlying assumptions in the hazard analyses. Furthermore, appropriate commitments to safety programs are presented in the administrative controls section of the TSRs. The B695 Segment (B695 and the west portion of B696) is a waste treatment and storage facility located in the northeast quadrant of the LLNL main site. The approximate area and boundary of the B695 Segment are shown in the B695 Segment DSA. Activities typically conducted in the B695 Segment include container storage, lab-packing, repacking, overpacking, bulking, sampling, waste transfer, and waste treatment. B695 is used to store and treat radioactive, mixed, and hazardous waste, and it also contains equipment used in conjunction with waste processing operations to treat various liquid and solid wastes. The portion of the building called Building 696 Solid Waste Processing Area (SWPA), also referred to as B696S in this report, is used primarily to manage solid radioactive, mixed, and hazardous waste. Operations specific to the SWPA include sorting and segregating waste, lab-packing, sampling, and crushing empty drums that previously contained waste. Furthermore, a Waste Packaging Unit will be permitted to treat hazardous and mixed waste. RHWM generally processes LLW with no, or extremely low, concentrations of transuranics (i.e., much less than 100 n

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

Segmentation Scheme for Safety Enhancement of Engineered Safety Features Component Control System

International Nuclear Information System (INIS)

Lee, Sangseok; Sohn, Kwangyoung; Lee, Junku; Park, Geunok

2013-01-01

Common Caused Failure (CCF) or undetectable failure would adversely impact safety functions of ESF-CCS in the existing nuclear power plants. We propose the segmentation scheme to solve these problems. Main function assignment to segments in the proposed segmentation scheme is based on functional dependency and critical function success path by using the dependency depth matrix. The segment has functional independence and physical isolation. The segmentation structure is that prohibit failure propagation to others from undetectable failures. Therefore, the segmentation system structure has robustness to undetectable failures. The segmentation system structure has functional diversity. The specific function in the segment defected by CCF, the specific function could be maintained by diverse control function that assigned to other segments. Device level control signals and system level control signals are separated and also control signal and status signals are separated due to signal transmission paths are allocated independently based on signal type. In this kind of design, single device failure or failures on signal path in the channel couldn't result in the loss of all segmented functions simultaneously. Thus the proposed segmentation function is the design scheme that improves availability of safety functions. In conventional ESF-CCS, the single controller generates the signal to control the multiple safety functions, and the reliability is achieved by multiplication within the channel. This design has a drawback causing the loss of multiple functions due to the CCF (Common Cause Failure) and single failure Heterogeneous controller guarantees the diversity ensuring the execution of safety functions against the CCF and single failure, but requiring a lot of resources like manpower and cost. The segmentation technology based on the compartmentalization and functional diversification decreases the CCF and single failure nonetheless the identical types of controllers

Segmentation Scheme for Safety Enhancement of Engineered Safety Features Component Control System

Energy Technology Data Exchange (ETDEWEB)

Lee, Sangseok; Sohn, Kwangyoung [Korea Reliability Technology and System, Daejeon (Korea, Republic of); Lee, Junku; Park, Geunok [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2013-05-15

Common Caused Failure (CCF) or undetectable failure would adversely impact safety functions of ESF-CCS in the existing nuclear power plants. We propose the segmentation scheme to solve these problems. Main function assignment to segments in the proposed segmentation scheme is based on functional dependency and critical function success path by using the dependency depth matrix. The segment has functional independence and physical isolation. The segmentation structure is that prohibit failure propagation to others from undetectable failures. Therefore, the segmentation system structure has robustness to undetectable failures. The segmentation system structure has functional diversity. The specific function in the segment defected by CCF, the specific function could be maintained by diverse control function that assigned to other segments. Device level control signals and system level control signals are separated and also control signal and status signals are separated due to signal transmission paths are allocated independently based on signal type. In this kind of design, single device failure or failures on signal path in the channel couldn't result in the loss of all segmented functions simultaneously. Thus the proposed segmentation function is the design scheme that improves availability of safety functions. In conventional ESF-CCS, the single controller generates the signal to control the multiple safety functions, and the reliability is achieved by multiplication within the channel. This design has a drawback causing the loss of multiple functions due to the CCF (Common Cause Failure) and single failure Heterogeneous controller guarantees the diversity ensuring the execution of safety functions against the CCF and single failure, but requiring a lot of resources like manpower and cost. The segmentation technology based on the compartmentalization and functional diversification decreases the CCF and single failure nonetheless the identical types of

Adductor magnus: An EMG investigation into proximal and distal portions and direction specific action.

Science.gov (United States)

Benn, Matthew L; Pizzari, Tania; Rath, Leanne; Tucker, Kylie; Semciw, Adam I

2018-05-01

Cadaveric studies indicate that adductor magnus is structurally partitioned into at least two regions. The aim of this study was to investigate the direction-specific actions of proximal and distal portions of adductor magnus, and in doing so determine if these segments have distinct functional roles. Fine-wire EMG electrodes were inserted into two portions of adductor magnus of 12 healthy young adults. Muscle activity was recorded during maximum voluntary isometric contractions (MVICs) across eight tests (hip flexion/extension, internal/external rotation, abduction, and adduction at 0°, 45°, and 90° hip flexion). Median activity within each action (normalized to peak) was compared between segments using repeated measures nonparametric tests (α = 0.05). An effect size (ES = z-score/√sample size) was calculated to determine the magnitude of difference between muscle segments. The relative contribution of each muscle segment differed significantly during internal rotation (P magnus has at least two functionally unique regions. Differences were most evident during rotation. The different direction-specific actions may imply that each segment performs separate roles in hip stability and movement. These findings may have implications on injury prevention and rehabilitation for adductor-related groin injuries, hamstring strain injury, and hip pathology. Clin. Anat. 31:535-543, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

ENTERPRISE RESTRUCTURING AIM AND TYPES

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S. P. Baranenko

2011-01-01

Full Text Available Enterprise restructuring is aimed at adapting it to market conditions and improving its competitiveness through selection of most effective model of using material, technical, technological, organizational, commercial, economical, financial, tax-related and other resources with due account of the demand. Restructuring classification signs and types as well as restructuring aims specific for industrial enterprises are provided for.

Delphi definition of the EADC-ADNI Harmonized Protocol for hippocampal segmentation on magnetic resonance

NARCIS (Netherlands)

Boccardi, M.; Bocchetta, M.; Apostolova, L.G.; Barnes, J.; Bartzokis, G.; Corbetta, G.; deCarli, C.; DeToledo-Morrell, L.; Firbank, M.; Ganzola, R.; Gerritsen, L.; Henneman, W.; Killiany, R.J.; Malykhin, N.; Pasqualetti, P.; Pruessner, J.C.; Redolfi, A.; Robitaille, N.; Soininen, H.; Tolomeo, D.; Wang, L.; Watson, C.; Wolf, H; Duvernoy, H.; Duchesne, S.; Jack, C.R.; Frisoni, G. B.

2015-01-01

Background: This study aimed to have international experts converge on a harmonized definition of whole hippocampus boundaries and segmentation procedures, to define standard operating procedures for magnetic resonance (MR)-based manual hippocampal segmentation. Methods: The panel received a

Segmentation of British Sign Language (BSL): mind the gap!

Science.gov (United States)

Orfanidou, Eleni; McQueen, James M; Adam, Robert; Morgan, Gary

2015-01-01

This study asks how users of British Sign Language (BSL) recognize individual signs in connected sign sequences. We examined whether this is achieved through modality-specific or modality-general segmentation procedures. A modality-specific feature of signed languages is that, during continuous signing, there are salient transitions between sign locations. We used the sign-spotting task to ask if and how BSL signers use these transitions in segmentation. A total of 96 real BSL signs were preceded by nonsense signs which were produced in either the target location or another location (with a small or large transition). Half of the transitions were within the same major body area (e.g., head) and half were across body areas (e.g., chest to hand). Deaf adult BSL users (a group of natives and early learners, and a group of late learners) spotted target signs best when there was a minimal transition and worst when there was a large transition. When location changes were present, both groups performed better when transitions were to a different body area than when they were within the same area. These findings suggest that transitions do not provide explicit sign-boundary cues in a modality-specific fashion. Instead, we argue that smaller transitions help recognition in a modality-general way by limiting lexical search to signs within location neighbourhoods, and that transitions across body areas also aid segmentation in a modality-general way, by providing a phonotactic cue to a sign boundary. We propose that sign segmentation is based on modality-general procedures which are core language-processing mechanisms.

A web-based procedure for liver segmentation in CT images

Science.gov (United States)

Yuan, Rong; Luo, Ming; Wang, Luyao; Xie, Qingguo

2015-03-01

Liver segmentation in CT images has been acknowledged as a basic and indispensable part in systems of computer aided liver surgery for operation design and risk evaluation. In this paper, we will introduce and implement a web-based procedure for liver segmentation to help radiologists and surgeons get an accurate result efficiently and expediently. Several clinical datasets are used to evaluate the accessibility and the accuracy. This procedure seems a promising approach for extraction of liver volumetry of various shapes. Moreover, it is possible for user to access the segmentation wherever the Internet is available without any specific machine.

Proposal of a segmentation procedure for skid resistance data

International Nuclear Information System (INIS)

Tejeda, S. V.; Tampier, Hernan de Solominihac; Navarro, T.E.

2008-01-01

Skin resistance of pavements presents a high spatial variability along a road. This pavement characteristic is directly related to wet weather accidents; therefore, it is important to identify and characterize the skid resistance of homogeneous segments along a road in order to implement proper road safety management. Several data segmentation methods have been applied to other pavement characteristics (e.g. roughness). However, no application to skin resistance data was found during the literature review for this study. Typical segmentation methods are rather too general or too specific to ensure a detailed segmentation of skid resistance data, which can be used for managing pavement performance. The main objective of this paper is to propose a procedure for segmenting skid resistance data, based on existing data segmentation methods. The procedure needs to be efficient and to fulfill road management requirements. The proposed procedure considers the Leverage method to identify outlier data, the CUSUM method to accomplish initial data segmentation and a statistical method to group consecutive segments that are statistically similar. The statistical method applies the Student's t-test of mean equities, along with analysis of variance and the Tuckey test for the multiple comparison of means. The proposed procedure was applied to a sample of skid resistance data measured with SCRIM (Side Force Coefficient Routine Investigatory Machine) on a 4.2 km section of Chilean road and was compared to conventional segmentation methods. Results showed that the proposed procedure is more efficient than the conventional segmentation procedures, achieving the minimum weighted sum of square errors (SSEp) with all the identified segments statistically different. Due to its mathematical basis, proposed procedure can be easily adapted and programmed for use in road safety management. (author)

Segmentation of nodules on chest computed tomography for growth assessment

International Nuclear Information System (INIS)

Mullally, William; Betke, Margrit; Wang Jingbin; Ko, Jane P.

2004-01-01

Several segmentation methods to evaluate growth of small isolated pulmonary nodules on chest computed tomography (CT) are presented. The segmentation methods are based on adaptively thresholding attenuation levels and use measures of nodule shape. The segmentation methods were first tested on a realistic chest phantom to evaluate their performance with respect to specific nodule characteristics. The segmentation methods were also tested on sequential CT scans of patients. The methods' estimation of nodule growth were compared to the volume change calculated by a chest radiologist. The best method segmented nodules on average 43% smaller or larger than the actual nodule when errors were computed across all nodule variations on the phantom. Some methods achieved smaller errors when examined with respect to certain nodule properties. In particular, on the phantom individual methods segmented solid nodules to within 23% of their actual size and nodules with 60.7 mm3 volumes to within 14%. On the clinical data, none of the methods examined showed a statistically significant difference in growth estimation from the radiologist

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)

Segmentation and packaging reactor vessels internals

International Nuclear Information System (INIS)

Boucau, Joseph

2014-01-01

Document available in abstract form only, full text follows: With more than 25 years of experience in the development of reactor vessel internals and reactor vessel segmentation and packaging technology, Westinghouse has accumulated significant know-how in the reactor dismantling market. The primary challenges of a segmentation and packaging project are to separate the highly activated materials from the less-activated materials and package them into appropriate containers for disposal. Since disposal cost is a key factor, it is important to plan and optimize waste segmentation and packaging. The choice of the optimum cutting technology is also important for a successful project implementation and depends on some specific constraints. Detailed 3-D modeling is the basis for tooling design and provides invaluable support in determining the optimum strategy for component cutting and disposal in waste containers, taking account of the radiological and packaging constraints. The usual method is to start at the end of the process, by evaluating handling of the containers, the waste disposal requirements, what type and size of containers are available for the different disposal options, and working backwards to select a cutting method and finally the cut geometry required. The 3-D models can include intelligent data such as weight, center of gravity, curie content, etc, for each segmented piece, which is very useful when comparing various cutting, handling and packaging options. The detailed 3-D analyses and thorough characterization assessment can draw the attention to material potentially subject to clearance, either directly or after certain period of decay, to allow recycling and further disposal cost reduction. Westinghouse has developed a variety of special cutting and handling tools, support fixtures, service bridges, water filtration systems, video-monitoring systems and customized rigging, all of which are required for a successful reactor vessel internals

Affinity imaging mass spectrometry (AIMS): high-throughput screening for specific small molecule interactions with frozen tissue sections.

Science.gov (United States)

Yoshimi, T; Kawabata, S; Taira, S; Okuno, A; Mikawa, R; Murayama, S; Tanaka, K; Takikawa, O

2015-11-07

A novel screening system, using affinity imaging mass spectrometry (AIMS), has been developed to identify protein aggregates or organ structures in unfixed human tissue. Frozen tissue sections are positioned on small (millimetre-scale) stainless steel chips and incubated with an extensive library of small molecules. Candidate molecules showing specific affinity for the tissue section are identified by imaging mass spectrometry (IMS). As an example application, we screened over a thousand compounds against Alzheimer's disease (AD) brain tissue and identified several compounds with high affinity for AD brain sections containing tau deposits compared to age-matched controls. It should also be possible to use AIMS to isolate chemical compounds with affinity for tissue structures or components that have been extensively modified by events such as oxidation, phosphorylation, acetylation, aggregation, racemization or truncation, for example, due to aging. It may also be applicable to biomarker screening programs.

Spinal segmental dysgenesis

Directory of Open Access Journals (Sweden)

N Mahomed

2009-06-01

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

Segmentation of dance movement: Effects of expertise, visual familiarity, motor experience and music

Directory of Open Access Journals (Sweden)

Bettina E. Bläsing

2015-01-01

Full Text Available According to event segmentation theory, action perception depends on sensory cues and prior knowledge, and the segmentation of observed actions is crucial for understanding and memorizing these actions. While most activities in everyday life are characterized by external goals and interaction with objects or persons, this does not necessarily apply to dance-like actions. We investigated to what extent visual familiarity of the observed movement and accompanying music influence the segmentation of a dance phrase in dancers of different skill level and non-dancers. In Experiment 1, dancers and non-dancers repeatedly watched a video clip showing a dancer performing a choreographed dance phrase and indicated segment boundaries by key press. Dancers generally defined less segment boundaries than non-dancers, specifically in the first trials in which visual familiarity with the phrase was low. Music increased the number of segment boundaries in the non-dancers and decreased it in the dancers. The results suggest that dance expertise reduces the number of perceived segment boundaries in an observed dance phrase, and that the ways visual familiarity and music affect movement segmentation are modulated by dance expertise. In a second experiment, motor experience was added as factor, based on empirical evidence suggesting that action perception is modified by visual and motor expertise in different ways. In Experiment 2, the same task as in Experiment 1 was performed by dance amateurs, and was repeated by the same participants after they had learned to dance the presented dance phrase. Less segment boundaries were defined in the middle trials after participants had learned to dance the phrase, and music reduced the number of segment boundaries before learning. The results suggest that specific motor experience of the observed movement influences its perception and anticipation and makes segmentation broader, but not to the same degree as dance expertise

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

Directory of Open Access Journals (Sweden)

Yang Fan

2012-10-01

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

Superiority Of Graph-Based Visual Saliency GVS Over Other Image Segmentation Methods

Directory of Open Access Journals (Sweden)

Umu Lamboi

2017-02-01

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

A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images

Directory of Open Access Journals (Sweden)

David Vázquez

2017-01-01

Full Text Available Colorectal cancer (CRC is the third cause of cancer death worldwide. Currently, the standard approach to reduce CRC-related mortality is to perform regular screening in search for polyps and colonoscopy is the screening tool of choice. The main limitations of this screening procedure are polyp miss rate and the inability to perform visual assessment of polyp malignancy. These drawbacks can be reduced by designing decision support systems (DSS aiming to help clinicians in the different stages of the procedure by providing endoluminal scene segmentation. Thus, in this paper, we introduce an extended benchmark of colonoscopy image segmentation, with the hope of establishing a new strong benchmark for colonoscopy image analysis research. The proposed dataset consists of 4 relevant classes to inspect the endoluminal scene, targeting different clinical needs. Together with the dataset and taking advantage of advances in semantic segmentation literature, we provide new baselines by training standard fully convolutional networks (FCNs. We perform a comparative study to show that FCNs significantly outperform, without any further postprocessing, prior results in endoluminal scene segmentation, especially with respect to polyp segmentation and localization.

Evaluation of segmental left ventricular wall motion by equilibrium gated radionuclide ventriculography.

Science.gov (United States)

Van Nostrand, D; Janowitz, W R; Holmes, D R; Cohen, H A

1979-01-01

The ability of equilibrium gated radionuclide ventriculography to detect segmental left ventricular (LV) wall motion abnormalities was determined in 26 patients undergoing cardiac catheterization. Multiple gated studies obtained in 30 degrees right anterior oblique and 45 degrees left anterior oblique projections, played back in a movie format, were compared to the corresponding LV ventriculograms. The LV wall in the two projections was divided into eight segments. Each segment was graded as normal, hypokinetic, akinetic, dyskinetic, or indeterminate. Thirteen percent of the segments in the gated images were indeterminate; 24 out of 27 of these were proximal or distal inferior wall segments. There was exact agreement in 86% of the remaining segments. The sensitivity of the radionuclide technique for detecting normal versus any abnormal wall motion was 71%, with a specificity of 99%. Equilibrium gated ventriculography is an excellent noninvasive technique for evaluating segmental LV wall motion. It is least reliable in assessing the proximal inferior wall and interventricular septum.

Novel techniques for enhancement and segmentation of acne vulgaris lesions.

Science.gov (United States)

Malik, A S; Humayun, J; Kamel, N; Yap, F B-B

2014-08-01

More than 99% acne patients suffer from acne vulgaris. While diagnosing the severity of acne vulgaris lesions, dermatologists have observed inter-rater and intra-rater variability in diagnosis results. This is because during assessment, identifying lesion types and their counting is a tedious job for dermatologists. To make the assessment job objective and easier for dermatologists, an automated system based on image processing methods is proposed in this study. There are two main objectives: (i) to develop an algorithm for the enhancement of various acne vulgaris lesions; and (ii) to develop a method for the segmentation of enhanced acne vulgaris lesions. For the first objective, an algorithm is developed based on the theory of high dynamic range (HDR) images. The proposed algorithm uses local rank transform to generate the HDR images from a single acne image followed by the log transformation. Then, segmentation is performed by clustering the pixels based on Mahalanobis distance of each pixel from spectral models of acne vulgaris lesions. Two metrics are used to evaluate the enhancement of acne vulgaris lesions, i.e., contrast improvement factor (CIF) and image contrast normalization (ICN). The proposed algorithm is compared with two other methods. The proposed enhancement algorithm shows better result than both the other methods based on CIF and ICN. In addition, sensitivity and specificity are calculated for the segmentation results. The proposed segmentation method shows higher sensitivity and specificity than other methods. This article specifically discusses the contrast enhancement and segmentation for automated diagnosis system of acne vulgaris lesions. The results are promising that can be used for further classification of acne vulgaris lesions for final grading of the lesions. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

Dietary Behaviours, Impulsivity and Food Involvement: Identification of Three Consumer Segments.

Science.gov (United States)

Sarmugam, Rani; Worsley, Anthony

2015-09-18

This study aims to (1) identify consumer segments based on consumers' impulsivity and level of food involvement, and (2) examine the dietary behaviours of each consumer segment. An Internet-based cross-sectional survey was conducted among 530 respondents. The mean age of the participants was 49.2 ± 16.6 years, and 27% were tertiary educated. Two-stage cluster analysis revealed three distinct segments; "impulsive, involved" (33.4%), "rational, health conscious" (39.2%), and "uninvolved" (27.4%). The "impulsive, involved" segment was characterised by higher levels of impulsivity and food involvement (importance of food) compared to the other two segments. This segment also reported significantly more frequent consumption of fast foods, takeaways, convenience meals, salted snacks and use of ready-made sauces and mixes in cooking compared to the "rational, health conscious" consumers. They also reported higher frequency of preparing meals at home, cooking from scratch, using ready-made sauces and mixes in cooking and higher vegetable consumption compared to the "uninvolved" consumers. The findings show the need for customised approaches to the communication and promotion of healthy eating habits.

Wavelet-filtering of symbolic music representations for folk tune segmentation and classification

DEFF Research Database (Denmark)

Velarde, Gissel; Weyde, Tillman; Meredith, David

2013-01-01

The aim of this study is to evaluate a machine-learning method in which symbolic representations of folk songs are segmented and classified into tune families with Haar-wavelet filtering. The method is compared with previously proposed Gestalt based method. Melodies are represented as discrete...... coefficients’ local maxima to indicate local boundaries and classify segments by means of k-nearest neighbours based on standard vector-metrics (Euclidean, cityblock), and compare the results to a Gestalt-based segmentation method and metrics applied directly to the pitch signal. We found that the wavelet...

The effectiveness of endobronchial therapy in patients with chemo-resistant tuberculosis when specific process is localized in the lungs apical segments

Directory of Open Access Journals (Sweden)

V. M. Khlystun

2017-08-01

Full Text Available Objective – to study the effectiveness of the additional methods of endobronchial pathology treatment in patients with chemo-resistant tuberculosis (CRTB of lungs, that aimed to treat a specific process in bronchi when destructions are localized in the apical segments (S1+2 of lungs. Materials and methods. In order to investigate effectiveness of the additional methods of endobronchial pathology treatment of bronchial mucosa 79 patients with CRTB of lungs were examined. They were divided into 3 groups: basic 1 group, which included 27 patients who were treated by using antimycobacterial drugs endobronchial introduction to S1+2 with further implementation of intraorganic electrophoresis in S1+2 zone in combination with systemic receiving of antimycobacterial drugs; the comparison basic 2 group 27 patients who were treated with systemic antimycobacterial therapy in combination with antituberculosis drugs inhalations; and the group included – 25 patients who received only systemic antimycobacterial therapy. Groups were compared by the severity of the process, age and gender. Tracheobronchial tree fiber-bronchoscopy in patients with CRTB of lungs was carried out on the basis of phthisiology and pulmonology department of ZSMU in communal institution "Zaporizhzhia regional antituberculosis dispensary", by the author on their own. Character of bronchial mucosa was examined under anesthesia by fiber-bronchoscopes of company "Olympus" (Japan. Bronchial tree pathology was described according to N. V. Shesterynoy, A. N. Kaliuk (1975 classification. Results of the study were processed with modern methods of analysis on a personal computer with using the Statistical Package license software Statistica® for Windows 6.0 (StatSoft Inc., № AXXR712 D833214FAN5. Results. The use of antimycobacterial drugs endobronchial introduction to S1+2 with further implementation of intraorganic electrophoresis in S1+2 zone contributed significantly increase the

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.

Segmentation of fluorescence microscopy cell images using unsupervised mining.

Science.gov (United States)

Du, Xian; Dua, Sumeet

2010-05-28

The accurate measurement of cell and nuclei contours are critical for the sensitive and specific detection of changes in normal cells in several medical informatics disciplines. Within microscopy, this task is facilitated using fluorescence cell stains, and segmentation is often the first step in such approaches. Due to the complex nature of cell issues and problems inherent to microscopy, unsupervised mining approaches of clustering can be incorporated in the segmentation of cells. In this study, we have developed and evaluated the performance of multiple unsupervised data mining techniques in cell image segmentation. We adapt four distinctive, yet complementary, methods for unsupervised learning, including those based on k-means clustering, EM, Otsu's threshold, and GMAC. Validation measures are defined, and the performance of the techniques is evaluated both quantitatively and qualitatively using synthetic and recently published real data. Experimental results demonstrate that k-means, Otsu's threshold, and GMAC perform similarly, and have more precise segmentation results than EM. We report that EM has higher recall values and lower precision results from under-segmentation due to its Gaussian model assumption. We also demonstrate that these methods need spatial information to segment complex real cell images with a high degree of efficacy, as expected in many medical informatics applications.

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

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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

Segmented trapped vortex cavity

Science.gov (United States)

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

2010-01-01

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

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

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Praveen Agarwal

2017-06-01

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

Coronary Arteries Segmentation Based on the 3D Discrete Wavelet Transform and 3D Neutrosophic Transform

OpenAIRE

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

2015-01-01

Purpose. Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies. Methods. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband c...

Automated segmentation of pigmented skin lesions in multispectral imaging

International Nuclear Information System (INIS)

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

2005-01-01

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

A distance measurement between specific sites on the cytoplasmic surface of bovine rhodopsin in rod outer segment disk membranes.

Science.gov (United States)

Albert, A D; Watts, A; Spooner, P; Groebner, G; Young, J; Yeagle, P L

1997-08-14

Structural information on mammalian integral membrane proteins is scarce. As part of work on an alternative approach to the structure of bovine rhodopsin, a method was devised to obtain an intramolecular distance between two specific sites on rhodopsin while in the rod outer segment disk membrane. In this report, the distance between the rhodopsin kinase phosphorylation site(s) on the carboxyl terminal and the top of the third transmembrane helix was measured on native rhodopsin. Rhodopsin was labeled with a nuclear spin label (31P) by limited phosphorylation with rhodopsin kinase. Major phosphorylation occurs at serines 343 and 338 on the carboxyl terminal. The phosphorylated rhodopsin was then specifically labeled on cysteine 140 with an electron spin label. Magic angle spinning 31P-nuclear magnetic resonance revealed the resonance arising from the phosphorylated protein. The enhancement of the transverse relaxation of this resonance by the paramagnetic spin label was observed. The strength of this perturbation was used to determine the through-space distance between the phosphorylation site(s) and the spin label position. A distance of 18 +/- 3 A was obtained.

Multifrequency right-side, localized and segmental BIA obtained with different bioimpedance analysers

International Nuclear Information System (INIS)

Bogónez-Franco, P; McAdams, E; Nescolarde, L; Rosell-Ferrer, J

2015-01-01

The aim of this study is to compare two commercial bioimpedance analysers, BioparHom Z-Métrix and Impedimed SFB7, measuring the impedance of three different body segments. The segments measured were ‘right-side’ (or ‘whole-body’), ‘segmental right-lower limb’ and ‘localized longitudinal right-quadriceps’. The comparison was made on electrical models of each segment, including electrode–skin impedance, and in vivo on nine healthy volunteers. Both devices are designed to measure right-side impedances and, in the present study, as the length of the segment investigated decreased, the accuracy of the impedance measured was found to decrease. The accuracy of the devices was calculated via measurements performed on RC networks of known values. It was found that adding electrode–skin contact impedances in the electrical model affected the accuracy by both devices. (paper)

Appearance of femoropopliteal segment aneurysms in patients with abdominal aortic aneurysm

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Maksić Milanko

2012-01-01

Full Text Available Background/Aim. To promote better treatment outcome, as well as economic benefit it is very important to find out patients with simultaneous occurrence of both aortic and arterial aneurysms. The aim of this prospective study was to determine the frequency and factors affecting femoropopliteal (F-P segment aneurysms appearance in patients with abdominal aortic aneurysms (AAA. Methods. This study included 70 patients who had underwent elective or urgent surgery of AAA from January 1, 2006 to December 31, 2007. After ultrasonographic examination of F-P segment, all the patients were divided into two groups - those with adjunctive F-P segment aneurysm (n = 20 and the group of 50 patients with no adjunctive F-P segment aneurysm. In both groups demographic characteristics (gender, age, risk factors (diabetes mellitus, elevated serum levels of cholesterol and triglycerides, arterial hypertension, smoking, obesity and cardiovascular comorbidity (cerebrovascular desease, ischemic heart desease were investigated. Results. Twenty (28.57% patients who had been operated on because of AAA, had adjunctive aneurysmal desease of F-P segment. Diabetes was no statistically significantly more present among the patients who, beside AAA, had adjunctive aneurismal desease of F-P segment (χ2 = 0.04; DF = 1; p > 0.05. Also, in both groups there was no statistically significant difference in gender structure (χ2 = 2. 05; DF = 2; p > 0.05, age (χ2 = 5. 46; DF = 1; p > 0.05, total cholesterol level (χ2 = 0.89; DF = 1; p > 0.05 and triglyceride (χ2 = 0.89; DF = 1; p > 0.05 levels, the presence of arterial hypertension (χ2 = 1.38; DF = 2; p > 0.05, smoking (χ2 = 1.74; DF = 1; p > 0.05, obesity (χ2 = 1.76; DF = 1; p > 0.05 and presence of cerebrovascular desease (χ2 = 2.34; DF = 1; p > 0.05. Conversly, ischemic heart desease was statistically significantly more present among the patients who, beside AAA, had adjunctive aneurismal desease of F-P segment (χ2 = 5

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?

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Pravesh Yadav

2014-01-01

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

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

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Valéria Riscarolli

2014-08-01

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

Fluence map segmentation

International Nuclear Information System (INIS)

Rosenwald, J.-C.

2008-01-01

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

Strategic market segmentation

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Maričić Branko R.

2015-01-01

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

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

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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).

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.

Polarization image segmentation of radiofrequency ablated porcine myocardial tissue.

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Iftikhar Ahmad

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

Concrete Image Segmentation Based on Multiscale Mathematic Morphology Operators and Otsu Method

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Sheng-Bo Zhou

2015-01-01

Full Text Available The aim of the current study lies in the development of a reformative technique of image segmentation for Computed Tomography (CT concrete images with the strength grades of C30 and C40. The results, through the comparison of the traditional threshold algorithms, indicate that three threshold algorithms and five edge detectors fail to meet the demand of segmentation for Computed Tomography concrete images. The paper proposes a new segmentation method, by combining multiscale noise suppression morphology edge detector with Otsu method, which is more appropriate for the segmentation of Computed Tomography concrete images with low contrast. This method cannot only locate the boundaries between objects and background with high accuracy, but also obtain a complete edge and eliminate noise.

Soft-tissue segmentation and three-dimensional display with MR imaging

International Nuclear Information System (INIS)

Koenig, H.A.; Laub, G.

1987-01-01

The purpose of this study is to design a method capable of segmenting different soft-tissue types. The investigated cases were measured using fast three-dimensional (3D) sequences (FISP of fast low-angle shot) with isotropic voxel resolution of nearly 1 mm. The segmentation is based on the assumption that different tissue types are discernible by their morphologic and/or physical features. Surface reconstructions are then used to display specific tissue types from different viewing directions. This automatic procedure is applied to different head cases to represent specific tissues in 3D format. With 3D techniques, rotation of classified objects in cine format is performed for better topologic correlation and therapeutic planning

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

Science.gov (United States)

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

2017-09-01

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

Understanding the market for geographic information: A market segmentation and characteristics analysis

Science.gov (United States)

Piper, William S.; Mick, Mark W.

1994-01-01

Findings and results from a marketing research study are presented. The report identifies market segments and the product types to satisfy demand in each. An estimate of market size is based on the specific industries in each segment. A sample of ten industries was used in the study. The scientific study covered U.S. firms only.

Automatic comic page image understanding based on edge segment analysis

Science.gov (United States)

Liu, Dong; Wang, Yongtao; Tang, Zhi; Li, Luyuan; Gao, Liangcai

2013-12-01

Comic page image understanding aims to analyse the layout of the comic page images by detecting the storyboards and identifying the reading order automatically. It is the key technique to produce the digital comic documents suitable for reading on mobile devices. In this paper, we propose a novel comic page image understanding method based on edge segment analysis. First, we propose an efficient edge point chaining method to extract Canny edge segments (i.e., contiguous chains of Canny edge points) from the input comic page image; second, we propose a top-down scheme to detect line segments within each obtained edge segment; third, we develop a novel method to detect the storyboards by selecting the border lines and further identify the reading order of these storyboards. The proposed method is performed on a data set consisting of 2000 comic page images from ten printed comic series. The experimental results demonstrate that the proposed method achieves satisfactory results on different comics and outperforms the existing methods.

FBIH financial market segmentation on the basis of image factors

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Arnela Bevanda

2008-12-01

Full Text Available The aim of the study is to recognize, single out and define market segments useful for future marketing strategies, using certain statistical techniques on the basis of influence of various image factors of financial institutions. The survey included a total of 500 interviewees: 250 bank clients and 250 clients of insurance companies. Starting from the problem area and research goal, the following hypothesis has been formulated: Basic preferences of clients in regard of image factors while selecting financial institutions are different enough to be used as such for differentiating significant market segments of clients. Two segments have been singled out by cluster analysis and named, respectively, traditionalists and visualists. Results of the research confirmed the established hypothesis and pointed to the fact that managers in the financial institutions of the Federation of Bosnia and Herzegovina (FBIH must undertake certain corrective actions, especially when planning and implementing communication strategies, if they wish to maintain their competitiveness in serving both selected segments.

Rooting of stem segments from fig tree cultivars

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Rayane Barcelos Bisi

2016-06-01

Full Text Available Although Brazil is the largest fig (Ficus carica L. producer in the Southern Hemisphere, it mainly uses only one cultivar, ‘Roxo de Valinhos’. In addition, propagation is almost entirely through hardwood cuttings. Therefore, the aim of this study was to establish a propagation method that provides more successful rooting of stem segments of fig cultivars for the purpose of expanding the genetic base of the fig tree. The cultivars used were ‘Brunswick’, ‘Calabacita’, ‘Negro de Bursa’, ‘Mini Figo’, ‘Lampa Preta’, ‘Lemon’, ‘Troiano’,’ Nazaré’, ‘Três num Prato’, ‘Princesa’, ‘Colo de Dama’, ‘Montes’, ‘Bêbera Branca’, ‘Pingo de Mel’, and ‘Roxo de Valinhos’. The propagation methods used were layering, hardwood cuttings, nodal segments, herbaceous cuttings originating from the removal of sprouts, and herbaceous cuttings obtained during growth. We found that the propagation method influences the rooting of stem segments, and cultivars differ in their rooting potential.

Dietary Behaviours, Impulsivity and Food Involvement: Identification of Three Consumer Segments

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Rani Sarmugam

2015-09-01

Full Text Available This study aims to (1 identify consumer segments based on consumers’ impulsivity and level of food involvement, and (2 examine the dietary behaviours of each consumer segment. An Internet-based cross-sectional survey was conducted among 530 respondents. The mean age of the participants was 49.2 ± 16.6 years, and 27% were tertiary educated. Two-stage cluster analysis revealed three distinct segments; “impulsive, involved” (33.4%, “rational, health conscious” (39.2%, and “uninvolved” (27.4%. The “impulsive, involved” segment was characterised by higher levels of impulsivity and food involvement (importance of food compared to the other two segments. This segment also reported significantly more frequent consumption of fast foods, takeaways, convenience meals, salted snacks and use of ready-made sauces and mixes in cooking compared to the “rational, health conscious” consumers. They also reported higher frequency of preparing meals at home, cooking from scratch, using ready-made sauces and mixes in cooking and higher vegetable consumption compared to the “uninvolved” consumers. The findings show the need for customised approaches to the communication and promotion of healthy eating habits.

Quantifying coordination among the rearfoot, midfoot, and forefoot segments during running.

Science.gov (United States)

Takabayashi, Tomoya; Edama, Mutsuaki; Yokoyama, Erika; Kanaya, Chiaki; Kubo, Masayoshi

2018-03-01

Because previous studies have suggested that there is a relationship between injury risk and inter-segment coordination, quantifying coordination between the segments is essential. Even though the midfoot and forefoot segments play important roles in dynamic tasks, previous studies have mostly focused on coordination between the shank and rearfoot segments. This study aimed to quantify coordination among rearfoot, midfoot, and forefoot segments during running. Eleven healthy young men ran on a treadmill. The coupling angle, representing inter-segment coordination, was calculated using a modified vector coding technique. The coupling angle was categorised into four coordination patterns. During the absorption phase, rearfoot-midfoot coordination in the frontal planes was mostly in-phase (rearfoot and midfoot eversion with similar amplitudes). The present study found that the eversion of the midfoot with respect to the rearfoot was comparable in magnitude to the eversion of the rearfoot with respect to the shank. A previous study has suggested that disruption of the coordination between the internal rotation of the shank and eversion of the rearfoot leads to running injuries such as anterior knee pain. Thus, these data might be used in the future to compare to individuals with foot deformities or running injuries.

Identification of the two rotavirus genes determining neutralization specificities

International Nuclear Information System (INIS)

Offit, P.A.; Blavat, G.

1986-01-01

Bovine rotavirus NCDV and simian rotavirus SA-11 represent two distinct rotavirus serotypes. A genetic approach was used to determine which viral gene segments segregated with serotype-specific viral neutralization. There were 16 reassortant rotarviruses derived by coinfection of MA-104 cells in vitro with the SA-11 and NCDV strains. The parental origin of reassortant rotavirus double-stranded RNA segments was determined by gene segment mobility in polyacrylamide gels and by hybridization with radioactively labeled parental viral transcripts. The authors found that two rotavirus gene segments found previously to code for outer capsid proteins vp3 and vp7 cosegreated with virus neutralization specificities

Identification of the two rotavirus genes determining neutralization specificities

Energy Technology Data Exchange (ETDEWEB)

Offit, P.A.; Blavat, G.

1986-01-01

Bovine rotavirus NCDV and simian rotavirus SA-11 represent two distinct rotavirus serotypes. A genetic approach was used to determine which viral gene segments segregated with serotype-specific viral neutralization. There were 16 reassortant rotarviruses derived by coinfection of MA-104 cells in vitro with the SA-11 and NCDV strains. The parental origin of reassortant rotavirus double-stranded RNA segments was determined by gene segment mobility in polyacrylamide gels and by hybridization with radioactively labeled parental viral transcripts. The authors found that two rotavirus gene segments found previously to code for outer capsid proteins vp3 and vp7 cosegreated with virus neutralization specificities.

A general system for automatic biomedical image segmentation using intensity neighborhoods.

Science.gov (United States)

Chen, Cheng; Ozolek, John A; Wang, Wei; Rohde, Gustavo K

2011-01-01

Image segmentation is important with applications to several problems in biology and medicine. While extensively researched, generally, current segmentation methods perform adequately in the applications for which they were designed, but often require extensive modifications or calibrations before being used in a different application. We describe an approach that, with few modifications, can be used in a variety of image segmentation problems. The approach is based on a supervised learning strategy that utilizes intensity neighborhoods to assign each pixel in a test image its correct class based on training data. We describe methods for modeling rotations and variations in scales as well as a subset selection for training the classifiers. We show that the performance of our approach in tissue segmentation tasks in magnetic resonance and histopathology microscopy images, as well as nuclei segmentation from fluorescence microscopy images, is similar to or better than several algorithms specifically designed for each of these applications.

A General System for Automatic Biomedical Image Segmentation Using Intensity Neighborhoods

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Cheng Chen

2011-01-01

Full Text Available Image segmentation is important with applications to several problems in biology and medicine. While extensively researched, generally, current segmentation methods perform adequately in the applications for which they were designed, but often require extensive modifications or calibrations before being used in a different application. We describe an approach that, with few modifications, can be used in a variety of image segmentation problems. The approach is based on a supervised learning strategy that utilizes intensity neighborhoods to assign each pixel in a test image its correct class based on training data. We describe methods for modeling rotations and variations in scales as well as a subset selection for training the classifiers. We show that the performance of our approach in tissue segmentation tasks in magnetic resonance and histopathology microscopy images, as well as nuclei segmentation from fluorescence microscopy images, is similar to or better than several algorithms specifically designed for each of these applications.

The benefits of segmentation: Evidence from a South African bank and other studies

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Douw G. Breed

2017-09-01

Full Text Available We applied different modelling techniques to six data sets from different disciplines in the industry, on which predictive models can be developed, to demonstrate the benefit of segmentation in linear predictive modelling. We compared the model performance achieved on the data sets to the performance of popular non-linear modelling techniques, by first segmenting the data (using unsupervised, semi-supervised, as well as supervised methods and then fitting a linear modelling technique. A total of eight modelling techniques was compared. We show that there is no one single modelling technique that always outperforms on the data sets. Specifically considering the direct marketing data set from a local South African bank, it is observed that gradient boosting performed the best. Depending on the characteristics of the data set, one technique may outperform another. We also show that segmenting the data benefits the performance of the linear modelling technique in the predictive modelling context on all data sets considered. Specifically, of the three segmentation methods considered, the semi-supervised segmentation appears the most promising. Significance: The use of non-linear modelling techniques may not necessarily increase model performance when data sets are first segmented. No single modelling technique always performed the best. Applications of predictive modelling are unlimited; some examples of areas of application include database marketing applications; financial risk management models; fraud detection methods; medical and environmental predictive models.

Word segmentation with universal prosodic cues.

Science.gov (United States)

Endress, Ansgar D; Hauser, Marc D

2010-09-01

When listening to speech from one's native language, words seem to be well separated from one another, like beads on a string. When listening to a foreign language, in contrast, words seem almost impossible to extract, as if there was only one bead on the same string. This contrast reveals that there are language-specific cues to segmentation. The puzzle, however, is that infants must be endowed with a language-independent mechanism for segmentation, as they ultimately solve the segmentation problem for any native language. Here, we approach the acquisition problem by asking whether there are language-independent cues to segmentation that might be available to even adult learners who have already acquired a native language. We show that adult learners recognize words in connected speech when only prosodic cues to word-boundaries are given from languages unfamiliar to the participants. In both artificial and natural speech, adult English speakers, with no prior exposure to the test languages, readily recognized words in natural languages with critically different prosodic patterns, including French, Turkish and Hungarian. We suggest that, even though languages differ in their sound structures, they carry universal prosodic characteristics. Further, these language-invariant prosodic cues provide a universally accessible mechanism for finding words in connected speech. These cues may enable infants to start acquiring words in any language even before they are fine-tuned to the sound structure of their native language. Copyright © 2010. Published by Elsevier Inc.

Consumer segmentation based on the level of environmental responsibility

Directory of Open Access Journals (Sweden)

Marija Ham

2009-12-01

Full Text Available Doubtless, there is an environmentally responsible segment of consumers in the market. However, with an increasing number of suppliers entering the green market, it is no longer sufficient to be aware of this fact. What is needed now are complex strategies of segmentation, targeting and positioning. The aim of this paper was to provide a theoretical framework for understanding the key concepts related to the green consumer segment and to help create a clearer picture of Croatia’s green consumers by gathering secondary data from the available literature, previous research and primary data from own research. Primary research was conducted by means of a structured questionnaire on a sample of 552 respondents. The questionnaire was divided into three parts, each measuring, respectively, attitudes, knowledge and activities undertaken. After the segmentation (three segments: green, neutral and brown consumers, a chi-square test was used in an attempt to prove statistically significant differences when comparing the given segment structure with the respondents’ demographic characteristics. The results of this research describe the average green consumer in the Republic of Croatia as a person who is 55 and older, with higher or university education, who is married, who responds to the advertising claims about eco-friendliness of products and is influenced by those claims, who occasionally or frequently makes purchasing decisions and shows readiness to pay a 20 percent mark-up for an environmentally friendly product.

Market segmentation and eliciting tourists’ motives for visiting the Czech Republic

OpenAIRE

Ja. Valentová; Jo. Abrhám

2016-01-01

The aim of this article. The paper describes a research project focused on motivations to travel by potential and existing foreign visitors that was conducted in order to envisage the creation of a positive image and select the appropriate distribution and marketing promotional mix for the various segments of the Czech tourism market. The paper builds on research that has been already completed and yielded interestig results and further extends the researched themes and selected segments. The...

Selective Segmentation for Global Optimization of Depth Estimation in Complex Scenes

Directory of Open Access Journals (Sweden)

Sheng Liu

2013-01-01

Full Text Available This paper proposes a segmentation-based global optimization method for depth estimation. Firstly, for obtaining accurate matching cost, the original local stereo matching approach based on self-adapting matching window is integrated with two matching cost optimization strategies aiming at handling both borders and occlusion regions. Secondly, we employ a comprehensive smooth term to satisfy diverse smoothness request in real scene. Thirdly, a selective segmentation term is used for enforcing the plane trend constraints selectively on the corresponding segments to further improve the accuracy of depth results from object level. Experiments on the Middlebury image pairs show that the proposed global optimization approach is considerably competitive with other state-of-the-art matching approaches.

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

Correlates between kinematics and baropodometric measurements for an integrated in-vivo assessment of the segmental foot function in gait.

Science.gov (United States)

Giacomozzi, Claudia; Leardini, Alberto; Caravaggi, Paolo

2014-08-22

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

Patient Segmentation Analysis Offers Significant Benefits For Integrated Care And Support.

Science.gov (United States)

Vuik, Sabine I; Mayer, Erik K; Darzi, Ara

2016-05-01

Integrated care aims to organize care around the patient instead of the provider. It is therefore crucial to understand differences across patients and their needs. Segmentation analysis that uses big data can help divide a patient population into distinct groups, which can then be targeted with care models and intervention programs tailored to their needs. In this article we explore the potential applications of patient segmentation in integrated care. We propose a framework for population strategies in integrated care-whole populations, subpopulations, and high-risk populations-and show how patient segmentation can support these strategies. Through international case examples, we illustrate practical considerations such as choosing a segmentation logic, accessing data, and tailoring care models. Important issues for policy makers to consider are trade-offs between simplicity and precision, trade-offs between customized and off-the-shelf solutions, and the availability of linked data sets. We conclude that segmentation can provide many benefits to integrated care, and we encourage policy makers to support its use. Project HOPE—The People-to-People Health Foundation, Inc.

Simultaneous Whole-Brain Segmentation and White Matter Lesion Detection Using Contrast-Adaptive Probabilistic Models

DEFF Research Database (Denmark)

Puonti, Oula; Van Leemput, Koen

2016-01-01

In this paper we propose a new generative model for simultaneous brain parcellation and white matter lesion segmentation from multi-contrast magnetic resonance images. The method combines an existing whole-brain segmentation technique with a novel spatial lesion model based on a convolutional...... restricted Boltzmann machine. Unlike current state-of-the-art lesion detection techniques based on discriminative modeling, the proposed method is not tuned to one specific scanner or imaging protocol, and simultaneously segments dozens of neuroanatomical structures. Experiments on a public benchmark dataset...... in multiple sclerosis indicate that the method’s lesion segmentation accuracy compares well to that of the current state-of-the-art in the field, while additionally providing robust whole-brain segmentations....

Efficacy of CTA portography for preoperatively determining the segmental location of focal hepatic lesions

International Nuclear Information System (INIS)

Nelson, R.C.; Chemzmar, J.L.; Sugarbaker, P.H.; Bernardino, M.E.

1989-01-01

Using cross-sectional images to localize tumors to specific hepatic segments before resection might be difficult because the transverse scissura, an important segmental landmark, is approximately parallel to the axial plane. Since this plane is parallel to the main right and left portal pedicles, the authors postulated that they could localize lesions above this plane to segments 2,4A,7, or 8, and below this plane to segments 3, 4B,5, or 6. The authors have retrospectively evaluated, in a blinded fashion, 24 hepatic masses in 13 patients who underwent CTA-portography and subsequent tumor resection. Using this scheme, they have accurately predicted the primary segmental location in 22 (92%) of 24 surgically confirmed lesions

Holistic segmentation of the lung in cine MRI.

Science.gov (United States)

Kovacs, William; Hsieh, Nathan; Roth, Holger; Nnamdi-Emeratom, Chioma; Bandettini, W Patricia; Arai, Andrew; Mankodi, Ami; Summers, Ronald M; Yao, Jianhua

2017-10-01

Duchenne muscular dystrophy (DMD) is a childhood-onset neuromuscular disease that results in the degeneration of muscle, starting in the extremities, before progressing to more vital areas, such as the lungs. Respiratory failure and pneumonia due to respiratory muscle weakness lead to hospitalization and early mortality. However, tracking the disease in this region can be difficult, as current methods are based on breathing tests and are incapable of distinguishing between muscle involvements. Cine MRI scans give insight into respiratory muscle movements, but the images suffer due to low spatial resolution and poor signal-to-noise ratio. Thus, a robust lung segmentation method is required for accurate analysis of the lung and respiratory muscle movement. We deployed a deep learning approach that utilizes sequence-specific prior information to assist the segmentation of lung in cine MRI. More specifically, we adopt a holistically nested network to conduct image-to-image holistic training and prediction. One frame of the cine MRI is used in the training and applied to the remainder of the sequence ([Formula: see text] frames). We applied this method to cine MRIs of the lung in the axial, sagittal, and coronal planes. Characteristic lung motion patterns during the breathing cycle were then derived from the segmentations and used for diagnosis. Our data set consisted of 31 young boys, age [Formula: see text] years, 15 of whom suffered from DMD. The remaining 16 subjects were age-matched healthy volunteers. For validation, slices from inspiratory and expiratory cycles were manually segmented and compared with results obtained from our method. The Dice similarity coefficient for the deep learning-based method was [Formula: see text] for the sagittal view, [Formula: see text] for the axial view, and [Formula: see text] for the coronal view. The holistic neural network approach was compared with an approach using Demon's registration and showed superior performance. These

SU-E-J-142: Performance Study of Automatic Image-Segmentation Algorithms in Motion Tracking Via MR-IGRT

International Nuclear Information System (INIS)

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

2014-01-01

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

SU-E-J-142: Performance Study of Automatic Image-Segmentation Algorithms in Motion Tracking Via MR-IGRT

Energy Technology Data Exchange (ETDEWEB)

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

2014-06-01

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

Latent segmentation based count models: Analysis of bicycle safety in Montreal and Toronto.

Science.gov (United States)

Yasmin, Shamsunnahar; Eluru, Naveen

2016-10-01

The study contributes to literature on bicycle safety by building on the traditional count regression models to investigate factors affecting bicycle crashes at the Traffic Analysis Zone (TAZ) level. TAZ is a traffic related geographic entity which is most frequently used as spatial unit for macroscopic crash risk analysis. In conventional count models, the impact of exogenous factors is restricted to be the same across the entire region. However, it is possible that the influence of exogenous factors might vary across different TAZs. To accommodate for the potential variation in the impact of exogenous factors we formulate latent segmentation based count models. Specifically, we formulate and estimate latent segmentation based Poisson (LP) and latent segmentation based Negative Binomial (LNB) models to study bicycle crash counts. In our latent segmentation approach, we allow for more than two segments and also consider a large set of variables in segmentation and segment specific models. The formulated models are estimated using bicycle-motor vehicle crash data from the Island of Montreal and City of Toronto for the years 2006 through 2010. The TAZ level variables considered in our analysis include accessibility measures, exposure measures, sociodemographic characteristics, socioeconomic characteristics, road network characteristics and built environment. A policy analysis is also conducted to illustrate the applicability of the proposed model for planning purposes. This macro-level research would assist decision makers, transportation officials and community planners to make informed decisions to proactively improve bicycle safety - a prerequisite to promoting a culture of active transportation. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Dynamic multi-segmental postural control in patients with chronic non-specific low back pain compared to pain-free controls: A cross-sectional study.

Science.gov (United States)

McCaskey, Michael A; Wirth, Brigitte; Schuster-Amft, Corina; de Bruin, Eling D

2018-01-01

Reduced postural control is thought to contribute to the development and persistence of chronic non-specific low back pain (CNLBP). It is therefore frequently assessed in affected patients and commonly reported as the average amount of postural sway while standing upright under a variety of sensory conditions. These averaged linear outcomes, such as mean centre of pressure (CP) displacement or mean CP surface areas, may not reflect the true postural status. Adding nonlinear outcomes and multi-segmental kinematic analysis has been reported to better reflect the complexity of postural control and may detect subtler postural differences. In this cross-sectional study, a combination of linear and nonlinear postural parameters were assessed in patients with CNLBP (n = 24, 24-75 years, 9 females) and compared to symptom-free controls (CG, n = 34, 22-67 years, 11 females). Primary outcome was postural control measured by variance of joint configurations (uncontrolled manifold index, UI), confidence ellipse surface areas (CEA) and approximate entropy (ApEn) of CP dispersion during the response phase of a perturbed postural control task on a swaying platform. Secondary outcomes were segment excursions and clinical outcome correlates for pain and function. Non-parametric tests for group comparison with P-adjustment for multiple comparisons were conducted. Principal component analysis was applied to identify patterns of segmental contribution in both groups. CNLBP and CG performed similarly with respect to the primary outcomes. Comparison of joint kinematics revealed significant differences of hip (P postural differences in CNLBP patients with low to moderate pain status.

Selecting salient frames for spatiotemporal video modeling and segmentation.

Science.gov (United States)

Song, Xiaomu; Fan, Guoliang

2007-12-01

We propose a new statistical generative model for spatiotemporal video segmentation. The objective is to partition a video sequence into homogeneous segments that can be used as "building blocks" for semantic video segmentation. The baseline framework is a Gaussian mixture model (GMM)-based video modeling approach that involves a six-dimensional spatiotemporal feature space. Specifically, we introduce the concept of frame saliency to quantify the relevancy of a video frame to the GMM-based spatiotemporal video modeling. This helps us use a small set of salient frames to facilitate the model training by reducing data redundancy and irrelevance. A modified expectation maximization algorithm is developed for simultaneous GMM training and frame saliency estimation, and the frames with the highest saliency values are extracted to refine the GMM estimation for video segmentation. Moreover, it is interesting to find that frame saliency can imply some object behaviors. This makes the proposed method also applicable to other frame-related video analysis tasks, such as key-frame extraction, video skimming, etc. Experiments on real videos demonstrate the effectiveness and efficiency of the proposed method.

Validation of a model of left ventricular segmentation for interpretation of SPET myocardial perfusion images

Energy Technology Data Exchange (ETDEWEB)

Aepfelbacher, F.C.; Johnson, R.B.; Schwartz, J.G.; Danias, P.G. [Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA (United States); Chen, L.; Parker, R.A. [Biometrics Center, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA (United States); Parker, A.J. [Nuclear Medicine Division, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA (United States)

2001-11-01

Several models of left ventricular segmentation have been developed that assume a standard coronary artery distribution, and are currently used for interpretation of single-photon emission tomography (SPET) myocardial perfusion imaging. This approach has the potential for incorrect assignment of myocardial segments to vascular territories, possibly over- or underestimating the number of vessels with significant coronary artery disease (CAD). We therefore sought to validate a 17-segment model of myocardial perfusion by comparing the predefined coronary territory assignment with the actual angiographically derived coronary distribution. We examined 135 patients who underwent both coronary angiography and stress SPET imaging within 30 days. Individualized coronary distribution was determined by review of the coronary angiograms and used to identify the coronary artery supplying each of the 17 myocardial segments of the model. The actual coronary distribution was used to assess the accuracy of the assumed coronary distribution of the model. The sensitivities and specificities of stress SPET for detection of CAD in individual coronary arteries and the classification regarding perceived number of diseased coronary arteries were also compared between the two coronary distributions (actual and assumed). The assumed coronary distribution corresponded to the actual coronary anatomy in all but one segment (3). The majority of patients (80%) had 14 or more concordant segments. Sensitivities and specificities of stress SPET for detection of CAD in the coronary territories were similar, with the exception of the RCA territory, for which specificity for detection of CAD was better for the angiographically derived coronary artery distribution than for the model. There was 95% agreement between assumed and angiographically derived coronary distributions in classification to single- versus multi-vessel CAD. Reassignment of a single segment (segment 3) from the LCX to the LAD

Validation of a model of left ventricular segmentation for interpretation of SPET myocardial perfusion images

International Nuclear Information System (INIS)

Aepfelbacher, F.C.; Johnson, R.B.; Schwartz, J.G.; Danias, P.G.; Chen, L.; Parker, R.A.; Parker, A.J.

2001-01-01

Several models of left ventricular segmentation have been developed that assume a standard coronary artery distribution, and are currently used for interpretation of single-photon emission tomography (SPET) myocardial perfusion imaging. This approach has the potential for incorrect assignment of myocardial segments to vascular territories, possibly over- or underestimating the number of vessels with significant coronary artery disease (CAD). We therefore sought to validate a 17-segment model of myocardial perfusion by comparing the predefined coronary territory assignment with the actual angiographically derived coronary distribution. We examined 135 patients who underwent both coronary angiography and stress SPET imaging within 30 days. Individualized coronary distribution was determined by review of the coronary angiograms and used to identify the coronary artery supplying each of the 17 myocardial segments of the model. The actual coronary distribution was used to assess the accuracy of the assumed coronary distribution of the model. The sensitivities and specificities of stress SPET for detection of CAD in individual coronary arteries and the classification regarding perceived number of diseased coronary arteries were also compared between the two coronary distributions (actual and assumed). The assumed coronary distribution corresponded to the actual coronary anatomy in all but one segment (3). The majority of patients (80%) had 14 or more concordant segments. Sensitivities and specificities of stress SPET for detection of CAD in the coronary territories were similar, with the exception of the RCA territory, for which specificity for detection of CAD was better for the angiographically derived coronary artery distribution than for the model. There was 95% agreement between assumed and angiographically derived coronary distributions in classification to single- versus multi-vessel CAD. Reassignment of a single segment (segment 3) from the LCX to the LAD

Recommendations for the Use of Automated Gray Matter Segmentation Tools: Evidence from Huntington's Disease.

Science.gov (United States)

Johnson, Eileanoir B; Gregory, Sarah; Johnson, Hans J; Durr, Alexandra; Leavitt, Blair R; Roos, Raymund A; Rees, Geraint; Tabrizi, Sarah J; Scahill, Rachael I

2017-01-01

The selection of an appropriate segmentation tool is a challenge facing any researcher aiming to measure gray matter (GM) volume. Many tools have been compared, yet there is currently no method that can be recommended above all others; in particular, there is a lack of validation in disease cohorts. This work utilizes a clinical dataset to conduct an extensive comparison of segmentation tools. Our results confirm that all tools have advantages and disadvantages, and we present a series of considerations that may be of use when selecting a GM segmentation method, rather than a ranking of these tools. Seven segmentation tools were compared using 3 T MRI data from 20 controls, 40 premanifest Huntington's disease (HD), and 40 early HD participants. Segmented volumes underwent detailed visual quality control. Reliability and repeatability of total, cortical, and lobular GM were investigated in repeated baseline scans. The relationship between each tool was also examined. Longitudinal within-group change over 3 years was assessed via generalized least squares regression to determine sensitivity of each tool to disease effects. Visual quality control and raw volumes highlighted large variability between tools, especially in occipital and temporal regions. Most tools showed reliable performance and the volumes were generally correlated. Results for longitudinal within-group change varied between tools, especially within lobular regions. These differences highlight the need for careful selection of segmentation methods in clinical neuroimaging studies. This guide acts as a primer aimed at the novice or non-technical imaging scientist providing recommendations for the selection of cohort-appropriate GM segmentation software.

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

Elephant: Sequence Labeling for Word and Sentence Segmentation

NARCIS (Netherlands)

Evang, Kilian; Basile, Valerio; Chrupala, Grzegorz; Bos, Johan

2013-01-01

Tokenization is widely regarded as a solved problem due to the high accuracy that rule-based tokenizers achieve. But rule-based tokenizers are hard to maintain and their rules language specific. We show that high-accuracy word and sentence segmentation can be achieved by using supervised sequence

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.

3D knee segmentation based on three MRI sequences from different planes.

Science.gov (United States)

Zhou, L; Chav, R; Cresson, T; Chartrand, G; de Guise, J

2016-08-01

In clinical practice, knee MRI sequences with 3.5~5 mm slice distance in sagittal, coronal, and axial planes are often requested for the knee examination since its acquisition is faster than high-resolution MRI sequence in a single plane, thereby reducing the probability of motion artifact. In order to take advantage of the three sequences from different planes, a 3D segmentation method based on the combination of three knee models obtained from the three sequences is proposed in this paper. In the method, the sub-segmentation is respectively performed with sagittal, coronal, and axial MRI sequence in the image coordinate system. With each sequence, an initial knee model is hierarchically deformed, and then the three deformed models are mapped to reference coordinate system defined by the DICOM standard and combined to obtain a patient-specific model. The experimental results verified that the three sub-segmentation results can complement each other, and their integration can compensate for the insufficiency of boundary information caused by 3.5~5 mm gap between consecutive slices. Therefore, the obtained patient-specific model is substantially more accurate than each sub-segmentation results.

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

3D segmentation of liver, kidneys and spleen from CT images

International Nuclear Information System (INIS)

Bekes, G.; Fidrich, M.; Nyul, L.G.; Mate, E.; Kuba, A.

2007-01-01

The clinicians often need to segment the abdominal organs for radiotherapy planning. Manual segmentation of these organs is very time-consuming, therefore automated methods are desired. We developed a semi-automatic segmentation method to outline liver, spleen and kidneys. It works on CT images without contrast intake that are acquired with a routine clinical protocol. From an initial surface around a user defined seed point, the segmentation of the organ is obtained by an active surface algorithm. Pre- and post-processing steps are used to adapt the general method for specific organs. The evaluation results show that the accuracy of our method is about 90%, which can be further improved with little manual editing, and that the precision is slightly higher than that of manual contouring. Our method is accurate, precise and fast enough to use in the clinical practice. (orig.)

Is STAPLE algorithm confident to assess segmentation methods in PET imaging?

International Nuclear Information System (INIS)

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

2015-01-01

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

Is STAPLE algorithm confident to assess segmentation methods in PET imaging?

Science.gov (United States)

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

2015-12-01

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

Final hazard classification and auditable safety analysis for the N basin segment

International Nuclear Information System (INIS)

Kloster, G.; Smith, R.I.; Larson, A.R.; Duncan, G.M.

1996-12-01

The purpose of this report is to provide the following: To serve as the auditable safety analysis (ASA) for the N Basin Segment, including both the quiescent state and planned intrusive activities. The ASA is developed through the realistic evaluation of potential hazards that envelope the threat to personnel. The ASA also includes the specification of the programmatic, baseline, and activity- specific controls that are necessary for the protection of workers. To determine and document the final hazard classification (FHC) for the N Basin Segment. The FHC is developed through the use of bounding accident analyses that envelope the potential exposures to personnel. The FHC also includes the specification of the special controls that are necessary to remain within the envelope of those accident analyses

Automatic segmentation of mandible in panoramic x-ray.

Science.gov (United States)

Abdi, Amir Hossein; Kasaei, Shohreh; Mehdizadeh, Mojdeh

2015-10-01

As the panoramic x-ray is the most common extraoral radiography in dentistry, segmentation of its anatomical structures facilitates diagnosis and registration of dental records. This study presents a fast and accurate method for automatic segmentation of mandible in panoramic x-rays. In the proposed four-step algorithm, a superior border is extracted through horizontal integral projections. A modified Canny edge detector accompanied by morphological operators extracts the inferior border of the mandible body. The exterior borders of ramuses are extracted through a contour tracing method based on the average model of mandible. The best-matched template is fetched from the atlas of mandibles to complete the contour of left and right processes. The algorithm was tested on a set of 95 panoramic x-rays. Evaluating the results against manual segmentations of three expert dentists showed that the method is robust. It achieved an average performance of [Formula: see text] in Dice similarity, specificity, and sensitivity.

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.

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...

Unsupervised motion-based object segmentation refined by color

Science.gov (United States)

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

2003-06-01

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

Depression in focal, segmental and generalized dystonia.

Science.gov (United States)

Lewis, L; Butler, A; Jahanshahi, M

2008-11-01

Dystonia causes body disfigurement in the majority of those affected. Our aim was to test the hypothesis that low self-esteem resulting from the sense of disfigurement is an important component of self-reported depression in focal, segmental and generalized dystonia. Questionnaires to assess self-reported depression, self-esteem, body concept, disfigurement, disability and quality of life were completed by 329 community based dystonia patients. Moderate to severe depression was reported by 30 %. Self-reported depression had a strong somatic component, but patients also showed a specific concern with self-image. Extent of dystonia, body parts affected and marital status influenced self-reported depression in dystonia. Self esteem, body concept, disfigurement and quality of life emerged as factors which accounted for the variance of self-reported depression in dystonia. These results suggest that in dystonia, disfigurement, negative body concept, low self-esteem, and the impact of the disease on quality of life make important contributions to depression. However, longitudinal followup is required to firmly establish the direction of causality between depression and these psychosocial variables in dystonia.

Automated epidermis segmentation in histopathological images of human skin stained with hematoxylin and eosin

Science.gov (United States)

Kłeczek, Paweł; Dyduch, Grzegorz; Jaworek-Korjakowska, Joanna; Tadeusiewicz, Ryszard

2017-03-01

Background: Epidermis area is an important observation area for the diagnosis of inflammatory skin diseases and skin cancers. Therefore, in order to develop a computer-aided diagnosis system, segmentation of the epidermis area is usually an essential, initial step. This study presents an automated and robust method for epidermis segmentation in whole slide histopathological images of human skin, stained with hematoxylin and eosin. Methods: The proposed method performs epidermis segmentation based on the information about shape and distribution of transparent regions in a slide image and information about distribution and concentration of hematoxylin and eosin stains. It utilizes domain-specific knowledge of morphometric and biochemical properties of skin tissue elements to segment the relevant histopathological structures in human skin. Results: Experimental results on 88 skin histopathological images from three different sources show that the proposed method segments the epidermis with a mean sensitivity of 87 %, a mean specificity of 95% and a mean precision of 57%. It is robust to inter- and intra-image variations in both staining and illumination, and makes no assumptions about the type of skin disorder. The proposed method provides a superior performance compared to the existing techniques.

A Modelling Framework for estimating Road Segment Based On-Board Vehicle Emissions

International Nuclear Information System (INIS)

Lin-Jun, Yu; Ya-Lan, Liu; Yu-Huan, Ren; Zhong-Ren, Peng; Meng, Liu Meng

2014-01-01

Traditional traffic emission inventory models aim to provide overall emissions at regional level which cannot meet planners' demand for detailed and accurate traffic emissions information at the road segment level. Therefore, a road segment-based emission model for estimating light duty vehicle emissions is proposed, where floating car technology is used to collect information of traffic condition of roads. The employed analysis framework consists of three major modules: the Average Speed and the Average Acceleration Module (ASAAM), the Traffic Flow Estimation Module (TFEM) and the Traffic Emission Module (TEM). The ASAAM is used to obtain the average speed and the average acceleration of the fleet on each road segment using FCD. The TFEM is designed to estimate the traffic flow of each road segment in a given period, based on the speed-flow relationship and traffic flow spatial distribution. Finally, the TEM estimates emissions from each road segment, based on the results of previous two modules. Hourly on-road light-duty vehicle emissions for each road segment in Shenzhen's traffic network are obtained using this analysis framework. The temporal-spatial distribution patterns of the pollutant emissions of road segments are also summarized. The results show high emission road segments cluster in several important regions in Shenzhen. Also, road segments emit more emissions during rush hours than other periods. The presented case study demonstrates that the proposed approach is feasible and easy-to-use to help planners make informed decisions by providing detailed road segment-based emission information

3D TEM reconstruction and segmentation process of laminar bio-nanocomposites

International Nuclear Information System (INIS)

Iturrondobeitia, M.; Okariz, A.; Fernandez-Martinez, R.; Jimbert, P.; Guraya, T.; Ibarretxe, J.

2015-01-01

The microstructure of laminar bio-nanocomposites (Poly (lactic acid)(PLA)/clay) depends on the amount of clay platelet opening after integration with the polymer matrix and determines the final properties of the material. Transmission electron microscopy (TEM) technique is the only one that can provide a direct observation of the layer dispersion and the degree of exfoliation. However, the orientation of the clay platelets, which affects the final properties, is practically immeasurable from a single 2D TEM image. This issue can be overcome using transmission electron tomography (ET), a technique that allows the complete 3D characterization of the structure, including the measurement of the orientation of clay platelets, their morphology and their 3D distribution. ET involves a 3D reconstruction of the study volume and a subsequent segmentation of the study object. Currently, accurate segmentation is performed manually, which is inefficient and tedious. The aim of this work is to propose an objective/automated segmentation methodology process of a 3D TEM tomography reconstruction. In this method the segmentation threshold is optimized by minimizing the variation of the dimensions of the segmented objects and matching the segmented V clay (%) and the actual one. The method is first validated using a fictitious set of objects, and then applied on a nanocomposite

Photoreceptor inner segment ellipsoid band integrity on spectral domain optical coherence tomography

Directory of Open Access Journals (Sweden)

Saxena S

2014-12-01

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

Korean WA-DGNSS User Segment Software Design

Directory of Open Access Journals (Sweden)

Sayed Chhattan Shah

2013-03-01

Full Text Available Korean WA-DGNSS is a large scale research project funded by Ministry of Land, Transport and Maritime Affairs Korea. It aims to augment the Global Navigation Satellite System by broadcasting additional signals from geostationary satellites and providing differential correction messages and integrity data for the GNSS satellites. The project is being carried out by a consortium of universities and research institutes. The research team at Electronics and Telecommunications Research Institute is involved in design and development of data processing softwares for wide area reference station and user segment. This paper focuses on user segment software design. Korean WA-DGNSS user segment software is designed to perform several functions such as calculation of pseudorange, ionosphere and troposphere delays, application of fast and slow correction messages, and data verification. It is based on a layered architecture that provides a model to develop flexible and reusable software and is divided into several independent, interchangeable and reusable components to reduce complexity and maintenance cost. The current version is designed to collect and process GPS and WA-DGNSS data however it is flexible to accommodate future GNSS systems such as GLONASS and Galileo.

Predictive market segmentation model: An application of logistic regression model and CHAID procedure

Directory of Open Access Journals (Sweden)

Soldić-Aleksić Jasna

2009-01-01

Full Text Available Market segmentation presents one of the key concepts of the modern marketing. The main goal of market segmentation is focused on creating groups (segments of customers that have similar characteristics, needs, wishes and/or similar behavior regarding the purchase of concrete product/service. Companies can create specific marketing plan for each of these segments and therefore gain short or long term competitive advantage on the market. Depending on the concrete marketing goal, different segmentation schemes and techniques may be applied. This paper presents a predictive market segmentation model based on the application of logistic regression model and CHAID analysis. The logistic regression model was used for the purpose of variables selection (from the initial pool of eleven variables which are statistically significant for explaining the dependent variable. Selected variables were afterwards included in the CHAID procedure that generated the predictive market segmentation model. The model results are presented on the concrete empirical example in the following form: summary model results, CHAID tree, Gain chart, Index chart, risk and classification tables.

Benchmark for license plate character segmentation

Science.gov (United States)

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

2016-09-01

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

Arizona TeleMedicine Network: System Procurement Specifications.

Science.gov (United States)

Atlantic Research Corp., Alexandria, VA.

Providing general specifications and system descriptions for segments within the Arizona TeleMedicine Project (a telecommunication system designed to deliver health services to rurally isolated American Indians in Arizona), this document, when used with the appropriate route segment document, will completely describe the project's required…

PREPAID TELECOM CUSTOMERS SEGMENTATION USING THE K-MEAN ALGORITHM

Directory of Open Access Journals (Sweden)

Marar Liviu Ioan

2012-07-01

Full Text Available The scope of relationship marketing is to retain customers and win their loyalty. This can be achieved if the companies’ products and services are developed and sold considering customers’ demands. Fulfilling customers’ demands, taken as the starting point of relationship marketing, can be obtained by acknowledging that the customers’ needs and wishes are heterogeneous. The segmentation of the customers’ base allows operators to overcome this because it illustrates the whole heterogeneous market as the sum of smaller homogeneous markets. The concept of segmentation relies on the high probability of persons grouped into segments based on common demands and behaviours to have a similar response to marketing strategies. This article focuses on the segmentation of a telecom customer base according to specific and noticeable criteria of a certain service. Although the segmentation concept is widely approached in professional literature, articles on the segmentation of a telecom customer base are very scarce, due to the strategic nature of this information. Market segmentation is carried out based on how customers spent their money on credit recharging, on making calls, on sending SMS and on Internet navigation. The method used for customer segmentation is the K-mean cluster analysis. To assess the internal cohesion of the clusters we employed the average sum of squares error indicator, and to determine the differences among the clusters we used the ANOVA and the post-hoc Tukey tests. The analyses revealed seven customer segments with different features and behaviours. The results enable the telecom company to conceive marketing strategies and planning which lead to better understanding of its customers’ needs and ultimately to a more efficient relationship with the subscribers and enhanced customer satisfaction. At the same time, the results enable the description and characterization of expenditure patterns

Skip segment Hirschsprung's disease: a systematic review.

LENUS (Irish Health Repository)

O'Donnell, Anne-Marie

2012-02-01

PURPOSE: Hirschsprung\\'s disease is characterised by the congenital absence of ganglion cells beginning in the distal rectum and extending proximally for varying distances. \\'Zonal aganglionosis\\' is a phenomenon involving a zone of aganglionosis occurring within normally innervated intestine. \\'Skip segment\\' Hirschsprung\\'s disease (SSHD) involves a \\'skip area\\' of normally ganglionated intestine, surrounded proximally and distally by aganglionosis. While Hirschsprung\\'s disease is believed to be the result of incomplete craniocaudal migration of neural crest-derived cells, the occurrence of SSHD has no clear embryological explanation. The aim of this study was to perform a systematic review of SSHD, reported in the literature between 1954 and 2009, in order to determine the clinical characteristics of this rare entity and its significance. METHODS: The first reported case of SSHD was published in 1954. A systematic review of SSHD cases in the literature, from 1954 to 2009, was carried out using the electronic database \\'Pubmed\\'. Detailed information was recorded regarding the age, gender, presenting symptoms and location of the skip segment in each patient. RESULTS: 24 cases of SSHD have been reported in the literature to date. 18\\/24 (75%) of these cases were males and 6\\/24 (25%) were females. Of these, 22\\/24 (92%) were cases of total colonic aganglionosis (TCA), and 2\\/24 (8%) were rectosigmoid Hirschsprung\\'s disease. Of the 22 TCA cases, 9 (41%) had a skip segment in the transverse colon, 6 (27%) in the ascending colon, 2 (9%) in the caecum and 5 (23%) had multiple skip segments. In both rectosigmoid Hirschsprung\\'s disease cases, the skip segment was in the sigmoid colon. Overall, the length of the skip segment was variable, with the entire transverse colon ganglionated in some cases. CONCLUSION: SSHD occurs predominantly in patients with TCA. The existence of a skip area of normally innervated colon in TCA may influence surgical

Rapid diagnosis of aneuploidy using segmental duplication quantitative fluorescent PCR.

Directory of Open Access Journals (Sweden)

Xiangdong Kong

Full Text Available The aim of this study was use a simple and rapid procedure, called segmental duplication quantitative fluorescent polymerase chain reaction (SD-QF-PCR, for the prenatal diagnosis of fetal chromosomal aneuploidies. This method is based on the co-amplification of segmental duplications located on two different chromosomes using a single pair of fluorescent primers. The PCR products of different sizes were subsequently analyzed through capillary electrophoresis, and the aneuploidies were determined based on the relative dosage between the two chromosomes. Each primer set, containing five pairs of primers, was designed to simultaneously detect aneuploidies located on chromosomes 21, 18, 13, X and Y in a single reaction. We applied these two primer sets to DNA samples isolated from individuals with trisomy 21 (n = 36; trisomy 18 (n = 6; trisomy 13 (n = 4; 45, X (n = 5; 47, XXX (n = 3; 48, XXYY (n = 2; and unaffected controls (n = 40. We evaluated the performance of this method using the karyotyping results. A correct and unambiguous diagnosis with 100% sensitivity and 100% specificity, was achieved for clinical samples examined. Thus, the present study demonstrates that SD-QF-PCR is a robust, rapid and sensitive method for the diagnosis of common aneuploidies, and these analyses can be performed in less than 4 hours for a single sample, providing a competitive alternative for routine use.

Topology and robustness in the Drosophila segment polarity network.

Directory of Open Access Journals (Sweden)

Nicholas T Ingolia

2004-06-01

Full Text Available A complex hierarchy of genetic interactions converts a single-celled Drosophila melanogaster egg into a multicellular embryo with 14 segments. Previously, von Dassow et al. reported that a mathematical model of the genetic interactions that defined the polarity of segments (the segment polarity network was robust (von Dassow et al. 2000. As quantitative information about the system was unavailable, parameters were sampled randomly. A surprisingly large fraction of these parameter sets allowed the model to maintain and elaborate on the segment polarity pattern. This robustness is due to the positive feedback of gene products on their own expression, which induces individual cells in a model segment to adopt different stable expression states (bistability corresponding to different cell types in the segment polarity pattern. A positive feedback loop will only yield multiple stable states when the parameters that describe it satisfy a particular inequality. By testing which random parameter sets satisfy these inequalities, I show that bistability is necessary to form the segment polarity pattern and serves as a strong predictor of which parameter sets will succeed in forming the pattern. Although the original model was robust to parameter variation, it could not reproduce the observed effects of cell division on the pattern of gene expression. I present a modified version that incorporates recent experimental evidence and does successfully mimic the consequences of cell division. The behavior of this modified model can also be understood in terms of bistability in positive feedback of gene expression. I discuss how this topological property of networks provides robust pattern formation and how large changes in parameters can change the specific pattern produced by a network.

Automated seeding-based nuclei segmentation in nonlinear optical microscopy.

Science.gov (United States)

Medyukhina, Anna; Meyer, Tobias; Heuke, Sandro; Vogler, Nadine; Dietzek, Benjamin; Popp, Jürgen

2013-10-01

Nonlinear optical (NLO) microscopy based, e.g., on coherent anti-Stokes Raman scattering (CARS) or two-photon-excited fluorescence (TPEF) is a fast label-free imaging technique, with a great potential for biomedical applications. However, NLO microscopy as a diagnostic tool is still in its infancy; there is a lack of robust and durable nuclei segmentation methods capable of accurate image processing in cases of variable image contrast, nuclear density, and type of investigated tissue. Nonetheless, such algorithms specifically adapted to NLO microscopy present one prerequisite for the technology to be routinely used, e.g., in pathology or intraoperatively for surgical guidance. In this paper, we compare the applicability of different seeding and boundary detection methods to NLO microscopic images in order to develop an optimal seeding-based approach capable of accurate segmentation of both TPEF and CARS images. Among different methods, the Laplacian of Gaussian filter showed the best accuracy for the seeding of the image, while a modified seeded watershed segmentation was the most accurate in the task of boundary detection. The resulting combination of these methods followed by the verification of the detected nuclei performs high average sensitivity and specificity when applied to various types of NLO microscopy images.

A fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy.

Science.gov (United States)

Guo, Lu; Wang, Ping; Sun, Ranran; Yang, Chengwen; Zhang, Ning; Guo, Yu; Feng, Yuanming

2018-02-19

The diffusion and perfusion magnetic resonance (MR) images can provide functional information about tumour and enable more sensitive detection of the tumour extent. We aimed to develop a fuzzy feature fusion method for auto-segmentation of gliomas in radiotherapy planning using multi-parametric functional MR images including apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV). For each functional modality, one histogram-based fuzzy model was created to transform image volume into a fuzzy feature space. Based on the fuzzy fusion result of the three fuzzy feature spaces, regions with high possibility belonging to tumour were generated automatically. The auto-segmentations of tumour in structural MR images were added in final auto-segmented gross tumour volume (GTV). For evaluation, one radiation oncologist delineated GTVs for nine patients with all modalities. Comparisons between manually delineated and auto-segmented GTVs showed that, the mean volume difference was 8.69% (±5.62%); the mean Dice's similarity coefficient (DSC) was 0.88 (±0.02); the mean sensitivity and specificity of auto-segmentation was 0.87 (±0.04) and 0.98 (±0.01) respectively. High accuracy and efficiency can be achieved with the new method, which shows potential of utilizing functional multi-parametric MR images for target definition in precision radiation treatment planning for patients with gliomas.

Research on segmentation based on multi-atlas in brain MR image

Science.gov (United States)

Qian, Yuejing

2018-03-01

Accurate segmentation of specific tissues in brain MR image can be effectively achieved with the multi-atlas-based segmentation method, and the accuracy mainly depends on the image registration accuracy and fusion scheme. This paper proposes an automatic segmentation method based on the multi-atlas for brain MR image. Firstly, to improve the registration accuracy in the area to be segmented, we employ a target-oriented image registration method for the refinement. Then In the label fusion, we proposed a new algorithm to detect the abnormal sparse patch and simultaneously abandon the corresponding abnormal sparse coefficients, this method is made based on the remaining sparse coefficients combined with the multipoint label estimator strategy. The performance of the proposed method was compared with those of the nonlocal patch-based label fusion method (Nonlocal-PBM), the sparse patch-based label fusion method (Sparse-PBM) and majority voting method (MV). Based on our experimental results, the proposed method is efficient in the brain MR images segmentation compared with MV, Nonlocal-PBM, and Sparse-PBM methods.

Neonatal Brain Tissue Classification with Morphological Adaptation and Unified Segmentation

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Richard eBeare

2016-03-01

Full Text Available Measuring the distribution of brain tissue types (tissue classification in neonates is necessary for studying typical and atypical brain development, such as that associated with preterm birth, and may provide biomarkers for neurodevelopmental outcomes. Compared with magnetic resonance images of adults, neonatal images present specific challenges that require the development of specialized, population-specific methods. This paper introduces MANTiS (Morphologically Adaptive Neonatal Tissue Segmentation, which extends the unified segmentation approach to tissue classification implemented in Statistical Parametric Mapping (SPM software to neonates. MANTiS utilizes a combination of unified segmentation, template adaptation via morphological segmentation tools and topological filtering, to segment the neonatal brain into eight tissue classes: cortical gray matter, white matter, deep nuclear gray matter, cerebellum, brainstem, cerebrospinal fluid (CSF, hippocampus and amygdala. We evaluated the performance of MANTiS using two independent datasets. The first dataset, provided by the NeoBrainS12 challenge, consisted of coronal T2-weighted images of preterm infants (born ≤30 weeks’ gestation acquired at 30 weeks’ corrected gestational age (n= 5, coronal T2-weighted images of preterm infants acquired at 40 weeks’ corrected gestational age (n= 5 and axial T2-weighted images of preterm infants acquired at 40 weeks’ corrected gestational age (n= 5. The second dataset, provided by the Washington University NeuroDevelopmental Research (WUNDeR group, consisted of T2-weighted images of preterm infants (born <30 weeks’ gestation acquired shortly after birth (n= 12, preterm infants acquired at term-equivalent age (n= 12, and healthy term-born infants (born ≥38 weeks’ gestation acquired within the first nine days of life (n= 12. For the NeoBrainS12 dataset, mean Dice scores comparing MANTiS with manual segmentations were all above 0.7, except for

Audio segmentation of broadcast news in the Albayzin-2010 evaluation: overview, results, and discussion

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Butko Taras

2011-01-01

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

Automated image alignment and segmentation to follow progression of geographic atrophy in age-related macular degeneration.

Science.gov (United States)

Ramsey, David J; Sunness, Janet S; Malviya, Poorva; Applegate, Carol; Hager, Gregory D; Handa, James T

2014-07-01

To develop a computer-based image segmentation method for standardizing the quantification of geographic atrophy (GA). The authors present an automated image segmentation method based on the fuzzy c-means clustering algorithm for the detection of GA lesions. The method is evaluated by comparing computerized segmentation against outlines of GA drawn by an expert grader for a longitudinal series of fundus autofluorescence images with paired 30° color fundus photographs for 10 patients. The automated segmentation method showed excellent agreement with an expert grader for fundus autofluorescence images, achieving a performance level of 94 ± 5% sensitivity and 98 ± 2% specificity on a per-pixel basis for the detection of GA area, but performed less well on color fundus photographs with a sensitivity of 47 ± 26% and specificity of 98 ± 2%. The segmentation algorithm identified 75 ± 16% of the GA border correctly in fundus autofluorescence images compared with just 42 ± 25% for color fundus photographs. The results of this study demonstrate a promising computerized segmentation method that may enhance the reproducibility of GA measurement and provide an objective strategy to assist an expert in the grading of images.

An Efficient Parallel Multi-Scale Segmentation Method for Remote Sensing Imagery

Directory of Open Access Journals (Sweden)

Haiyan Gu

2018-04-01

Full Text Available Remote sensing (RS image segmentation is an essential step in geographic object-based image analysis (GEOBIA to ultimately derive “meaningful objects”. While many segmentation methods exist, most of them are not efficient for large data sets. Thus, the goal of this research is to develop an efficient parallel multi-scale segmentation method for RS imagery by combining graph theory and the fractal net evolution approach (FNEA. Specifically, a minimum spanning tree (MST algorithm in graph theory is proposed to be combined with a minimum heterogeneity rule (MHR algorithm that is used in FNEA. The MST algorithm is used for the initial segmentation while the MHR algorithm is used for object merging. An efficient implementation of the segmentation strategy is presented using data partition and the “reverse searching-forward processing” chain based on message passing interface (MPI parallel technology. Segmentation results of the proposed method using images from multiple sensors (airborne, SPECIM AISA EAGLE II, WorldView-2, RADARSAT-2 and different selected landscapes (residential/industrial, residential/agriculture covering four test sites indicated its efficiency in accuracy and speed. We conclude that the proposed method is applicable and efficient for the segmentation of a variety of RS imagery (airborne optical, satellite optical, SAR, high-spectral, while the accuracy is comparable with that of the FNEA method.

Segmented arch or continuous arch technique? A rational approach

Directory of Open Access Journals (Sweden)

Sergei Godeiro Fernandes Rabelo Caldas

2014-04-01

Full Text Available This study aims at revising the biomechanical principles of the segmented archwire technique as well as describing the clinical conditions in which the rational use of scientific biomechanics is essential to optimize orthodontic treatment and reduce the side effects produced by the straight wire technique.

Metabolically active tumour volume segmentation from dynamic [(18)F]FLT PET studies in non-small cell lung cancer.

Science.gov (United States)

Hoyng, Lieke L; Frings, Virginie; Hoekstra, Otto S; Kenny, Laura M; Aboagye, Eric O; Boellaard, Ronald

2015-01-01

Positron emission tomography (PET) with (18)F-3'-deoxy-3'-fluorothymidine ([(18)F]FLT) can be used to assess tumour proliferation. A kinetic-filtering (KF) classification algorithm has been suggested for segmentation of tumours in dynamic [(18)F]FLT PET data. The aim of the present study was to evaluate KF segmentation and its test-retest performance in [(18)F]FLT PET in non-small cell lung cancer (NSCLC) patients. Nine NSCLC patients underwent two 60-min dynamic [(18)F]FLT PET scans within 7 days prior to treatment. Dynamic scans were reconstructed with filtered back projection (FBP) as well as with ordered subsets expectation maximisation (OSEM). Twenty-eight lesions were identified by an experienced physician. Segmentation was performed using KF applied to the dynamic data set and a source-to-background corrected 50% threshold (A50%) was applied to the sum image of the last three frames (45- to 60-min p.i.). Furthermore, several adaptations of KF were tested. Both for KF and A50% test-retest (TRT) variability of metabolically active tumour volume and standard uptake value (SUV) were evaluated. KF performed better on OSEM- than on FBP-reconstructed PET images. The original KF implementation segmented 15 out of 28 lesions, whereas A50% segmented each lesion. Adapted KF versions, however, were able to segment 26 out of 28 lesions. In the best performing adapted versions, metabolically active tumour volume and SUV TRT variability was similar to those of A50%. KF misclassified certain tumour areas as vertebrae or liver tissue, which was shown to be related to heterogeneous [(18)F]FLT uptake areas within the tumour. For [(18)F]FLT PET studies in NSCLC patients, KF and A50% show comparable tumour volume segmentation performance. The KF method needs, however, a site-specific optimisation. The A50% is therefore a good alternative for tumour segmentation in NSCLC [(18)F]FLT PET studies in multicentre studies. Yet, it was observed that KF has the potential to subsegment

Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming

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Chiu, Stephanie J.; Toth, Cynthia A.; Bowes Rickman, Catherine; Izatt, Joseph A.; Farsiu, Sina

2012-01-01

This paper presents a generalized framework for segmenting closed-contour anatomical and pathological features using graph theory and dynamic programming (GTDP). More specifically, the GTDP method previously developed for quantifying retinal and corneal layer thicknesses is extended to segment objects such as cells and cysts. The presented technique relies on a transform that maps closed-contour features in the Cartesian domain into lines in the quasi-polar domain. The features of interest are then segmented as layers via GTDP. Application of this method to segment closed-contour features in several ophthalmic image types is shown. Quantitative validation experiments for retinal pigmented epithelium cell segmentation in confocal fluorescence microscopy images attests to the accuracy of the presented technique. PMID:22567602

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.

Excluded segmental duct bile leakage: the case for bilio-enteric anastomosis.

Science.gov (United States)

Patrono, Damiano; Tandoi, Francesco; Romagnoli, Renato; Salizzoni, Mauro

2014-06-01

Excluded segmental duct bile leak is the rarest type of post-hepatectomy bile leak and presents unique diagnostic and management features. Classical management strategies invariably entail a significant loss of functioning hepatic parenchyma. The aim of this study is to report a new liver-sparing technique to handle excluded segmental duct bile leakage. Two cases of excluded segmental duct bile leak occurring after major hepatic resection were managed by a Roux-en-Y hepatico-jejunostomy on the excluded segmental duct, avoiding the sacrifice of the liver parenchyma origin of the fistula. In both cases, classical management strategies would have led to the functional loss of roughly 50 % of the liver remnant. Diagnostic and management implications are thoroughly discussed. Both cases had an uneventful postoperative course. The timing of repair was associated with a different outcome: the patient who underwent surgical repair in the acute phase developed no long-term complications, whereas the patient who underwent delayed repair developed a late stenosis requiring percutaneous dilatation. Roux-en-Y hepatico-jejunostomy on the excluded bile duct is a valuable technique in selected cases of excluded segmental duct bile leakage.

Fully automated segmentation of callus by micro-CT compared to biomechanics.

Science.gov (United States)

Bissinger, Oliver; Götz, Carolin; Wolff, Klaus-Dietrich; Hapfelmeier, Alexander; Prodinger, Peter Michael; Tischer, Thomas

2017-07-11

A high percentage of closed femur fractures have slight comminution. Using micro-CT (μCT), multiple fragment segmentation is much more difficult than segmentation of unfractured or osteotomied bone. Manual or semi-automated segmentation has been performed to date. However, such segmentation is extremely laborious, time-consuming and error-prone. Our aim was to therefore apply a fully automated segmentation algorithm to determine μCT parameters and examine their association with biomechanics. The femura of 64 rats taken after randomised inhibitory or neutral medication, in terms of the effect on fracture healing, and controls were closed fractured after a Kirschner wire was inserted. After 21 days, μCT and biomechanical parameters were determined by a fully automated method and correlated (Pearson's correlation). The fully automated segmentation algorithm automatically detected bone and simultaneously separated cortical bone from callus without requiring ROI selection for each single bony structure. We found an association of structural callus parameters obtained by μCT to the biomechanical properties. However, results were only explicable by additionally considering the callus location. A large number of slightly comminuted fractures in combination with therapies that influence the callus qualitatively and/or quantitatively considerably affects the association between μCT and biomechanics. In the future, contrast-enhanced μCT imaging of the callus cartilage might provide more information to improve the non-destructive and non-invasive prediction of callus mechanical properties. As studies evaluating such important drugs increase, fully automated segmentation appears to be clinically important.

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...

Lumbar segmental instability: a criterion-related validity study of manual therapy assessment

Directory of Open Access Journals (Sweden)

Chapple Cathy

2005-11-01

Full Text Available Abstract Background Musculoskeletal physiotherapists routinely assess lumbar segmental motion during the clinical examination of a patient with low back pain. The validity of manual assessment of segmental motion has not, however, been adequately investigated. Methods In this prospective, multi-centre, pragmatic, diagnostic validity study, 138 consecutive patients with recurrent or chronic low back pain (R/CLBP were recruited. Physiotherapists with post-graduate training in manual therapy performed passive accessory intervertebral motion tests (PAIVMs and passive physiological intervertebral motion tests (PPIVMs. Consenting patients were referred for flexion-extension radiographs. Sagittal angular rotation and sagittal translation of each lumbar spinal motion segment was measured from these radiographs, and compared to a reference range derived from a study of 30 asymptomatic volunteers. Motion beyond two standard deviations from the reference mean was considered diagnostic of rotational lumbar segmental instability (LSI and translational LSI. Accuracy and validity of the clinical assessments were expressed using sensitivity, specificity, and likelihood ratio statistics with 95% confidence intervals (CI. Results Only translation LSI was found to be significantly associated with R/CLBP (p Conclusion This study provides the first evidence reporting the concurrent validity of manual tests for the detection of abnormal sagittal planar motion. PAIVMs and PPIVMs are highly specific, but not sensitive, for the detection of translation LSI. Likelihood ratios resulting from positive test results were only moderate. This research indicates that manual clinical examination procedures have moderate validity for detecting segmental motion abnormality.

Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions.

Science.gov (United States)

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

2017-08-01

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

Recommendations for the Use of Automated Gray Matter Segmentation Tools: Evidence from Huntington’s Disease

Science.gov (United States)

Johnson, Eileanoir B.; Gregory, Sarah; Johnson, Hans J.; Durr, Alexandra; Leavitt, Blair R.; Roos, Raymund A.; Rees, Geraint; Tabrizi, Sarah J.; Scahill, Rachael I.

2017-01-01

The selection of an appropriate segmentation tool is a challenge facing any researcher aiming to measure gray matter (GM) volume. Many tools have been compared, yet there is currently no method that can be recommended above all others; in particular, there is a lack of validation in disease cohorts. This work utilizes a clinical dataset to conduct an extensive comparison of segmentation tools. Our results confirm that all tools have advantages and disadvantages, and we present a series of considerations that may be of use when selecting a GM segmentation method, rather than a ranking of these tools. Seven segmentation tools were compared using 3 T MRI data from 20 controls, 40 premanifest Huntington’s disease (HD), and 40 early HD participants. Segmented volumes underwent detailed visual quality control. Reliability and repeatability of total, cortical, and lobular GM were investigated in repeated baseline scans. The relationship between each tool was also examined. Longitudinal within-group change over 3 years was assessed via generalized least squares regression to determine sensitivity of each tool to disease effects. Visual quality control and raw volumes highlighted large variability between tools, especially in occipital and temporal regions. Most tools showed reliable performance and the volumes were generally correlated. Results for longitudinal within-group change varied between tools, especially within lobular regions. These differences highlight the need for careful selection of segmentation methods in clinical neuroimaging studies. This guide acts as a primer aimed at the novice or non-technical imaging scientist providing recommendations for the selection of cohort-appropriate GM segmentation software. PMID:29066997

Recommendations for the Use of Automated Gray Matter Segmentation Tools: Evidence from Huntington’s Disease

Directory of Open Access Journals (Sweden)

Eileanoir B. Johnson

2017-10-01

Full Text Available The selection of an appropriate segmentation tool is a challenge facing any researcher aiming to measure gray matter (GM volume. Many tools have been compared, yet there is currently no method that can be recommended above all others; in particular, there is a lack of validation in disease cohorts. This work utilizes a clinical dataset to conduct an extensive comparison of segmentation tools. Our results confirm that all tools have advantages and disadvantages, and we present a series of considerations that may be of use when selecting a GM segmentation method, rather than a ranking of these tools. Seven segmentation tools were compared using 3 T MRI data from 20 controls, 40 premanifest Huntington’s disease (HD, and 40 early HD participants. Segmented volumes underwent detailed visual quality control. Reliability and repeatability of total, cortical, and lobular GM were investigated in repeated baseline scans. The relationship between each tool was also examined. Longitudinal within-group change over 3 years was assessed via generalized least squares regression to determine sensitivity of each tool to disease effects. Visual quality control and raw volumes highlighted large variability between tools, especially in occipital and temporal regions. Most tools showed reliable performance and the volumes were generally correlated. Results for longitudinal within-group change varied between tools, especially within lobular regions. These differences highlight the need for careful selection of segmentation methods in clinical neuroimaging studies. This guide acts as a primer aimed at the novice or non-technical imaging scientist providing recommendations for the selection of cohort-appropriate GM segmentation software.

Vasopressin-induced constriction of the isolated rat occipital artery is segment dependent.

Science.gov (United States)

Chelko, Stephen P; Schmiedt, Chad W; Lewis, Tristan H; Lewis, Stephen J; Robertson, Tom P

2013-01-01

Circulating factors delivered to the nodose ganglion (NG) by the occipital artery (OA) have been shown to affect vagal afferent activity, and thus the contractile state of the OA may influence blood flow to the NG. OA were isolated and bisected into proximal and distal segments relative to the external carotid artery. Bisection highlighted stark differences between maximal contractile responses and OA sensitivity. Specifically, maximum responses to vasopressin and the V1 receptor agonist were significantly higher in distal than proximal segments. Distal segments were significantly more sensitive to 5-hydroxytryptamine (5-HT) and the 5-HT2 receptor agonist than proximal segments. Angiotensin II (AT)2, V2 and 5-HT(1B/1D) receptor agonists did not elicit vascular responses. Additionally, AT1 receptor agonists elicited mild, yet not significantly different maximal responses between segments. The results of this study are consistent with contractile properties of rat OA being mediated via AT1, V1 and 5-HT2 receptors and dependent upon the OA segment. Furthermore, vasopressin-induced constriction of the OA, regardless of a bolus dose or a first and second concentration-response curve, retained this unique segmental difference. We hypothesize that these segmental differences may be important in the regulation of blood flow through the OA in health and disease. © 2013 S. Karger AG, Basel.

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.

Idiopathic focal segmental glomerulosclerosis: a favourable prognosis in untreated patients?

NARCIS (Netherlands)

Deegens, J.K.J.; Assmann, K.J.M.; Steenbergen, E.; Hilbrands, L.B.; Gerlag, P.G.G.; Jansen, J.L.; Wetzels, J.F.M.

2005-01-01

BACKGROUND: Patients with focal segmental glomerulosclerosis (FSGS) are considered to have a poor prognosis and spontaneous remissions are seldom reported. However, FSGS is not a single disease entity. Our aim was to describe the clinical course in initially untreated patients with recently

Interactive lung segmentation in abnormal human and animal chest CT scans

International Nuclear Information System (INIS)

Kockelkorn, Thessa T. J. P.; Viergever, Max A.; Schaefer-Prokop, Cornelia M.; Bozovic, Gracijela; Muñoz-Barrutia, Arrate; Rikxoort, Eva M. van; Brown, Matthew S.; Jong, Pim A. de; Ginneken, Bram van

2014-01-01

Purpose: Many medical image analysis systems require segmentation of the structures of interest as a first step. For scans with gross pathology, automatic segmentation methods may fail. The authors’ aim is to develop a versatile, fast, and reliable interactive system to segment anatomical structures. In this study, this system was used for segmenting lungs in challenging thoracic computed tomography (CT) scans. Methods: In volumetric thoracic CT scans, the chest is segmented and divided into 3D volumes of interest (VOIs), containing voxels with similar densities. These VOIs are automatically labeled as either lung tissue or nonlung tissue. The automatic labeling results can be corrected using an interactive or a supervised interactive approach. When using the supervised interactive system, the user is shown the classification results per slice, whereupon he/she can adjust incorrect labels. The system is retrained continuously, taking the corrections and approvals of the user into account. In this way, the system learns to make a better distinction between lung tissue and nonlung tissue. When using the interactive framework without supervised learning, the user corrects all incorrectly labeled VOIs manually. Both interactive segmentation tools were tested on 32 volumetric CT scans of pigs, mice and humans, containing pulmonary abnormalities. Results: On average, supervised interactive lung segmentation took under 9 min of user interaction. Algorithm computing time was 2 min on average, but can easily be reduced. On average, 2.0% of all VOIs in a scan had to be relabeled. Lung segmentation using the interactive segmentation method took on average 13 min and involved relabeling 3.0% of all VOIs on average. The resulting segmentations correspond well to manual delineations of eight axial slices per scan, with an average Dice similarity coefficient of 0.933. Conclusions: The authors have developed two fast and reliable methods for interactive lung segmentation in

Functional transient receptor potential vanilloid 1 and transient receptor potential vanilloid 4 channels along different segments of the renal vasculature

DEFF Research Database (Denmark)

Chen, L; Kaßmann, M; Sendeski, M

2015-01-01

with functional TRPV1 having a narrow, discrete distribution in the resistance vasculature and TRPV4 having more universal, widespread distribution along different vascular segments. We suggest that TRPV1/4 channels are potent therapeutic targets for site-specific vasodilation in the kidney.......AIM: Transient receptor potential vanilloid 1 (TRPV1) and vanilloid 4 (TRPV4) cation channels have been recently identified to promote endothelium-dependent relaxation of mouse mesenteric arteries. However, the role of TRPV1 and TRPV4 in the renal vasculature is largely unknown. We hypothesized...... that TRPV1/4 plays a role in endothelium-dependent vasodilation of renal blood vessels. METHODS: We studied the distribution of functional TRPV1/4 along different segments of the renal vasculature. Mesenteric arteries were studied as control vessels. RESULTS: The TRPV1 agonist capsaicin relaxed mouse...

A novel magnet based 3D printed marker wand as basis for repeated in-shoe multi segment foot analysis: a proof of concept.

Science.gov (United States)

Eerdekens, Maarten; Staes, Filip; Pilkington, Thomas; Deschamps, Kevin

2017-01-01

Application of in-shoe multi-segment foot kinematic analyses currently faces a number of challenges, including: (i) the difficulty to apply regular markers onto the skin, (ii) the necessity for an adequate shoe which fits various foot morphologies and (iii) the need for adequate repeatability throughout a repeated measure condition. The aim of this study therefore was to design novel magnet based 3D printed markers for repeated in-shoe measurements while using accordingly adapted modified shoes for a specific multi-segment foot model. Multi-segment foot kinematics of ten participants were recorded and kinematics of hindfoot, midfoot and forefoot were calculated. Dynamic trials were conducted to check for intra and inter-session repeatability when combining novel markers and modified shoes in a repeated measures design. Intraclass correlation coefficients were calculated to determine reliability. Both repeatability and reliability were proven to be good to excellent with maximum joint angle deviations of 1.11° for intra-session variability and 1.29° for same-day inter-session variability respectively and ICC values of >0.91. The novel markers can be reliably used in future research settings using in-shoe multi-segment foot kinematic analyses with multiple shod conditions.

Automated vessel segmentation using cross-correlation and pooled covariance matrix analysis.

Science.gov (United States)

Du, Jiang; Karimi, Afshin; Wu, Yijing; Korosec, Frank R; Grist, Thomas M; Mistretta, Charles A

2011-04-01

Time-resolved contrast-enhanced magnetic resonance angiography (CE-MRA) provides contrast dynamics in the vasculature and allows vessel segmentation based on temporal correlation analysis. Here we present an automated vessel segmentation algorithm including automated generation of regions of interest (ROIs), cross-correlation and pooled sample covariance matrix analysis. The dynamic images are divided into multiple equal-sized regions. In each region, ROIs for artery, vein and background are generated using an iterative thresholding algorithm based on the contrast arrival time map and contrast enhancement map. Region-specific multi-feature cross-correlation analysis and pooled covariance matrix analysis are performed to calculate the Mahalanobis distances (MDs), which are used to automatically separate arteries from veins. This segmentation algorithm is applied to a dual-phase dynamic imaging acquisition scheme where low-resolution time-resolved images are acquired during the dynamic phase followed by high-frequency data acquisition at the steady-state phase. The segmented low-resolution arterial and venous images are then combined with the high-frequency data in k-space and inverse Fourier transformed to form the final segmented arterial and venous images. Results from volunteer and patient studies demonstrate the advantages of this automated vessel segmentation and dual phase data acquisition technique. Copyright © 2011 Elsevier Inc. All rights reserved.

Intradomain phase transitions in flexible block copolymers with self-aligning segments

Science.gov (United States)

Burke, Christopher J.; Grason, Gregory M.

2018-05-01

We study a model of flexible block copolymers (BCPs) in which there is an enlthalpic preference for orientational order, or local alignment, among like-block segments. We describe a generalization of the self-consistent field theory of flexible BCPs to include inter-segment orientational interactions via a Landau-de Gennes free energy associated with a polar or nematic order parameter for segments of one component of a diblock copolymer. We study the equilibrium states of this model numerically, using a pseudo-spectral approach to solve for chain conformation statistics in the presence of a self-consistent torque generated by inter-segment alignment forces. Applying this theory to the structure of lamellar domains composed of symmetric diblocks possessing a single block of "self-aligning" polar segments, we show the emergence of spatially complex segment order parameters (segment director fields) within a given lamellar domain. Because BCP phase separation gives rise to spatially inhomogeneous orientation order of segments even in the absence of explicit intra-segment aligning forces, the director fields of BCPs, as well as thermodynamics of lamellar domain formation, exhibit a highly non-linear dependence on both the inter-block segregation (χN) and the enthalpy of alignment (ɛ). Specifically, we predict the stability of new phases of lamellar order in which distinct regions of alignment coexist within the single mesodomain and spontaneously break the symmetries of the lamella (or smectic) pattern of composition in the melt via in-plane tilt of the director in the centers of the like-composition domains. We further show that, in analogy to Freedericksz transition confined nematics, the elastic costs to reorient segments within the domain, as described by the Frank elasticity of the director, increase the threshold value ɛ needed to induce this intra-domain phase transition.

Vasopressin-induced constriction of the isolated rat occipital artery is segment-dependent

Science.gov (United States)

Chelko, Stephen P.; Schmiedt, Chad W.; Lewis, Tristan H.; Lewis, Stephen J.; Robertson, Tom P.

2014-01-01

Background Circulating factors delivered to the nodose ganglion (NG) by the occipital artery (OA) have shown to affect vagal afferent activity, and thus the contractile state of the OA may influence blood flow to the NG. Methods OA were isolated and bisected into proximal and distal segments, relative to the external carotid artery. Results Bisection, highlighted stark differences between maximal contractile responses and OA sensitivity. Specifically, maximum responses to vasopressin and the V1 receptor agonist, were significantly higher in distal than proximal segments. Distal segments were significantly more sensitive to 5-HT and the 5-HT2 receptor agonist than proximal segments. AT2, V2 and 5-HT1B/1D receptor agonists did not elicit vascular responses. Additionally, AT1 receptor agonists elicited mild, yet not significantly different maximal responses between segments. Conclusion The results of this study are consistent with contractile properties of rat OA being mediated via AT1, V1 and 5-HT2 receptors, and are dependent upon the OA segment. Furthermore, vasopressin-induced constriction of the OA, regardless of a bolus dose or a first and second concentration response curve retained this unique segmental difference and therefore we hypothesize this may be a pathophysiological response in the regulation of blood flow through the OA. PMID:24192548

A systematic review of definitions and classification systems of adjacent segment pathology.

Science.gov (United States)

Kraemer, Paul; Fehlings, Michael G; Hashimoto, Robin; Lee, Michael J; Anderson, Paul A; Chapman, Jens R; Raich, Annie; Norvell, Daniel C

2012-10-15

Systematic review. To undertake a systematic review to determine how "adjacent segment degeneration," "adjacent segment disease," or clinical pathological processes that serve as surrogates for adjacent segment pathology are classified and defined in the peer-reviewed literature. Adjacent segment degeneration and adjacent segment disease are terms referring to degenerative changes known to occur after reconstructive spine surgery, most commonly at an immediately adjacent functional spinal unit. These can include disc degeneration, instability, spinal stenosis, facet degeneration, and deformity. The true incidence and clinical impact of degenerative changes at the adjacent segment is unclear because there is lack of a universally accepted classification system that rigorously addresses clinical and radiological issues. A systematic review of the English language literature was undertaken and articles were classified using the Grades of Recommendation Assessment, Development, and Evaluation criteria. RESULTS.: Seven classification systems of spinal degeneration, including degeneration at the adjacent segment, were identified. None have been evaluated for reliability or validity specific to patients with degeneration at the adjacent segment. The ways in which terms related to adjacent segment "degeneration" or "disease" are defined in the peer-reviewed literature are highly variable. On the basis of the systematic review presented in this article, no formal classification system for either cervical or thoracolumbar adjacent segment disorders currently exists. No recommendations regarding the use of current classification of degeneration at any segments can be made based on the available literature. A new comprehensive definition for adjacent segment pathology (ASP, the now preferred terminology) has been proposed in this Focus Issue, which reflects the diverse pathology observed at functional spinal units adjacent to previous spinal reconstruction and balances

Targeting Political Communications: A Problem in Market Segmentation.

Science.gov (United States)

Markwart, Richard I.

Political campaigns are major, high-budget marketing efforts, but because they are usually managed by people with little training in either marketing or communications, they fail to persuade voters to vote in the desired way. Political targeting can be treated as a segmentation problem, one of identifying and responding to the specific qualities…

Reflection symmetry-integrated image segmentation.

Science.gov (United States)

Sun, Yu; Bhanu, Bir

2012-09-01

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

Fully convolutional neural networks improve abdominal organ segmentation

Science.gov (United States)

Bobo, Meg F.; Bao, Shunxing; Huo, Yuankai; Yao, Yuang; Virostko, Jack; Plassard, Andrew J.; Lyu, Ilwoo; Assad, Albert; Abramson, Richard G.; Hilmes, Melissa A.; Landman, Bennett A.

2018-03-01

Abdominal image segmentation is a challenging, yet important clinical problem. Variations in body size, position, and relative organ positions greatly complicate the segmentation process. Historically, multi-atlas methods have achieved leading results across imaging modalities and anatomical targets. However, deep learning is rapidly overtaking classical approaches for image segmentation. Recently, Zhou et al. showed that fully convolutional networks produce excellent results in abdominal organ segmentation of computed tomography (CT) scans. Yet, deep learning approaches have not been applied to whole abdomen magnetic resonance imaging (MRI) segmentation. Herein, we evaluate the applicability of an existing fully convolutional neural network (FCNN) designed for CT imaging to segment abdominal organs on T2 weighted (T2w) MRI's with two examples. In the primary example, we compare a classical multi-atlas approach with FCNN on forty-five T2w MRI's acquired from splenomegaly patients with five organs labeled (liver, spleen, left kidney, right kidney, and stomach). Thirty-six images were used for training while nine were used for testing. The FCNN resulted in a Dice similarity coefficient (DSC) of 0.930 in spleens, 0.730 in left kidneys, 0.780 in right kidneys, 0.913 in livers, and 0.556 in stomachs. The performance measures for livers, spleens, right kidneys, and stomachs were significantly better than multi-atlas (p < 0.05, Wilcoxon rank-sum test). In a secondary example, we compare the multi-atlas approach with FCNN on 138 distinct T2w MRI's with manually labeled pancreases (one label). On the pancreas dataset, the FCNN resulted in a median DSC of 0.691 in pancreases versus 0.287 for multi-atlas. The results are highly promising given relatively limited training data and without specific training of the FCNN model and illustrate the potential of deep learning approaches to transcend imaging modalities. 1

Prognosis and high-risk complication identification in unselected patients with ST-segment elevation myocardial infarction treated with primary percutaneous coronary intervention

DEFF Research Database (Denmark)

Andersson, Hedvig; Ripa, Maria Sejersten; Clemmensen, Peter

2010-01-01

The aim of this study was to evaluate treatment with primary percutaneous coronary intervention (PCI) in unselected patients with ST-segment elevation myocardial infarction (STEMI).......The aim of this study was to evaluate treatment with primary percutaneous coronary intervention (PCI) in unselected patients with ST-segment elevation myocardial infarction (STEMI)....

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.

A novel infrastructure modularity index for the segmentation of water distribution networks

Science.gov (United States)

Giustolisi, O.; Ridolfi, L.

2014-10-01

The search for suitable segmentations is a challenging and urgent issue for the analysis, planning and management of complex water distribution networks (WDNs). In fact, complex and large size hydraulic systems require the division into modules in order to simplify the analysis and the management tasks. In the complex network theory, modularity index has been proposed as a measure of the strength of the network division into modules and its maximization is used in order to identify community of nodes (i.e., modules) which are characterized by strong interconnections. Nevertheless, modularity index needs to be revised considering the specificity of the hydraulic systems as infrastructure systems. To this aim, the classic modularity index has been recently modified and tailored for WDNs. Nevertheless, the WDN-oriented modularity is affected by the resolution limit stemming from classic modularity index. Such a limit hampers the identification/design of small modules and this is a major drawback for technical tasks requiring a detailed resolution of the network segmentation. In order to get over this problem, we propose a novel infrastructure modularity index that is not affected by the resolution limit of the classic one. The rationale and good features of the proposed index are theoretically demonstrated and discussed using two real hydraulic networks.

Morphometric Atlas Selection for Automatic Brachial Plexus Segmentation

International Nuclear Information System (INIS)

Van de Velde, Joris; Wouters, Johan; Vercauteren, Tom; De Gersem, Werner; Duprez, Fréderic; De Neve, Wilfried; Van Hoof, Tom

2015-01-01

Purpose: The purpose of this study was to determine the effects of atlas selection based on different morphometric parameters, on the accuracy of automatic brachial plexus (BP) segmentation for radiation therapy planning. The segmentation accuracy was measured by comparing all of the generated automatic segmentations with anatomically validated gold standard atlases developed using cadavers. Methods and Materials: Twelve cadaver computed tomography (CT) atlases (3 males, 9 females; mean age: 73 years) were included in the study. One atlas was selected to serve as a patient, and the other 11 atlases were registered separately onto this “patient” using deformable image registration. This procedure was repeated for every atlas as a patient. Next, the Dice and Jaccard similarity indices and inclusion index were calculated for every registered BP with the original gold standard BP. In parallel, differences in several morphometric parameters that may influence the BP segmentation accuracy were measured for the different atlases. Specific brachial plexus-related CT-visible bony points were used to define the morphometric parameters. Subsequently, correlations between the similarity indices and morphometric parameters were calculated. Results: A clear negative correlation between difference in protraction-retraction distance and the similarity indices was observed (mean Pearson correlation coefficient = −0.546). All of the other investigated Pearson correlation coefficients were weak. Conclusions: Differences in the shoulder protraction-retraction position between the atlas and the patient during planning CT influence the BP autosegmentation accuracy. A greater difference in the protraction-retraction distance between the atlas and the patient reduces the accuracy of the BP automatic segmentation result

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...

Fragmented esophageal smooth muscle contraction segments on high resolution manometry: a marker of esophageal hypomotility.

Science.gov (United States)

Porter, R F; Kumar, N; Drapekin, J E; Gyawali, C P

2012-08-01

Esophageal peristalsis consists of a chain of contracting striated and smooth muscle segments on high resolution manometry (HRM). We compared smooth muscle contraction segments in symptomatic subjects with reflux disease to healthy controls. High resolution manometry Clouse plots were analyzed in 110 subjects with reflux disease (50 ± 1.4 years, 51.5% women) and 15 controls (27 ± 2.1 years, 60.0% women). Using the 30 mmHg isobaric contour tool, sequences were designated fragmented if either smooth muscle contraction segment was absent or if the two smooth muscle segments were separated by a pressure trough, and failed if both smooth muscle contraction segments were absent. The discriminative value of contraction segment analysis was assessed. A total of 1115 swallows were analyzed (reflux group: 965, controls: 150). Reflux subjects had lower peak and averaged contraction amplitudes compared with controls (P value to HRM analysis. Specifically, fragmented smooth muscle contraction segments may be a marker of esophageal hypomotility. © 2012 Blackwell Publishing Ltd.

Segmentation of urinary bladder in CT Urography (CTU) using CLASS

Science.gov (United States)

Hadjiiski, Lubomir; Chan, Heang-Ping; Law, Yuen; Cohan, Richard H.; Caoili, Elaine M.; Cho, Hyun-Chong; Zhou, Chuan; Wei, Jun

2012-03-01

We are developing a computerized system for bladder segmentation on CTU, as a critical component for computer aided diagnosis of bladder cancer. A challenge for bladder segmentation is the presence of regions without contrast (NC) and filled with IV contrast (C). We are developing a Conjoint Level set Analysis and Segmentation System (CLASS) specifically for this application. CLASS performs a series of image processing tasks: preprocessing, initial segmentation, and 3D and 2D level set segmentation and post-processing, designed according to the characteristics of the bladder in CTU. The NC and the C regions of the bladder were segmented separately in CLASS. The final contour is obtained in the post-processing stage by the union of the NC and C contours. Seventy bladders (31 containing lesions, 24 containing wall thickening, and 15 normal) were segmented. The performance of CLASS was assessed by rating the quality of the contours on a 5-point scale (1= "very poor", 3= "fair", 5 = "excellent"). For the 53 partially contrast-filled bladders, the average quality ratings for the 53 NC and 53 C regions were 4.0+/-0.7 and 4.0+/-1.0, respectively. 46 NC and 41 C regions were given quality ratings of 4 or above. Only 2 NC and 5 C regions had ratings under 3. The average quality ratings for the remaining 12 completely no contrast (NC) and 5 completely contrast-filled (C) bladder contours were 3.3+/-1.0 and 3.4+/-0.5, respectively. After combining the NC and C contours for each of the 70 bladders, 46 had quality ratings of 4 or above. Only 4 had ratings under 3. The average quality rating was 3.8+/-0.7. The results demonstrate the potential of CLASS for automated segmentation of the bladder.

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.

Novel Music Segmentation Interface and the Jazz Tune Collection

NARCIS (Netherlands)

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

2015-01-01

In this paper we present MOSSA, an easy-to-use interface for mobile devices, developed to annotate the segment structure of music. Moreover, we present the jazz tune collection (JTC), a database of 125 Jazz melodies annotated using MOSSA, and developed specifically for benchmarking of computational

Image Segmentation Parameter Optimization Considering Within- and Between-Segment Heterogeneity at Multiple Scale Levels: Test Case for Mapping Residential Areas Using Landsat Imagery

Directory of Open Access Journals (Sweden)

Brian A. Johnson

2015-10-01

Full Text Available Multi-scale/multi-level geographic object-based image analysis (MS-GEOBIA methods are becoming widely-used in remote sensing because single-scale/single-level (SS-GEOBIA methods are often unable to obtain an accurate segmentation and classification of all land use/land cover (LULC types in an image. However, there have been few comparisons between SS-GEOBIA and MS-GEOBIA approaches for the purpose of mapping a specific LULC type, so it is not well understood which is more appropriate for this task. In addition, there are few methods for automating the selection of segmentation parameters for MS-GEOBIA, while manual selection (i.e., trial-and-error approach of parameters can be quite challenging and time-consuming. In this study, we examined SS-GEOBIA and MS-GEOBIA approaches for extracting residential areas in Landsat 8 imagery, and compared naïve and parameter-optimized segmentation approaches to assess whether unsupervised segmentation parameter optimization (USPO could improve the extraction of residential areas. Our main findings were: (i the MS-GEOBIA approaches achieved higher classification accuracies than the SS-GEOBIA approach, and (ii USPO resulted in more accurate MS-GEOBIA classification results while reducing the number of segmentation levels and classification variables considerably.

Japanese migration in contemporary Japan: economic segmentation and interprefectural migration.

Science.gov (United States)

Fukurai, H

1991-01-01

This paper examines the economic segmentation model in explaining 1985-86 Japanese interregional migration. The analysis takes advantage of statistical graphic techniques to illustrate the following substantive issues of interregional migration: (1) to examine whether economic segmentation significantly influences Japanese regional migration and (2) to explain socioeconomic characteristics of prefectures for both in- and out-migration. Analytic techniques include a latent structural equation (LISREL) methodology and statistical residual mapping. The residual dispersion patterns, for instance, suggest the extent to which socioeconomic and geopolitical variables explain migration differences by showing unique clusters of unexplained residuals. The analysis further points out that extraneous factors such as high residential land values, significant commuting populations, and regional-specific cultures and traditions need to be incorporated in the economic segmentation model in order to assess the extent of the model's reliability in explaining the pattern of interprefectural migration.

Automated segmentation of dental CBCT image with prior-guided sequential random forests

Energy Technology Data Exchange (ETDEWEB)

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

2016-01-15

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

Automated segmentation of dental CBCT image with prior-guided sequential random forests

International Nuclear Information System (INIS)

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

2016-01-01

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

Determining the proportion of coronary segments assessable on 16-slice CT coronary angiography: a brief report

International Nuclear Information System (INIS)

Soon, K. H.; Cox, N.; Eccleston, D.; Lim, Y.; Chaitowitz, I.; Bell, K. W.; Kelly, A-M.

2007-01-01

Computed tomography coronary angiography (CT-CA) is becoming a popular non-invasive coronary imaging method. We aimed to determine the proportion of coronary segments assessable on a 16-slice CT in comparison with conventional selective coronary angiography (SCA). We identified all patients who had both 16-slice CT-CA and recent SCA (less than 12 months) from March 2004 to July 2005. Two CT reporters blinded to SCA independently classified coronary segment assessability on CT-CA. A cardiologist blinded to CT findings classified assess-ability of coronary segments on SCA. Data were analysed using descriptive statistics and proportion of agreement. Ninety-five study pairs were included in the analysis. Of those, 1161 coronary segments were deemed assessable on SCA and 1103 segments (95%) were also assessable on CT-CA. Nonassessable segments on CT-CA were predominantly in the distal segments and branches of coronary arteries. Reasons for nonassessability were small calibre (48.3%), motion artefacts (20.7%) and poorly reconstructed segments (22.4%). The 16-slice CT was able to assess a high proportion of but not all coronary segments. Nonassessable segments were predominantly distal segments or branches of coronary arteries. Motion artefacts due to heart-rate changes, small calibre and poorly reconstructed images were main causes of nonassessability on 16-slice CT-CA

Clonal expansion of T-cell receptor beta gene segment in the retrocochlear lesions of EAE mice.

Science.gov (United States)

Cheng, K C; Lee, K M; Yoo, T J

1998-01-01

It has been reported that the T cell receptor V beta 8.2 (TcrbV8.2) gene segment is predominantly expressed in encephalomyelitic T cells responding to myelin basic protein (MBP) in experimental allergic encephalomyelitis (EAE) mice. We have demonstrated retrocochlear hearing loss in EAE mice in previous studies. Administration of a monoclonal antibody specific to the T cell receptor V beta 8 (TcrbV8) subfamily prevented both this type of hearing loss and the central nerve disease. In this study, we examined the role of the TcrbV8.2 gene segment in the retrocochlear lesions of EAE mice. A clonal expression of T cell receptor beta chain gene segment (TcrbV8.2-TcrbD2-TcrbJ2.7) was identified in the retrocochlear lesions. The TcrbV8.2 gene segment appears to recombine only with TcrbJ2.1 (32.1%) and TcrbJ2.7 (67.9%) gene segments. The TcrbJ2.7 gene segment has also been previously identified as the dominant TcrbJ gene in the lymph nodes of EAE mice. Only TcrbD2, with a length of 4 amino acids, was observed recombining with these TcrbV8.2 sequences. G and C nucleotides are predominantly expressed at the N regions between the V-D and D-J junctions. This dominant TcrbV gene segment (TcrbV8.2-TcrbD2-TcrbJ2.7) observed in the retrocochlear lesions has been identified in the MBP-specific T cells from the lymph nodes of EAE mice. These results suggest that a small subset of antigen-specific T cells migrate to, and expand at, the retrocochlear lesions, which leads to hearing loss.

Customer Segmentation by Factors Influencing Brand Loyalty and Customer Involvement

OpenAIRE

Tereza Vebrová; Kateřina Venclová; Stanislav Rojík

2016-01-01

Brand loyalty and customer involvement are two important concepts that help explain and understand a significant part of consumer shopping behavior. The aim of the present work is to identify factors influencing brand loyalty and customer involvement. A further aim is to consider subsequent segmentation of customers with respect to different degrees of brand loyalty and customer involvement. The research was focused on the field of Czech telecommunication services – mobile operators. Primary ...

The use of ileocolic segment for esophageal replacement in children

Directory of Open Access Journals (Sweden)

Harshjeet Singh Bal

2016-01-01

Full Text Available Aims: To evaluate and describe the procedure and outcome of ileocolic replacement of esophagus. Materials and Methods: We review 7 children with esophageal injuries, who underwent esophageal replacement using ileocolic segment in Christian Medical College, Vellore, India between 2006 and 2014. Results: The ileocolic segment was used in 7 children with scarred or inadequate esophagus. There were 4 girls and 3 boys, who underwent esophageal replacement using isoperistaltic ileocolic segment in this period. Age at presentation varied from 1 month to 14 years with an average of 4.6 years. The indications for ileocolic replacements were corrosive strictures in 5, failed esophageal atresia repair in one and gastric volvulus related esophageal stricture in another. The average follow-up duration was 37 months. One child with corrosive stricture lost to follow-up and died 2 years later in another center. Other 6 children were free of dysphagia till the last follow-up. Conclusions: Although the ileocolic segment is not commonly used for esophageal substitution, it can be useful in special situations where the substitution needs to reach the high cervical esophagus and also where the stomach is scarred and not suitable for gastric pull-up.

Automated segmentation of geographic atrophy using deep convolutional neural networks

Science.gov (United States)

Hu, Zhihong; Wang, Ziyuan; Sadda, SriniVas R.

2018-02-01

Geographic atrophy (GA) is an end-stage manifestation of the advanced age-related macular degeneration (AMD), the leading cause of blindness and visual impairment in developed nations. Techniques to rapidly and precisely detect and quantify GA would appear to be of critical importance in advancing the understanding of its pathogenesis. In this study, we develop an automated supervised classification system using deep convolutional neural networks (CNNs) for segmenting GA in fundus autofluorescene (FAF) images. More specifically, to enhance the contrast of GA relative to the background, we apply the contrast limited adaptive histogram equalization. Blood vessels may cause GA segmentation errors due to similar intensity level to GA. A tensor-voting technique is performed to identify the blood vessels and a vessel inpainting technique is applied to suppress the GA segmentation errors due to the blood vessels. To handle the large variation of GA lesion sizes, three deep CNNs with three varying sized input image patches are applied. Fifty randomly chosen FAF images are obtained from fifty subjects with GA. The algorithm-defined GA regions are compared with manual delineation by a certified grader. A two-fold cross-validation is applied to evaluate the algorithm performance. The mean segmentation accuracy, true positive rate (i.e. sensitivity), true negative rate (i.e. specificity), positive predictive value, false discovery rate, and overlap ratio, between the algorithm- and manually-defined GA regions are 0.97 +/- 0.02, 0.89 +/- 0.08, 0.98 +/- 0.02, 0.87 +/- 0.12, 0.13 +/- 0.12, and 0.79 +/- 0.12 respectively, demonstrating a high level of agreement.

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

Multivariate analysis for customer segmentation based on RFM

Directory of Open Access Journals (Sweden)

Álvaro Julio Cuadros López

2018-02-01

Full Text Available Context: To build a successful relationship management (CRM, companies must start with the identification of the true value of customers, as this provides basic information to implement more targeted and customized marketing strategies. The RFM methodology, a classic analysis tool that uses three evaluation parameters, allows companies to understand customer behavior, and to establish customer segments. The addition of a new parameter in the traditional technique is an opportunity to refine the possible outcomes of a customer segmentation since it not only provides a new element of evaluation to identify the most valuable customers, but it also makes it possible to differentiate and get to know customers even better. Method: The article presents a methodology that allows to establish customer segments using an extended RFM method with new variables, selected through multivariate analysis..  Results: The proposed implementation was applied in a company in which variables such as profit, profit percentage, and billing due date were tested. Therefore, it was possible to establish a more detailed customer segmentation than with the classic RFM. Conclusions: the RFM analysis is a method widely used in the industry for its easy understanding and applicability. However, it can be improved with the use of statistical procedures and new variables, which will allow companies to have deeper information about the behavior of the clients, and will facilitate the design of specific marketing strategies.

4D segmentation of brain MR images with constrained cortical thickness variation.

Directory of Open Access Journals (Sweden)

Li Wang

Full Text Available Segmentation of brain MR images plays an important role in longitudinal investigation of developmental, aging, disease progression changes in the cerebral cortex. However, most existing brain segmentation methods consider multiple time-point images individually and thus cannot achieve longitudinal consistency. For example, cortical thickness measured from the segmented image will contain unnecessary temporal variations, which will affect the time related change pattern and eventually reduce the statistical power of analysis. In this paper, we propose a 4D segmentation framework for the adult brain MR images with the constraint of cortical thickness variations. Specifically, we utilize local intensity information to address the intensity inhomogeneity, spatial cortical thickness constraint to maintain the cortical thickness being within a reasonable range, and temporal cortical thickness variation constraint in neighboring time-points to suppress the artificial variations. The proposed method has been tested on BLSA dataset and ADNI dataset with promising results. Both qualitative and quantitative experimental results demonstrate the advantage of the proposed method, in comparison to other state-of-the-art 4D segmentation methods.

Using data mining to segment healthcare markets from patients' preference perspectives.

Science.gov (United States)

Liu, Sandra S; Chen, Jie

2009-01-01

This paper aims to provide an example of how to use data mining techniques to identify patient segments regarding preferences for healthcare attributes and their demographic characteristics. Data were derived from a number of individuals who received in-patient care at a health network in 2006. Data mining and conventional hierarchical clustering with average linkage and Pearson correlation procedures are employed and compared to show how each procedure best determines segmentation variables. Data mining tools identified three differentiable segments by means of cluster analysis. These three clusters have significantly different demographic profiles. The study reveals, when compared with traditional statistical methods, that data mining provides an efficient and effective tool for market segmentation. When there are numerous cluster variables involved, researchers and practitioners need to incorporate factor analysis for reducing variables to clearly and meaningfully understand clusters. Interests and applications in data mining are increasing in many businesses. However, this technology is seldom applied to healthcare customer experience management. The paper shows that efficient and effective application of data mining methods can aid the understanding of patient healthcare preferences.

A new model for the determination of limb segment mass in children.

Science.gov (United States)

Kuemmerle-Deschner, J B; Hansmann, S; Rapp, H; Dannecker, G E

2007-04-01

The knowledge of limb segment masses is critical for the calculation of joint torques. Several methods for segment mass estimation have been described in the literature. They are either inaccurate or not applicable to the limb segments of children. Therefore, we developed a new cylinder brick model (CBM) to estimate segment mass in children. The aim of this study was to compare CBM and a model based on a polynomial regression equation (PRE) to volume measurement obtained by the water displacement method (WDM). We examined forearms, hands, lower legs, and feet of 121 children using CBM, PRE, and WDM. The differences between CBM and WDM or PRE and WDM were calculated and compared using a Bland-Altman plot of differences. Absolute limb segment mass measured by WDM ranged from 0.16+/-0.04 kg for hands in girls 5-6 years old, up to 2.72+/-1.03 kg for legs in girls 11-12 years old. The differences of normalised segment masses ranged from 0.0002+/-0.0021 to 0.0011+/-0.0036 for CBM-WDM and from 0.0023+/-0.0041 to 0.0127+/-0.036 for PRE-WDM (values are mean+/-2 S.D.). The CBM showed better agreement with WDM than PRE for all limb segments in girls and boys. CBM is accurate and superior to PRE for the estimation of individual limb segment mass of children. Therefore, CBM is a practical and useful tool for the analysis of kinetic parameters and the calculation of resulting forces to assess joint functionality in children.

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...

Three-dimensional geometric model of the middle segment of the thoracic spine based on graphical images for finite element analysis

Directory of Open Access Journals (Sweden)

Rozilene Maria Cota Aroeira

2017-05-01

Full Text Available Abstract Introduction: Biomedical studies involve complex anatomical structures, which require specific methodology to generate their geometric models. The middle segment of the thoracic spine (T5-T10 is the site of the highest incidence of vertebral deformity in adolescents. Traditionally, its geometries are derived from computed tomography or magnetic resonance imaging data. However, this approach may restrict certain studies. The study aimed to generate two 3D geometric model of the T5-T10 thoracic spine segment, obtained from graphical images, and to create mesh for finite element studies. Methods A 3D geometric model of T5-T10 was generated using two anatomical images of T6 vertebra (side and top. The geometric model was created in Autodesk® Maya® 3D 2013, and the mesh process in HiperMesh and MeshMixer (v11.0.544 Autodesk. Results The T5-T10 thoracic segment model is presented with its passive components, bones, intervertebral discs and flavum, intertransverse and supraspinous ligaments, in different views, as well as the volumetric mesh. Conclusion The 3D geometric model generated from graphical images is suitable for application in non-patient-specific finite element model studies or, with restrictions, in the use of computed tomography or magnetic resonance imaging. This model may be useful for biomechanical studies related to the middle thoracic spine, the most vulnerable site for vertebral deformations.

Attitudes of the Lifestyle of Health and Sustainability Segment in Hungary

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Zoltán Szakály

2017-09-01

Full Text Available The aim of the research was to define the size of the Hungarian LOHAS (Lifestyle of Health and Sustainability consumer group by analyzing its lifestyle based on sustainable values. To achieve this goal, a representative questionnaire-based survey was carried out involving 1000 individuals in Hungary. During the value-orientated research, 25 lifestyle statements were drawn up. According to the results, five value-based segments could be distinguished. The largest cluster, the young trend followers group, reflects the characteristics of the LOHAS consumers’ lifestyle to the greatest extent. However, this segment cannot entirely be regarded as a consumer group devoted to LOHAS values, which is why a further segmentation of this group was necessary. As a result of this further segmentation, the third sub-cluster, which emphasizes the ethical (competence statements the most, can be identified with the LOHAS consumer group, which makes up 8.7% of the Hungarian population. Further research is necessary to find out whether the situation regarding value orientation in Hungary is similar to that in other Eastern European countries whose social and cultural backgrounds are very similar. Revealing the values of the Lifestyle of Health and Sustainability segment contributes to the extension of the literature.

Random walks with statistical shape prior for cochlea and inner ear segmentation in micro-CT images

DEFF Research Database (Denmark)

Ruiz Pujadas, Esmeralda; Piella, Gemma; Kjer, Hans Martin

2017-01-01

A cochlear implant is an electronic device which can restore sound to completely or partially deaf patients. For surgical planning, a patient-specific model of the inner ear must be built using high-resolution images accurately segmented. We propose a new framework for segmentation of micro-CT...

ADVANCED CLUSTER BASED IMAGE SEGMENTATION

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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.

Non-canonical ribosomal DNA segments in the human genome, and nucleoli functioning.

Science.gov (United States)

Kupriyanova, Natalia S; Netchvolodov, Kirill K; Sadova, Anastasia A; Cherepanova, Marina D; Ryskov, Alexei P

2015-11-10

Ribosomal DNA (rDNA) in the human genome is represented by tandem repeats of 43 kb nucleotide sequences that form nucleoli organizers (NORs) on each of five pairs of acrocentric chromosomes. RDNA-similar segments of different lengths are also present on (NOR)(-) chromosomes. Many of these segments contain nucleotide substitutions, supplementary microsatellite clusters, and extended deletions. Recently, it was shown that, in addition to ribosome biogenesis, nucleoli exhibit additional functions, such as cell-cycle regulation and response to stresses. In particular, several stress-inducible loci located in the ribosomal intergenic spacer (rIGS) produce stimuli-specific noncoding nucleolus RNAs. By mapping the 5'/3' ends of the rIGS segments scattered throughout (NOR)(-) chromosomes, we discovered that the bonds in the rIGS that were most often susceptible to disruption in the rIGS were adjacent to, or overlapped with stimuli-specific inducible loci. This suggests the interconnection of the two phenomena - nucleoli functioning and the scattering of rDNA-like sequences on (NOR)(-) chromosomes. Copyright © 2015 Elsevier B.V. All rights reserved.

Smoke regions extraction based on two steps segmentation and motion detection in early fire

Science.gov (United States)

Jian, Wenlin; Wu, Kaizhi; Yu, Zirong; Chen, Lijuan

2018-03-01

Aiming at the early problems of video-based smoke detection in fire video, this paper proposes a method to extract smoke suspected regions by combining two steps segmentation and motion characteristics. Early smoldering smoke can be seen as gray or gray-white regions. In the first stage, regions of interests (ROIs) with smoke are obtained by using two step segmentation methods. Then, suspected smoke regions are detected by combining the two step segmentation and motion detection. Finally, morphological processing is used for smoke regions extracting. The Otsu algorithm is used as segmentation method and the ViBe algorithm is used to detect the motion of smoke. The proposed method was tested on 6 test videos with smoke. The experimental results show the effectiveness of our proposed method over visual observation.

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

Energy Technology Data Exchange (ETDEWEB)

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

2012-03-15

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

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

International Nuclear Information System (INIS)

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

2012-01-01

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

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

Science.gov (United States)

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

2012-03-01

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

Cluster Ensemble-Based Image Segmentation

Directory of Open Access Journals (Sweden)

Xiaoru Wang

2013-07-01

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

Population segmentation: an approach to reducing childhood obesity inequalities.

Science.gov (United States)

Mahmood, Hashum; Lowe, Susan

2017-05-01

The aims of this study are threefold: (1) to investigate the relationship between socio-economic status (inequality) and childhood obesity prevalence within Birmingham local authority, (2) to identify any change in childhood obesity prevalence between deprivation quintiles and (3) to analyse individualised Birmingham National Child Measurement Programme (NCMP) data using a population segmentation tool to better inform obesity prevention strategies. Data from the NCMP for Birmingham (2010/2011 and 2014/2015) were analysed using the deprivation scores from the Income Domain Affecting Children Index (IDACI 2010). The percentage of children with excess weight was calculated for each local deprivation quintile. Population segmentation was carried out using the Experian's Mosaic Public Sector 6 (MPS6) segmentation tool. Childhood obesity levels have remained static at the national and Birmingham level. For Year 6 pupils, obesity levels have increased in the most deprived deprivation quintiles for boys and girls. The most affluent quintile shows a decreasing trend of obesity prevalence for boys and girls in both year groups. For the middle quintiles, the results show fluctuating trends. This research highlighted the link in Birmingham between obesity and socio-economic factors with the gap increasing between deprivation quintiles. Obesity is a complex problem that cannot simply be addressed through targeting most deprived populations, rather through a range of effective interventions tailored for the various population segments that reside within communities. Using population segmentation enables a more nuanced understanding of the potential barriers and levers within populations on their readiness for change. The segmentation of childhood obesity data will allow utilisation of social marketing methodology that will facilitate identification of suitable methods for interventions and motivate individuals to sustain behavioural change. Sequentially, it will also inform

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.

MULTI-SCALE SEGMENTATION OF HIGH RESOLUTION REMOTE SENSING IMAGES BY INTEGRATING MULTIPLE FEATURES

Directory of Open Access Journals (Sweden)

Y. Di

2017-05-01

Full Text Available Most of multi-scale segmentation algorithms are not aiming at high resolution remote sensing images and have difficulty to communicate and use layers’ information. In view of them, we proposes a method of multi-scale segmentation of high resolution remote sensing images by integrating multiple features. First, Canny operator is used to extract edge information, and then band weighted distance function is built to obtain the edge weight. According to the criterion, the initial segmentation objects of color images can be gained by Kruskal minimum spanning tree algorithm. Finally segmentation images are got by the adaptive rule of Mumford–Shah region merging combination with spectral and texture information. The proposed method is evaluated precisely using analog images and ZY-3 satellite images through quantitative and qualitative analysis. The experimental results show that the multi-scale segmentation of high resolution remote sensing images by integrating multiple features outperformed the software eCognition fractal network evolution algorithm (highest-resolution network evolution that FNEA on the accuracy and slightly inferior to FNEA on the efficiency.

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

Three-body segment musculoskeletal model of the upper limb

Directory of Open Access Journals (Sweden)

Valdmanová L.

2013-06-01

Full Text Available The main aim is to create a computational three-body segment model of an upper limb of a human body for determination of muscle forces generated to keep a given loaded upper limb position. The model consists of three segments representing arm, forearm, hand and of all major muscles connected to the segments. Muscle origins and insertions determination corresponds to a real anatomy. Muscle behaviour is defined according to the Hill-type muscle model consisting of contractile and viscoelastic element. The upper limb is presented by a system of three rigid bars connected by rotational joints. The whole limb is fixed to the frame in the shoulder joint. A static balance problem is solved by principle of virtual work. The system of equation describing the musculoskeletal system is overdetermined because more muscles than necessary contribute to get the concrete upper limb position. Hence the mathematical problem is solved by an optimization method searching the least energetically-consuming solution. The upper limb computational model is verified by electromyography of the biceps brachii muscle.

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.

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

International Nuclear Information System (INIS)

Debreuve, Eric

2000-01-01

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

ReMixT: clone-specific genomic structure estimation in cancer.

Science.gov (United States)

McPherson, Andrew W; Roth, Andrew; Ha, Gavin; Chauve, Cedric; Steif, Adi; de Souza, Camila P E; Eirew, Peter; Bouchard-Côté, Alexandre; Aparicio, Sam; Sahinalp, S Cenk; Shah, Sohrab P

2017-07-27

Somatic evolution of malignant cells produces tumors composed of multiple clonal populations, distinguished in part by rearrangements and copy number changes affecting chromosomal segments. Whole genome sequencing mixes the signals of sampled populations, diluting the signals of clone-specific aberrations, and complicating estimation of clone-specific genotypes. We introduce ReMixT, a method to unmix tumor and contaminating normal signals and jointly predict mixture proportions, clone-specific segment copy number, and clone specificity of breakpoints. ReMixT is free, open-source software and is available at http://bitbucket.org/dranew/remixt .

Automatic segmentation of the glenohumeral cartilages from magnetic resonance images

International Nuclear Information System (INIS)

Neubert, A.; Yang, Z.; Engstrom, C.; Xia, Y.; Strudwick, M. W.; Chandra, S. S.; Crozier, S.; Fripp, J.

2016-01-01

Purpose: Magnetic resonance (MR) imaging plays a key role in investigating early degenerative disorders and traumatic injuries of the glenohumeral cartilages. Subtle morphometric and biochemical changes of potential relevance to clinical diagnosis, treatment planning, and evaluation can be assessed from measurements derived from in vivo MR segmentation of the cartilages. However, segmentation of the glenohumeral cartilages, using approaches spanning manual to automated methods, is technically challenging, due to their thin, curved structure and overlapping intensities of surrounding tissues. Automatic segmentation of the glenohumeral cartilages from MR imaging is not at the same level compared to the weight-bearing knee and hip joint cartilages despite the potential applications with respect to clinical investigation of shoulder disorders. In this work, the authors present a fully automated segmentation method for the glenohumeral cartilages using MR images of healthy shoulders. Methods: The method involves automated segmentation of the humerus and scapula bones using 3D active shape models, the extraction of the expected bone–cartilage interface, and cartilage segmentation using a graph-based method. The cartilage segmentation uses localization, patient specific tissue estimation, and a model of the cartilage thickness variation. The accuracy of this method was experimentally validated using a leave-one-out scheme on a database of MR images acquired from 44 asymptomatic subjects with a true fast imaging with steady state precession sequence on a 3 T scanner (Siemens Trio) using a dedicated shoulder coil. The automated results were compared to manual segmentations from two experts (an experienced radiographer and an experienced musculoskeletal anatomist) using the Dice similarity coefficient (DSC) and mean absolute surface distance (MASD) metrics. Results: Accurate and precise bone segmentations were achieved with mean DSC of 0.98 and 0.93 for the humeral head

Automatic segmentation of the glenohumeral cartilages from magnetic resonance images

Energy Technology Data Exchange (ETDEWEB)

Neubert, A., E-mail: ales.neubert@csiro.au [School of Information Technology and Electrical Engineering, University of Queensland, Brisbane 4072, Australia and The Australian E-Health Research Centre, CSIRO Health and Biosecurity, Brisbane 4029 (Australia); Yang, Z. [School of Information Technology and Electrical Engineering, University of Queensland, Brisbane 4072, Australia and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190 (China); Engstrom, C. [School of Human Movement Studies, University of Queensland, Brisbane 4072 (Australia); Xia, Y.; Strudwick, M. W.; Chandra, S. S.; Crozier, S. [School of Information Technology and Electrical Engineering, University of Queensland, Brisbane 4072 (Australia); Fripp, J. [The Australian E-Health Research Centre, CSIRO Health and Biosecurity, Brisbane, 4029 (Australia)

2016-10-15

Purpose: Magnetic resonance (MR) imaging plays a key role in investigating early degenerative disorders and traumatic injuries of the glenohumeral cartilages. Subtle morphometric and biochemical changes of potential relevance to clinical diagnosis, treatment planning, and evaluation can be assessed from measurements derived from in vivo MR segmentation of the cartilages. However, segmentation of the glenohumeral cartilages, using approaches spanning manual to automated methods, is technically challenging, due to their thin, curved structure and overlapping intensities of surrounding tissues. Automatic segmentation of the glenohumeral cartilages from MR imaging is not at the same level compared to the weight-bearing knee and hip joint cartilages despite the potential applications with respect to clinical investigation of shoulder disorders. In this work, the authors present a fully automated segmentation method for the glenohumeral cartilages using MR images of healthy shoulders. Methods: The method involves automated segmentation of the humerus and scapula bones using 3D active shape models, the extraction of the expected bone–cartilage interface, and cartilage segmentation using a graph-based method. The cartilage segmentation uses localization, patient specific tissue estimation, and a model of the cartilage thickness variation. The accuracy of this method was experimentally validated using a leave-one-out scheme on a database of MR images acquired from 44 asymptomatic subjects with a true fast imaging with steady state precession sequence on a 3 T scanner (Siemens Trio) using a dedicated shoulder coil. The automated results were compared to manual segmentations from two experts (an experienced radiographer and an experienced musculoskeletal anatomist) using the Dice similarity coefficient (DSC) and mean absolute surface distance (MASD) metrics. Results: Accurate and precise bone segmentations were achieved with mean DSC of 0.98 and 0.93 for the humeral head

Segmentation of corpus callosum using diffusion tensor imaging: validation in patients with glioblastoma

International Nuclear Information System (INIS)

Nazem-Zadeh, Mohammad-Reza; Saksena, Sona; Babajani-Fermi, Abbas; Jiang, Quan; Soltanian-Zadeh, Hamid; Rosenblum, Mark; Mikkelsen, Tom; Jain, Rajan

2012-01-01

This paper presents a three-dimensional (3D) method for segmenting corpus callosum in normal subjects and brain cancer patients with glioblastoma. Nineteen patients with histologically confirmed treatment naïve glioblastoma and eleven normal control subjects underwent DTI on a 3T scanner. Based on the information inherent in diffusion tensors, a similarity measure was proposed and used in the proposed algorithm. In this algorithm, diffusion pattern of corpus callosum was used as prior information. Subsequently, corpus callosum was automatically divided into Witelson subdivisions. We simulated the potential rotation of corpus callosum under tumor pressure and studied the reproducibility of the proposed segmentation method in such cases. Dice coefficients, estimated to compare automatic and manual segmentation results for Witelson subdivisions, ranged from 94% to 98% for control subjects and from 81% to 95% for tumor patients, illustrating closeness of automatic and manual segmentations. Studying the effect of corpus callosum rotation by different Euler angles showed that although segmentation results were more sensitive to azimuth and elevation than skew, rotations caused by brain tumors do not have major effects on the segmentation results. The proposed method and similarity measure segment corpus callosum by propagating a hyper-surface inside the structure (resulting in high sensitivity), without penetrating into neighboring fiber bundles (resulting in high specificity)

Comparison of segmentation techniques to determine the geometric parameters of structured surfaces

International Nuclear Information System (INIS)

MacAulay, Gavin D; Giusca, Claudiu L; Leach, Richard K; Senin, Nicola

2014-01-01

Structured surfaces, defined as surfaces characterized by topography features whose shape is defined by design specifications, are increasingly being used in industry for a variety of applications, including improving the tribological properties of surfaces. However, characterization of such surfaces still remains an issue. Techniques have been recently proposed, based on identifying and extracting the relevant features from a structured surface so they can be verified individually, using methods derived from those commonly applied to standard-sized parts. Such emerging approaches show promise but are generally complex and characterized by multiple data processing steps making performance difficult to assess. This paper focuses on the segmentation step, i.e. partitioning the topography so that the relevant features can be separated from the background. Segmentation is key for defining the geometric boundaries of the individual feature, which in turn affects any computation of feature size, shape and localization. This paper investigates the effect of varying the segmentation algorithm and its controlling parameters by considering a test case: a structured surface for bearing applications, the relevant features being micro-dimples designed for friction reduction. In particular, the mechanisms through which segmentation leads to identification of the dimple boundary and influences dimensional properties, such as dimple diameter and depth, are illustrated. It is shown that, by using different methods and control parameters, a significant range of measurement results can be achieved, which may not necessarily agree. Indications on how to investigate the influence of each specific choice are given; in particular, stability of the algorithms with respect to control parameters is analyzed as a means to investigate ease of calibration and flexibility to adapt to specific, application-dependent characterization requirements. (paper)

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

THE COMMUNICATION MIX ADRESSED TO THE FEMININE SEGMENT. CASE STUDY ON THE ROMANIAN MARKET OF COSMETIC PRODUCTS

Directory of Open Access Journals (Sweden)

CLAUDIA ELENA PAICU

2015-04-01

Full Text Available Currently, the female segment represents a genuine power in terms of consumer behavior. We can certainly argue that the feminine segment is no longer just a market niche. We can relate to this segment as the majority. To support this idea, we consider the data provided by the National Institute of Statistics. According to these statistics, the female segment sums up 51.4% of the total population, an increase being recorded in the last 10 years, from just over 50% to more than 51%. Therefore, it is not wrong to claim that feminine segment holds the majority in terms of consumer behavior. In this context, the female consumer’s preferences and needs should be integrated into all the communication strategies of organizations. The present study aims to see to what extent, at present, an attention is paid to this segment, proposing as an example a study in an area addressed in a high percentage to the feminine segment, the market of cosmetic products.

Hitchhiker'S Guide to Voxel Segmentation for Partial Volume Correction of in Vivo Magnetic Resonance Spectroscopy

Directory of Open Access Journals (Sweden)

Scott Quadrelli

2016-01-01

Full Text Available Partial volume effects have the potential to cause inaccuracies when quantifying metabolites using proton magnetic resonance spectroscopy (MRS. In order to correct for cerebrospinal fluid content, a spectroscopic voxel needs to be segmented according to different tissue contents. This article aims to detail how automated partial volume segmentation can be undertaken and provides a software framework for researchers to develop their own tools. While many studies have detailed the impact of partial volume correction on proton magnetic resonance spectroscopy quantification, there is a paucity of literature explaining how voxel segmentation can be achieved using freely available neuroimaging packages.

The use of atlas registration and graph cuts for prostate segmentation in magnetic resonance images

Energy Technology Data Exchange (ETDEWEB)

Korsager, Anne Sofie, E-mail: asko@hst.aau.dk; Østergaard, Lasse Riis [Department of Health Science and Technology, Aalborg University, Aalborg 9220 (Denmark); Fortunati, Valerio; Lijn, Fedde van der; Niessen, Wiro; Walsum, Theo van [Biomedical Imaging Group of Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC, Rotterdam 3015 GE Rotterdam (Netherlands); Carl, Jesper [Department of Medical Physics, Oncology, Aalborg University Hospital, Aalborg 9220 (Denmark)

2015-04-15

Purpose: An automatic method for 3D prostate segmentation in magnetic resonance (MR) images is presented for planning image-guided radiotherapy treatment of prostate cancer. Methods: A spatial prior based on intersubject atlas registration is combined with organ-specific intensity information in a graph cut segmentation framework. The segmentation is tested on 67 axial T{sub 2}-weighted MR images in a leave-one-out cross validation experiment and compared with both manual reference segmentations and with multiatlas-based segmentations using majority voting atlas fusion. The impact of atlas selection is investigated in both the traditional atlas-based segmentation and the new graph cut method that combines atlas and intensity information in order to improve the segmentation accuracy. Best results were achieved using the method that combines intensity information, shape information, and atlas selection in the graph cut framework. Results: A mean Dice similarity coefficient (DSC) of 0.88 and a mean surface distance (MSD) of 1.45 mm with respect to the manual delineation were achieved. Conclusions: This approaches the interobserver DSC of 0.90 and interobserver MSD 0f 1.15 mm and is comparable to other studies performing prostate segmentation in MR.

Linking gene regulation to cell behaviors in the posterior growth zone of sequentially segmenting arthropods.

Science.gov (United States)

Williams, Terri A; Nagy, Lisa M

2017-05-01

Virtually all arthropods all arthropods add their body segments sequentially, one by one in an anterior to posterior progression. That process requires not only segment specification but typically growth and elongation. Here we review the functions of some of the key genes that regulate segmentation: Wnt, caudal, Notch pathway, and pair-rule genes, and discuss what can be inferred about their evolution. We focus on how these regulatory factors are integrated with growth and elongation and discuss the importance and challenges of baseline measures of growth and elongation. We emphasize a perspective that integrates the genetic regulation of segment patterning with the cellular mechanisms of growth and elongation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Minimum monitor unit per segment IMRT planning and over-shoot-ratio

International Nuclear Information System (INIS)

Grigorov, G.; Barnett, R.; Chow, J.

2004-01-01

The aim of this work is to describe the modulation quality for dose delivery of small Multi-Leaf Collimator (MLC) fields and MU/segment. The results were obtained with Pinnacle (V6) and a Varian Clinac 2100 EX (Varis 6.2) linear accelerator. The over-shoot effect was investigated by comparing integrated multiple segmented exposures to a single exposure with the same number of total MU (1, 2, 3,4, 5 and 6 MU). To present the OS effect the Over-Shoot-Ratio (OSR) was defined as the ratio of the segmented dose for a 1 cm 2 field at depth to the static dose for the same field size and depth. OSR was measured as a function of MU/segment and dose rate. Measured results can be used to optimise IMRT planning and also to calculate the surface dose. The dependence of the dose in depth with 1, 2, 3, 4, and 5 MU/segments for 6 MV photon beam, dose rate of 100 MU/min and 1 cm 2 beam field at the central axis is presented, where the argument of the function is the depth and parameter of the function is the number of minimum MU/segment. The dependence of the overshoot ratio on the MU/segment with a parameter of the dose rates (100, 400 and 600 MU/min) is also shown. The effect increases with the dose rate and decreases with the increasing of the minimum number of MU/segment. Having measured OSR for the 2100 EX linac it is possible to do correction and calibration of the dose of the first segment of IMRT beam, where the dose to the target and on the surface can increase over the planed dose of 1 MU by 40% and 70% for dose rate of 400 and 600 MU/min respectively. The Over-Shoot-Ratio is an important parameter to be determined as part of the routine quality assurance for IMRT and can be used to significantly improve the agreement between planned and delivered doses to the patient

Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

Science.gov (United States)

Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang

2015-01-01

The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6–8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multimodality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. PMID:25562829

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,

Starch digestibility and predicted glycemic index in the bread fortified with pomelo (Citrus maxima) fruit segments.

Science.gov (United States)

Reshmi, S K; Sudha, M L; Shashirekha, M N

2017-12-15

The aim of this study was to evaluate the starch digestibility and predicted glycemic index in breads incorporated with pomelo fruit (Citrus maxima) segments. Volume of the white and brown breads supplemented with pomelo fresh segments increased, while the crumb firmness decreased. Bread with 20% fresh and 5% dry pomelo segments were sensorily acceptable. Bioactive components such as phenolics, flavonoids, naringin and carotenoids were retained to a greater extent in bread containing dry pomelo segments. The pomelo incorporated bread had higher levels of resistant starch fractions (3.87-10.96%) with low predicted glycemic index (62.97-53.13%), despite their higher total starch (69.87-75.47%) content compared to control bread. Thus pomelo segments in the product formulations lowered the glycemic index probably by inhibiting carbohydrate hydrolyzing enzyme activity which could be attributed to naringin. Hence fortified bread prepared from pomelo fruit segment is recommended to gain nutritional value and to decrease the risk of diabetes. Copyright © 2017 Elsevier Ltd. All rights reserved.

AN ADAPTIVE APPROACH FOR SEGMENTATION OF 3D LASER POINT CLOUD

Directory of Open Access Journals (Sweden)

Z. Lari

2012-09-01

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

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.

A label field fusion bayesian model and its penalized maximum rand estimator for image segmentation.

Science.gov (United States)

Mignotte, Max

2010-06-01

This paper presents a novel segmentation approach based on a Markov random field (MRF) fusion model which aims at combining several segmentation results associated with simpler clustering models in order to achieve a more reliable and accurate segmentation result. The proposed fusion model is derived from the recently introduced probabilistic Rand measure for comparing one segmentation result to one or more manual segmentations of the same image. This non-parametric measure allows us to easily derive an appealing fusion model of label fields, easily expressed as a Gibbs distribution, or as a nonstationary MRF model defined on a complete graph. Concretely, this Gibbs energy model encodes the set of binary constraints, in terms of pairs of pixel labels, provided by each segmentation results to be fused. Combined with a prior distribution, this energy-based Gibbs model also allows for definition of an interesting penalized maximum probabilistic rand estimator with which the fusion of simple, quickly estimated, segmentation results appears as an interesting alternative to complex segmentation models existing in the literature. This fusion framework has been successfully applied on the Berkeley image database. The experiments reported in this paper demonstrate that the proposed method is efficient in terms of visual evaluation and quantitative performance measures and performs well compared to the best existing state-of-the-art segmentation methods recently proposed in the literature.

Coronary arteries segmentation based on the 3D discrete wavelet transform and 3D neutrosophic transform.

Science.gov (United States)

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

2015-01-01

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

A statistical pixel intensity model for segmentation of confocal laser scanning microscopy images.

Science.gov (United States)

Calapez, Alexandre; Rosa, Agostinho

2010-09-01

Confocal laser scanning microscopy (CLSM) has been widely used in the life sciences for the characterization of cell processes because it allows the recording of the distribution of fluorescence-tagged macromolecules on a section of the living cell. It is in fact the cornerstone of many molecular transport and interaction quantification techniques where the identification of regions of interest through image segmentation is usually a required step. In many situations, because of the complexity of the recorded cellular structures or because of the amounts of data involved, image segmentation either is too difficult or inefficient to be done by hand and automated segmentation procedures have to be considered. Given the nature of CLSM images, statistical segmentation methodologies appear as natural candidates. In this work we propose a model to be used for statistical unsupervised CLSM image segmentation. The model is derived from the CLSM image formation mechanics and its performance is compared to the existing alternatives. Results show that it provides a much better description of the data on classes characterized by their mean intensity, making it suitable not only for segmentation methodologies with known number of classes but also for use with schemes aiming at the estimation of the number of classes through the application of cluster selection criteria.

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.

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

Science.gov (United States)

2013-01-01

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

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...

Automatic segmentation of dynamic neuroreceptor single-photon emission tomography images using fuzzy clustering

International Nuclear Information System (INIS)

Acton, P.D.; Pilowsky, L.S.; Kung, H.F.; Ell, P.J.

1999-01-01

The segmentation of medical images is one of the most important steps in the analysis and quantification of imaging data. However, partial volume artefacts make accurate tissue boundary definition difficult, particularly for images with lower resolution commonly used in nuclear medicine. In single-photon emission tomography (SPET) neuroreceptor studies, areas of specific binding are usually delineated by manually drawing regions of interest (ROIs), a time-consuming and subjective process. This paper applies the technique of fuzzy c-means clustering (FCM) to automatically segment dynamic neuroreceptor SPET images. Fuzzy clustering was tested using a realistic, computer-generated, dynamic SPET phantom derived from segmenting an MR image of an anthropomorphic brain phantom. Also, the utility of applying FCM to real clinical data was assessed by comparison against conventional ROI analysis of iodine-123 iodobenzamide (IBZM) binding to dopamine D 2 /D 3 receptors in the brains of humans. In addition, a further test of the methodology was assessed by applying FCM segmentation to [ 123 I]IDAM images (5-iodo-2-[[2-2-[(dimethylamino)methyl]phenyl]thio] benzyl alcohol) of serotonin transporters in non-human primates. In the simulated dynamic SPET phantom, over a wide range of counts and ratios of specific binding to background, FCM correlated very strongly with the true counts (correlation coefficient r 2 >0.99, P 123 I]IBZM data comparable with manual ROI analysis, with the binding ratios derived from both methods significantly correlated (r 2 =0.83, P<0.0001). Fuzzy clustering is a powerful tool for the automatic, unsupervised segmentation of dynamic neuroreceptor SPET images. Where other automated techniques fail completely, and manual ROI definition would be highly subjective, FCM is capable of segmenting noisy images in a robust and repeatable manner. (orig.)

Deep Learning-Based Iris Segmentation for Iris Recognition in Visible Light Environment

Directory of Open Access Journals (Sweden)

Muhammad Arsalan

2017-11-01

Full Text Available Existing iris recognition systems are heavily dependent on specific conditions, such as the distance of image acquisition and the stop-and-stare environment, which require significant user cooperation. In environments where user cooperation is not guaranteed, prevailing segmentation schemes of the iris region are confronted with many problems, such as heavy occlusion of eyelashes, invalid off-axis rotations, motion blurs, and non-regular reflections in the eye area. In addition, iris recognition based on visible light environment has been investigated to avoid the use of additional near-infrared (NIR light camera and NIR illuminator, which increased the difficulty of segmenting the iris region accurately owing to the environmental noise of visible light. To address these issues; this study proposes a two-stage iris segmentation scheme based on convolutional neural network (CNN; which is capable of accurate iris segmentation in severely noisy environments of iris recognition by visible light camera sensor. In the experiment; the noisy iris challenge evaluation part-II (NICE-II training database (selected from the UBIRIS.v2 database and mobile iris challenge evaluation (MICHE dataset were used. Experimental results showed that our method outperformed the existing segmentation methods.

Investigation of Primary Mirror Segment's Residual Errors for the Thirty Meter Telescope

Science.gov (United States)

Seo, Byoung-Joon; Nissly, Carl; Angeli, George; MacMynowski, Doug; Sigrist, Norbert; Troy, Mitchell; Williams, Eric

2009-01-01

The primary mirror segment aberrations after shape corrections with warping harness have been identified as the single largest error term in the Thirty Meter Telescope (TMT) image quality error budget. In order to better understand the likely errors and how they will impact the telescope performance we have performed detailed simulations. We first generated unwarped primary mirror segment surface shapes that met TMT specifications. Then we used the predicted warping harness influence functions and a Shack-Hartmann wavefront sensor model to determine estimates for the 492 corrected segment surfaces that make up the TMT primary mirror. Surface and control parameters, as well as the number of subapertures were varied to explore the parameter space. The corrected segment shapes were then passed to an optical TMT model built using the Jet Propulsion Laboratory (JPL) developed Modeling and Analysis for Controlled Optical Systems (MACOS) ray-trace simulator. The generated exit pupil wavefront error maps provided RMS wavefront error and image-plane characteristics like the Normalized Point Source Sensitivity (PSSN). The results have been used to optimize the segment shape correction and wavefront sensor designs as well as provide input to the TMT systems engineering error budgets.

Preference segmentation of health care services: the old-fashioneds, value conscious, affluents and professional want-it-alls.

Science.gov (United States)

Woodside, A G; Nielsen, R L; Walters, F; Muller, G D

1988-06-01

The results of a national segmentation study are reported. The findings extend the empirical work of Finn and Lamb and the benefit-seeking conjectures by Kotler and Clarke that consumers with preferences toward specific hospitals can be segmented into a few distinct groups. The groups described in the findings are identified as the value conscious, the affluents, the old-fashioneds, and the professional want-it-alls. Each segment has a unique demographic profile. The substantial importance of doctors' recommendations in influencing hospital choice is supported for all four consumer segments. Suggestions for additional research and hospital marketing strategies are provided.

Specifics of marketing strategy in the segment of high fashion

OpenAIRE

Butigan, Ružica; Grilec Kaurić, Alica; Ujević, Darko

2013-01-01

The success of high fashion designers is not only in a specificity of the products but also in specific and very well executed marketing strategy. Emphasis is placed on the design of very specific marketing program and marketing strategies that must concider all the characteristics of the high fashion market. Therefore, a scientific research problem is defined as follows: although the market of high fashion at first glance does not imply a completely different marketing approach than other fa...

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...

Segmentation of lung fields using Chan-Vese active contour model in chest radiographs

Science.gov (United States)

Sohn, Kiwon

2011-03-01

A CAD tool for chest radiographs consists of several procedures and the very first step is segmentation of lung fields. We develop a novel methodology for segmentation of lung fields in chest radiographs that can satisfy the following two requirements. First, we aim to develop a segmentation method that does not need a training stage with manual estimation of anatomical features in a large training dataset of images. Secondly, for the ease of implementation, it is desirable to apply a well established model that is widely used for various image-partitioning practices. The Chan-Vese active contour model, which is based on Mumford-Shah functional in the level set framework, is applied for segmentation of lung fields. With the use of this model, segmentation of lung fields can be carried out without detailed prior knowledge on the radiographic anatomy of the chest, yet in some chest radiographs, the trachea regions are unfavorably segmented out in addition to the lung field contours. To eliminate artifacts from the trachea, we locate the upper end of the trachea, find a vertical center line of the trachea and delineate it, and then brighten the trachea region to make it less distinctive. The segmentation process is finalized by subsequent morphological operations. We randomly select 30 images from the Japanese Society of Radiological Technology image database to test the proposed methodology and the results are shown. We hope our segmentation technique can help to promote of CAD tools, especially for emerging chest radiographic imaging techniques such as dual energy radiography and chest tomosynthesis.

MITK-based segmentation of co-registered MRI for subject-related regional anesthesia simulation

Science.gov (United States)

Teich, Christian; Liao, Wei; Ullrich, Sebastian; Kuhlen, Torsten; Ntouba, Alexandre; Rossaint, Rolf; Ullisch, Marcus; Deserno, Thomas M.

2008-03-01

With a steadily increasing indication, regional anesthesia is still trained directly on the patient. To develop a virtual reality (VR)-based simulation, a patient model is needed containing several tissues, which have to be extracted from individual magnet resonance imaging (MRI) volume datasets. Due to the given modality and the different characteristics of the single tissues, an adequate segmentation can only be achieved by using a combination of segmentation algorithms. In this paper, we present a framework for creating an individual model from MRI scans of the patient. Our work splits in two parts. At first, an easy-to-use and extensible tool for handling the segmentation task on arbitrary datasets is provided. The key idea is to let the user create a segmentation for the given subject by running different processing steps in a purposive order and store them in a segmentation script for reuse on new datasets. For data handling and visualization, we utilize the Medical Imaging Interaction Toolkit (MITK), which is based on the Visualization Toolkit (VTK) and the Insight Segmentation and Registration Toolkit (ITK). The second part is to find suitable segmentation algorithms and respectively parameters for differentiating the tissues required by the RA simulation. For this purpose, a fuzzy c-means clustering algorithm combined with mathematical morphology operators and a geometric active contour-based approach is chosen. The segmentation process itself aims at operating with minimal user interaction, and the gained model fits the requirements of the simulation. First results are shown for both, male and female MRI of the pelvis.

Design and Optimization of Effective Segmented Thermoelectric Generator for Waste Heat Recovery

DEFF Research Database (Denmark)

Pham, Hoang Ngan

ranges of 300 ‒ 700, and 900 – 1100 K are considered. The obtained results reveals that segmented thermoelectric generator comprising of Bi0.6Sb1.4Te3/Ba8Au5.3Ge40.7/PbTe-SrTe/SiGe as p-leg and either segmented Bi2Te3/PbTe/SiGe or Bi2Te3/Ba0.08La0.05Yb0.04Co4Sb12/La3Te4 as n-leg working in 300 – 1100 K...... been focused on material development, realizing high efficient thermoelectric generators from such well-developed materials is still limited. Moreover, no single thermoelectric material could withstand the wide temperature range required to boost efficiency of TEGs. By segmentation of different TE...... materials which operate optimally in each temperature range, this study aims at developing high performance segmented TEGs for medium-high (450 – 850 K) temperature application. The research is focused on the challenges in joining and minimizing the contact resistances between different TE materials...

SpArcFiRe: Scalable automated detection of spiral galaxy arm segments

International Nuclear Information System (INIS)

Davis, Darren R.; Hayes, Wayne B.

2014-01-01

Given an approximately centered image of a spiral galaxy, we describe an entirely automated method that finds, centers, and sizes the galaxy (possibly masking nearby stars and other objects if necessary in order to isolate the galaxy itself) and then automatically extracts structural information about the spiral arms. For each arm segment found, we list the pixels in that segment, allowing image analysis on a per-arm-segment basis. We also perform a least-squares fit of a logarithmic spiral arc to the pixels in that segment, giving per-arc parameters, such as the pitch angle, arm segment length, location, etc. The algorithm takes about one minute per galaxies, and can easily be scaled using parallelism. We have run it on all ∼644,000 Sloan objects that are larger than 40 pixels across and classified as 'galaxies'. We find a very good correlation between our quantitative description of a spiral structure and the qualitative description provided by Galaxy Zoo humans. Our objective, quantitative measures of structure demonstrate the difficulty in defining exactly what constitutes a spiral 'arm', leading us to prefer the term 'arm segment'. We find that pitch angle often varies significantly segment-to-segment in a single spiral galaxy, making it difficult to define the pitch angle for a single galaxy. We demonstrate how our new database of arm segments can be queried to find galaxies satisfying specific quantitative visual criteria. For example, even though our code does not explicitly find rings, a good surrogate is to look for galaxies having one long, low-pitch-angle arm—which is how our code views ring galaxies. SpArcFiRe is available at http://sparcfire.ics.uci.edu.

Imaging QRS complex and ST segment in myocardial infarction

DEFF Research Database (Denmark)

Bacharova, Ljuba; Bang, Lia E; Szathmary, Vavrinec

2014-01-01

BACKGROUND: Acute myocardial infarction creates regions of altered electrical properties of myocardium resulting in typical QRS patterns (pathological Q waves) and ST segment deviations observed in leads related to the MI location. The aim of this study was to present a graphical method for imaging...... the changes in the sequence of depolarization and the ST segment deviations in myocardial infarction using the Dipolar ElectroCARdioTOpography (DECARTO) method. MATERIAL AND METHODS: Simulated ECG data corresponding to intramural, electrically inactive areas encircled by transmural areas with slowed impulse...... propagation velocity in anteroseptal and inferior locations were used for imaging the altered sequence of depolarization and the ST vector. The ECGs were transformed to areas projected on the image surface so as to image the process of ventricular depolarization based on the orientation and magnitude...

Retinal Vessels Segmentation Techniques and Algorithms: A Survey

Directory of Open Access Journals (Sweden)

Jasem Almotiri

2018-01-01

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

Ultrasound image-based thyroid nodule automatic segmentation using convolutional neural networks.

Science.gov (United States)

Ma, Jinlian; Wu, Fa; Jiang, Tian'an; Zhao, Qiyu; Kong, Dexing

2017-11-01

Delineation of thyroid nodule boundaries from ultrasound images plays an important role in calculation of clinical indices and diagnosis of thyroid diseases. However, it is challenging for accurate and automatic segmentation of thyroid nodules because of their heterogeneous appearance and components similar to the background. In this study, we employ a deep convolutional neural network (CNN) to automatically segment thyroid nodules from ultrasound images. Our CNN-based method formulates a thyroid nodule segmentation problem as a patch classification task, where the relationship among patches is ignored. Specifically, the CNN used image patches from images of normal thyroids and thyroid nodules as inputs and then generated the segmentation probability maps as outputs. A multi-view strategy is used to improve the performance of the CNN-based model. Additionally, we compared the performance of our approach with that of the commonly used segmentation methods on the same dataset. The experimental results suggest that our proposed method outperforms prior methods on thyroid nodule segmentation. Moreover, the results show that the CNN-based model is able to delineate multiple nodules in thyroid ultrasound images accurately and effectively. In detail, our CNN-based model can achieve an average of the overlap metric, dice ratio, true positive rate, false positive rate, and modified Hausdorff distance as [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] on overall folds, respectively. Our proposed method is fully automatic without any user interaction. Quantitative results also indicate that our method is so efficient and accurate that it can be good enough to replace the time-consuming and tedious manual segmentation approach, demonstrating the potential clinical applications.

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...

A Dataset and Benchmarks for Segmentation and Recognition of Gestures in Robotic Surgery.

Science.gov (United States)

Ahmidi, Narges; Tao, Lingling; Sefati, Shahin; Gao, Yixin; Lea, Colin; Haro, Benjamin Bejar; Zappella, Luca; Khudanpur, Sanjeev; Vidal, Rene; Hager, Gregory D

2017-09-01

State-of-the-art techniques for surgical data analysis report promising results for automated skill assessment and action recognition. The contributions of many of these techniques, however, are limited to study-specific data and validation metrics, making assessment of progress across the field extremely challenging. In this paper, we address two major problems for surgical data analysis: First, lack of uniform-shared datasets and benchmarks, and second, lack of consistent validation processes. We address the former by presenting the JHU-ISI Gesture and Skill Assessment Working Set (JIGSAWS), a public dataset that we have created to support comparative research benchmarking. JIGSAWS contains synchronized video and kinematic data from multiple performances of robotic surgical tasks by operators of varying skill. We address the latter by presenting a well-documented evaluation methodology and reporting results for six techniques for automated segmentation and classification of time-series data on JIGSAWS. These techniques comprise four temporal approaches for joint segmentation and classification: hidden Markov model, sparse hidden Markov model (HMM), Markov semi-Markov conditional random field, and skip-chain conditional random field; and two feature-based ones that aim to classify fixed segments: bag of spatiotemporal features and linear dynamical systems. Most methods recognize gesture activities with approximately 80% overall accuracy under both leave-one-super-trial-out and leave-one-user-out cross-validation settings. Current methods show promising results on this shared dataset, but room for significant progress remains, particularly for consistent prediction of gesture activities across different surgeons. The results reported in this paper provide the first systematic and uniform evaluation of surgical activity recognition techniques on the benchmark database.

Event segmentation and seven types of narrative discontinuity in popular movies.

Science.gov (United States)

Cutting, James E

2014-06-01

Using a sample of 24 movies I investigate narrative shifts in location, characters, and time frame that do and do not align with viewer segmentations of events (scenes and subscenes) in popular movies. Taken independently these dimensions create eight categories, seven of change and one of nonchange. Data show that the more dimensions that are changed the more viewers agree on their segmentations, although the nonadditive variations across the seven change types are large and systematic. Dissolves aid segmentation but over the last 70 years they have been used less and less by filmmakers, except for two infrequent shift types. Locations and characters are strongly yoked, jointly accounting for most narrative shifts. There are also interactions of shift types over the 70-year span and across genres, as well as differences that affect the scale of the establishing shot in a new scene. In addition, several aspects of the narratives of individual movies affect the distributions of shift types. Together these results suggest that there are at least four different signatures of narrative shifts to be found in popular movies - general patterns across time, patterns of historical change, genre-specific patterns, and film-specific patterns. Copyright © 2014 The Author. Published by Elsevier B.V. All rights reserved.

Quality Assurance of Serial 3D Image Registration, Fusion, and Segmentation

International Nuclear Information System (INIS)

Sharpe, Michael; Brock, Kristy K.

2008-01-01

Radiotherapy relies on images to plan, guide, and assess treatment. Image registration, fusion, and segmentation are integral to these processes; specifically for aiding anatomic delineation, assessing organ motion, and aligning targets with treatment beams in image-guided radiation therapy (IGRT). Future developments in image registration will also improve estimations of the actual dose delivered and quantitative assessment in patient follow-up exams. This article summarizes common and emerging technologies and reviews the role of image registration, fusion, and segmentation in radiotherapy processes. The current quality assurance practices are summarized, and implications for clinical procedures are discussed

Delphi definition of the EADC-ADNI Harmonized Protocol for hippocampal segmentation on magnetic resonance.

Science.gov (United States)

Boccardi, Marina; Bocchetta, Martina; Apostolova, Liana G; Barnes, Josephine; Bartzokis, George; Corbetta, Gabriele; DeCarli, Charles; deToledo-Morrell, Leyla; Firbank, Michael; Ganzola, Rossana; Gerritsen, Lotte; Henneman, Wouter; Killiany, Ronald J; Malykhin, Nikolai; Pasqualetti, Patrizio; Pruessner, Jens C; Redolfi, Alberto; Robitaille, Nicolas; Soininen, Hilkka; Tolomeo, Daniele; Wang, Lei; Watson, Craig; Wolf, Henrike; Duvernoy, Henri; Duchesne, Simon; Jack, Clifford R; Frisoni, Giovanni B

2015-02-01

This study aimed to have international experts converge on a harmonized definition of whole hippocampus boundaries and segmentation procedures, to define standard operating procedures for magnetic resonance (MR)-based manual hippocampal segmentation. The panel received a questionnaire regarding whole hippocampus boundaries and segmentation procedures. Quantitative information was supplied to allow evidence-based answers. A recursive and anonymous Delphi procedure was used to achieve convergence. Significance of agreement among panelists was assessed by exact probability on Fisher's and binomial tests. Agreement was significant on the inclusion of alveus/fimbria (P = .021), whole hippocampal tail (P = .013), medial border of the body according to visible morphology (P = .0006), and on this combined set of features (P = .001). This definition captures 100% of hippocampal tissue, 100% of Alzheimer's disease-related atrophy, and demonstrated good reliability on preliminary intrarater (0.98) and inter-rater (0.94) estimates. Consensus was achieved among international experts with respect to hippocampal segmentation using MR resulting in a harmonized segmentation protocol. Copyright © 2015 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Design and experimental investigation of a Multi-segment plate concentrated photovoltaic solar energy system

International Nuclear Information System (INIS)

Wang, Gang; Chen, Zeshao; Hu, Peng

2017-01-01

Highlights: • A multi-segment plate concentrated photovoltaic solar energy system was proposed. • A prototype of this new concentrator was developed for experimental investigation. • Experimental investigation results showed a good concentrating uniformity. - Abstract: Solar energy is one of the most promising renewable energies and meaningful for the sustainable development of energy source. A multi-segment plate concentrated photovoltaic (CPV) solar power system was proposed in this paper, the design principle of the multi-segment plate concentrator of this solar power system was given, which could provide uniform solar radiation flux density distribution on solar cells. A prototype of this multi-segment plate CPV solar power system was developed for the experimental study, aiming at the investigations of solar radiation flux density distribution and PV performances under this concentrator design. The experimental results showed that the solar radiation flux density distribution provided by the multi-segment plate concentrator had a good uniformity, and the number and temperature of solar cells both influence the photoelectric transformation efficiency of the CPV solar power system.

USABILITY TESTING OF JAPANESE CAPTIONS SEGMENTATION SYSTEM TO SCAFFOLD BEGINNERS TO COMPREHEND JAPANESE VIDEOS

Directory of Open Access Journals (Sweden)

Ya-Fei Yang

2013-06-01

Full Text Available A major learning difficulty of Japanese foreign language (JFL learners is the complex composition of two syllabaries, hiragana and katakana, and kanji characters adopted from logographic Chinese ones. As the number of Japanese language learners increases, computer-assisted Japanese language education gradually gains more attention. This study aimed to adopt a Japanese word segmentation system to help JFL learners overcome literacy problems. This study adopted MeCab, a Japanese morphological analyzer and part-of-speech (POS tagger, to segment Japanese texts into separate morphemes by adding spaces and to attach POS tags to each morpheme for beginners. The participants were asked to participate in three experimental activities involvingwatching two Japanese videos with general or segmented Japanese captions and complete the Nielsen’s Attributes of Usability (NAU survey and the After Scenario Questionnaire (ASQ to evaluate the usability of the learning activities. The results of the system evaluation showed that the videos with the segmented captions could increase the participants’ learning motivation and willingness to adopt the word segmentation system to learn Japanese.

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...

Functional measurements based on feature tracking of cine magnetic resonance images identify left ventricular segments with myocardial scar

Directory of Open Access Journals (Sweden)

Nylander Eva

2009-11-01

Full Text Available Abstract Background The aim of the study was to perform a feature tracking analysis on cine magnetic resonance (MR images to elucidate if functional measurements of the motion of the left ventricular wall may detect scar defined with gadolinium enhanced MR. Myocardial contraction can be measured in terms of the velocity, displacement and local deformation (strain of a particular myocardial segment. Contraction of the myocardial wall will be reduced in the presence of scar and as a consequence of reduced myocardial blood flow. Methods Thirty patients (3 women and 27 men were selected based on the presence or absence of extensive scar in the anteroseptal area of the left ventricle. The patients were investigated in stable clinical condition, 4-8 weeks post ST-elevation myocardial infarction treated with percutaneous coronary intervention. Seventeen had a scar area >75% in at least one anteroseptal segment (scar and thirteen had scar area Results In the scar patients, segments with scar showed lower functional measurements than remote segments. Radial measurements of velocity, displacement and strain performed better in terms of receiver-operator-characteristic curves (ROC than the corresponding longitudinal measurements. The best area-under-curve was for radial strain, 0.89, where a cut-off value of 38.8% had 80% sensitivity and 86% specificity for the detection of a segment with scar area >50%. As a percentage of the mean, intraobserver variability was 16-14-26% for radial measurements of displacement-velocity-strain and corresponding interobserver variability was 13-12-18%. Conclusion Feature tracking analysis of cine-MR displays velocity, displacement and strain in the radial and longitudinal direction and may be used for the detection of transmural scar. The accuracy and repeatability of the radial functional measurements is satisfactory and global measures agree.

Evaluation of soft segment modeling on a context independent phoneme classification system

International Nuclear Information System (INIS)

Razzazi, F.; Sayadiyan, A.

2007-01-01

The geometric distribution of states duration is one of the main performance limiting assumptions of hidden Markov modeling of speech signals. Stochastic segment models, generally, and segmental HMM, specifically overcome this deficiency partly at the cost of more complexity in both training and recognition phases. In addition to this assumption, the gradual temporal changes of speech statistics has not been modeled in HMM. In this paper, a new duration modeling approach is presented. The main idea of the model is to consider the effect of adjacent segments on the probability density function estimation and evaluation of each acoustic segment. This idea not only makes the model robust against segmentation errors, but also it models gradual change from one segment to the next one with a minimum set of parameters. The proposed idea is analytically formulated and tested on a TIMIT based context independent phenomena classification system. During the test procedure, the phoneme classification of different phoneme classes was performed by applying various proposed recognition algorithms. The system was optimized and the results have been compared with a continuous density hidden Markov model (CDHMM) with similar computational complexity. The results show 8-10% improvement in phoneme recognition rate in comparison with standard continuous density hidden Markov model. This indicates improved compatibility of the proposed model with the speech nature. (author)

Segmental and dynamic intensity-modulated radiotherapy delivery techniques for micro-multileaf collimator

International Nuclear Information System (INIS)

Agazaryan, Nzhde; Solberg, Timothy D.

2003-01-01

A leaf sequencing algorithm has been implemented to deliver segmental and dynamic multileaf collimated intensity-modulated radiotherapy (SMLC-IMRT and DMLC-IMRT, respectively) using a linear accelerator equipped with a micro-multileaf collimator (mMLC). The implementation extends a previously published algorithm for the SMLC-IMRT to include the dynamic MLC-IMRT method and several dosimetric considerations. The algorithm has been extended to account for the transmitted radiation and minimize the leakage between opposing and neighboring leaves. The underdosage problem associated with the tongue-and-groove design of the MLC is significantly reduced by synchronizing the MLC leaf movements. The workings of the leaf sequencing parameters have been investigated and the results of the planar dosimetric investigations show that the sequencing parameters affect the measured dose distributions as intended. Investigations of clinical cases suggest that SMLC and DMLC delivery methods produce comparable results with leaf sequences obtained by root-mean-square (RMS) errors specification of 1.5% and lower, approximately corresponding to 20 or more segments. For SMLC-IMRT, there is little to be gained by using an RMS error specification smaller than 2%, approximately corresponding to 15 segments; however, more segments directly translate to longer treatment time and more strain on the MLC. The implemented leaf synchronization method does not increase the required monitor units while it reduces the measured TG underdoses from a maximum of 12% to a maximum of 3% observed with single field measurements of representative clinical cases studied

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...

Segmental torso masses in adolescent idiopathic scoliosis.

Science.gov (United States)

Keenan, Bethany E; Izatt, Maree T; Askin, Geoffrey N; Labrom, Robert D; Pettet, Graeme J; Pearcy, Mark J; Adam, Clayton J

2014-08-01

Adolescent idiopathic scoliosis is the most common type of spinal deformity whose aetiology remains unclear. Studies suggest that gravitational forces in the standing position play an important role in scoliosis progression, therefore anthropometric data is required to develop biomechanical models of the deformity. Few studies have analysed the trunk by vertebral level and none have performed investigations of the scoliotic trunk. The aim of this study was to determine the centroid, thickness, volume and estimated mass, for sections of the scoliotic trunk. Existing low-dose CT scans were used to estimate vertebral level-by-level torso masses for 20 female adolescent idiopathic scoliosis patients. ImageJ processing software was used to analyse the CT images and enable estimation of the segmental torso mass corresponding to each vertebral level. The patients' mean age was 15.0 (SD 2.7) years with mean major Cobb angle of 52 (SD 5.9)° and mean patient weight of 58.2 (SD 11.6) kg. The magnitude of torso segment mass corresponding to each vertebral level increased by 150% from 0.6kg at T1 to 1.5kg at L5. Similarly, segmental thickness from T1-L5 increased inferiorly from a mean 18.5 (SD 2.2) mm at T1 to 32.8 (SD 3.4) mm at L5. The mean total trunk mass, as a percentage of total body mass, was 27.8 (SD 0.5) % which was close to values reported in previous literature. This study provides new anthropometric reference data on segmental (vertebral level-by-level) torso mass in adolescent idiopathic scoliosis patients, useful for biomechanical models of scoliosis progression and treatment. Copyright © 2014 Elsevier Ltd. All rights reserved.

Patient-Specific Computational Modeling

CERN Document Server

Peña, Estefanía

2012-01-01

This book addresses patient-specific modeling. It integrates computational modeling, experimental procedures, imagine clinical segmentation and mesh generation with the finite element method (FEM) to solve problems in computational biomedicine and bioengineering. Specific areas of interest include cardiovascular problems, ocular and muscular systems and soft tissue modeling. Patient-specific modeling has been the subject of serious research over the last seven years and interest in the area is continually growing and this area is expected to further develop in the near future.

Multi-scale image segmentation method with visual saliency constraints and its application

Science.gov (United States)

Chen, Yan; Yu, Jie; Sun, Kaimin

2018-03-01

Object-based image analysis method has many advantages over pixel-based methods, so it is one of the current research hotspots. It is very important to get the image objects by multi-scale image segmentation in order to carry out object-based image analysis. The current popular image segmentation methods mainly share the bottom-up segmentation principle, which is simple to realize and the object boundaries obtained are accurate. However, the macro statistical characteristics of the image areas are difficult to be taken into account, and fragmented segmentation (or over-segmentation) results are difficult to avoid. In addition, when it comes to information extraction, target recognition and other applications, image targets are not equally important, i.e., some specific targets or target groups with particular features worth more attention than the others. To avoid the problem of over-segmentation and highlight the targets of interest, this paper proposes a multi-scale image segmentation method with visually saliency graph constraints. Visual saliency theory and the typical feature extraction method are adopted to obtain the visual saliency information, especially the macroscopic information to be analyzed. The visual saliency information is used as a distribution map of homogeneity weight, where each pixel is given a weight. This weight acts as one of the merging constraints in the multi- scale image segmentation. As a result, pixels that macroscopically belong to the same object but are locally different can be more likely assigned to one same object. In addition, due to the constraint of visual saliency model, the constraint ability over local-macroscopic characteristics can be well controlled during the segmentation process based on different objects. These controls will improve the completeness of visually saliency areas in the segmentation results while diluting the controlling effect for non- saliency background areas. Experiments show that this method works

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)

Fast CSF MRI for brain segmentation; Cross-validation by comparison with 3D T1-based brain segmentation methods.

Science.gov (United States)

van der Kleij, Lisa A; de Bresser, Jeroen; Hendrikse, Jeroen; Siero, Jeroen C W; Petersen, Esben T; De Vis, Jill B

2018-01-01

In previous work we have developed a fast sequence that focusses on cerebrospinal fluid (CSF) based on the long T2 of CSF. By processing the data obtained with this CSF MRI sequence, brain parenchymal volume (BPV) and intracranial volume (ICV) can be automatically obtained. The aim of this study was to assess the precision of the BPV and ICV measurements of the CSF MRI sequence and to validate the CSF MRI sequence by comparison with 3D T1-based brain segmentation methods. Ten healthy volunteers (2 females; median age 28 years) were scanned (3T MRI) twice with repositioning in between. The scan protocol consisted of a low resolution (LR) CSF sequence (0:57min), a high resolution (HR) CSF sequence (3:21min) and a 3D T1-weighted sequence (6:47min). Data of the HR 3D-T1-weighted images were downsampled to obtain LR T1-weighted images (reconstructed imaging time: 1:59 min). Data of the CSF MRI sequences was automatically segmented using in-house software. The 3D T1-weighted images were segmented using FSL (5.0), SPM12 and FreeSurfer (5.3.0). The mean absolute differences for BPV and ICV between the first and second scan for CSF LR (BPV/ICV: 12±9/7±4cc) and CSF HR (5±5/4±2cc) were comparable to FSL HR (9±11/19±23cc), FSL LR (7±4, 6±5cc), FreeSurfer HR (5±3/14±8cc), FreeSurfer LR (9±8, 12±10cc), and SPM HR (5±3/4±7cc), and SPM LR (5±4, 5±3cc). The correlation between the measured volumes of the CSF sequences and that measured by FSL, FreeSurfer and SPM HR and LR was very good (all Pearson's correlation coefficients >0.83, R2 .67-.97). The results from the downsampled data and the high-resolution data were similar. Both CSF MRI sequences have a precision comparable to, and a very good correlation with established 3D T1-based automated segmentations methods for the segmentation of BPV and ICV. However, the short imaging time of the fast CSF MRI sequence is superior to the 3D T1 sequence on which segmentation with established methods is performed.

Proposition Analysis of Fixed Broadband Services Based on Product Segmentation And Purchasing Power of Urban Society

Directory of Open Access Journals (Sweden)

Triyono Budi Santoso

2016-03-01

Full Text Available Tight competition in the broadband industry has forced the provider to have a good product propotition and strategy in the market, including market segmentation and type of services delivered based on customer’s expextation and intention to buy. This research aims to make a product proposition based on two major criteries in fixed broadband service, which are speed and price of the product, by looking into the competition in existing market (competitor’s product. As many players in Indonesia have created very tight situation, the will be launched product should have an attractive matter or differentiation in order to compete and get a “buy in” of the customer. In the research, some analysis was conducted across all the propositions by spreading questionnaires to respondents in urban area especially in Jakarta and Bandung, thus the provider can create product with an appropriate specifications to answer the needs of customers on their affordable price to buy. Some close-ended questions in the questionairres were scaled and performed by basic statistical approach methods. The result shows that product with affordable price is still become the choice of respondents in each segment (low, medium and high income. Price list per speed which is fitted to any segments is also suggested in this research. The result of the research can also be used to develop the product as a differentiation to be the choices and preferencesof customers.

Understanding heterogeneity among elderly consumers: an evaluation of segmentation approaches in the functional food market.

Science.gov (United States)

van der Zanden, Lotte D T; van Kleef, Ellen; de Wijk, René A; van Trijp, Hans C M

2014-06-01

It is beneficial for both the public health community and the food industry to meet nutritional needs of elderly consumers through product formats that they want. The heterogeneity of the elderly market poses a challenge, however, and calls for market segmentation. Although many researchers have proposed ways to segment the elderly consumer population, the elderly food market has received surprisingly little attention in this respect. Therefore, the present paper reviewed eight potential segmentation bases on their appropriateness in the context of functional foods aimed at the elderly: cognitive age, life course, time perspective, demographics, general food beliefs, food choice motives, product attributes and benefits sought, and past purchase. Each of the segmentation bases had strengths as well as weaknesses regarding seven evaluation criteria. Given that both product design and communication are useful tools to increase the appeal of functional foods, we argue that elderly consumers in this market may best be segmented using a preference-based segmentation base that is predictive of behaviour (for example, attributes and benefits sought), combined with a characteristics-based segmentation base that describes consumer characteristics (for example, demographics). In the end, the effectiveness of (combinations of) segmentation bases for elderly consumers in the functional food market remains an empirical matter. We hope that the present review stimulates further empirical research that substantiates the ideas presented in this paper.

Skipping Posterior Dynamic Transpedicular Stabilization for Distant Segment Degenerative Disease

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Bilgehan Solmaz

2012-01-01

Full Text Available Objective. To date, there is still no consensus on the treatment of spinal degenerative disease. Current surgical techniques to manage painful spinal disorders are imperfect. In this paper, we aimed to evaluate the prospective results of posterior transpedicular dynamic stabilization, a novel surgical approach that skips the segments that do not produce pain. This technique has been proven biomechanically and radiologically in spinal degenerative diseases. Methods. A prospective study of 18 patients averaging 54.94 years of age with distant spinal segment degenerative disease. Indications consisted of degenerative disc disease (57%, herniated nucleus pulposus (50%, spinal stenosis (14.28%, degenerative spondylolisthesis (14.28%, and foraminal stenosis (7.1%. The Oswestry Low-Back Pain Disability Questionnaire and visual analog scale (VAS for pain were recorded preoperatively and at the third and twelfth postoperative months. Results. Both the Oswestry and VAS scores showed significant improvement postoperatively (P<0.05. We observed complications in one patient who had spinal epidural hematoma. Conclusion. We recommend skipping posterior transpedicular dynamic stabilization for surgical treatment of distant segment spinal degenerative disease.

NEW APPROACHES TO CUSTOMER BASE SEGMENTATION FOR SMALL AND MEDIUM-SIZED ENTERPRISES

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Meleancă Raluca-Cristina

2012-12-01

Full Text Available The primary purpose of this paper is to explore current praxis and theory related to customer segmentation and to offer an approach which is best suited for small and medium sized enterprises. The proposed solution is the result of an exploratory research aiming to recognize the main variables which influence the practice of segmenting the customer base and to study the most applied alternatives available for all types of enterprises. The research has been performed by studying a large set of secondary data, scientific literature and case studies regarding smaller companies from the European Union. The result of the research consists in an original approach to customer base segmentation, which combines aspects belonging to different well spread practices and applies them to the specific needs of a small or medium company, which typically has limited marketing resources in general and targeted marketing resources in particular. The significance of the proposed customer base segmentation approach lies in the fact that, even though smaller enterprises are in most economies the greatest in number compared to large companies, most of the literature on targeting practices has focused primarily on big companies dealing with a very large clientele, while the case of the smaller companies has been to some extent unfairly neglected. Targeted marketing is becoming more and more important for all types of companies nowadays, as a result of technology advances which make targeted communication easier and less expensive than in the past and also due to the fact that broad-based media have decreased their impact over the years. For a very large proportion of smaller companies, directing their marketing budgets towards targeted campaigns is a clever initiative, as broad based approaches are in many cases less effective and much more expensive. Targeted marketing stratagems are generally related to high tech domains such as artificial intelligence, data mining

Integration of sparse multi-modality representation and geometrical constraint for isointense infant brain segmentation.

Science.gov (United States)

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

2013-01-01

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

Coronary Arteries Segmentation Based on the 3D Discrete Wavelet Transform and 3D Neutrosophic Transform

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Shuo-Tsung Chen

2015-01-01

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

Label fusion based brain MR image segmentation via a latent selective model

Science.gov (United States)

Liu, Gang; Guo, Xiantang; Zhu, Kai; Liao, Hengxu

2018-04-01

Multi-atlas segmentation is an effective approach and increasingly popular for automatically labeling objects of interest in medical images. Recently, segmentation methods based on generative models and patch-based techniques have become the two principal branches of label fusion. However, these generative models and patch-based techniques are only loosely related, and the requirement for higher accuracy, faster segmentation, and robustness is always a great challenge. In this paper, we propose novel algorithm that combines the two branches using global weighted fusion strategy based on a patch latent selective model to perform segmentation of specific anatomical structures for human brain magnetic resonance (MR) images. In establishing this probabilistic model of label fusion between the target patch and patch dictionary, we explored the Kronecker delta function in the label prior, which is more suitable than other models, and designed a latent selective model as a membership prior to determine from which training patch the intensity and label of the target patch are generated at each spatial location. Because the image background is an equally important factor for segmentation, it is analyzed in label fusion procedure and we regard it as an isolated label to keep the same privilege between the background and the regions of interest. During label fusion with the global weighted fusion scheme, we use Bayesian inference and expectation maximization algorithm to estimate the labels of the target scan to produce the segmentation map. Experimental results indicate that the proposed algorithm is more accurate and robust than the other segmentation methods.

Hydrophobic coating of microfluidic chips structured by SU-8 polymer for segmented flow operation

International Nuclear Information System (INIS)

Schumacher, J T; Grodrian, A; Metze, J; Kremin, C; Hoffmann, M

2008-01-01

We present a hydrophobization procedure for SU-8-based microfluidic chips on borofloat substrates. Different layouts of gold electrodes passivated by the polymer have been investigated. The chips are used for segmented flow in a two-fluid mode that requires a distinct hydrophobicity of the channel walls which is generated by the use of specific silane. In this paper we describe the production and silanization of the chips and demonstrate segmented flow operation

Training labels for hippocampal segmentation based on the EADC-ADNI harmonized hippocampal protocol.

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Boccardi, Marina; Bocchetta, Martina; Morency, Félix C; Collins, D Louis; Nishikawa, Masami; Ganzola, Rossana; Grothe, Michel J; Wolf, Dominik; Redolfi, Alberto; Pievani, Michela; Antelmi, Luigi; Fellgiebel, Andreas; Matsuda, Hiroshi; Teipel, Stefan; Duchesne, Simon; Jack, Clifford R; Frisoni, Giovanni B

2015-02-01

The European Alzheimer's Disease Consortium and Alzheimer's Disease Neuroimaging Initiative (ADNI) Harmonized Protocol (HarP) is a Delphi definition of manual hippocampal segmentation from magnetic resonance imaging (MRI) that can be used as the standard of truth to train new tracers, and to validate automated segmentation algorithms. Training requires large and representative data sets of segmented hippocampi. This work aims to produce a set of HarP labels for the proper training and certification of tracers and algorithms. Sixty-eight 1.5 T and 67 3 T volumetric structural ADNI scans from different subjects, balanced by age, medial temporal atrophy, and scanner manufacturer, were segmented by five qualified HarP tracers whose absolute interrater intraclass correlation coefficients were 0.953 and 0.975 (left and right). Labels were validated as HarP compliant through centralized quality check and correction. Hippocampal volumes (mm(3)) were as follows: controls: left = 3060 (standard deviation [SD], 502), right = 3120 (SD, 897); mild cognitive impairment (MCI): left = 2596 (SD, 447), right = 2686 (SD, 473); and Alzheimer's disease (AD): left = 2301 (SD, 492), right = 2445 (SD, 525). Volumes significantly correlated with atrophy severity at Scheltens' scale (Spearman's ρ = segmentation algorithms. The publicly released labels will allow the widespread implementation of the standard segmentation protocol. Copyright © 2015 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

The strategic marketing planning – General Framework for Customer Segmentation

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Alina Elena OPRESCU

2014-03-01

Full Text Available Any approach that involves the use of strategic resources of an organisation requires a responsible approach, a behaviour that enables it to properly integrate itself into the dynamic of the business environment. This articles addresses in a synthetic manner, the issues of specific integration efforts for customers’ segmentation in the strategic marketing planning. The essential activity for any organisation wishing to optimise its response to the market, the customer segmentation will fully benefit from the framework provided by the strategic marketing planning. Being a sequential process, it not only allows time optimisation of the entire marketing activity but it also leads to accuracy of the strategic planning and its stages.

Mild toxic anterior segment syndrome mimicking delayed onset toxic anterior segment syndrome after cataract surgery

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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

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Peni Agustin Tjahyaningtijas, Hapsari

2018-04-01

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

Colour application on mammography image segmentation

Science.gov (United States)

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

2017-09-01

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

Topology optimization for design of segmented permanent magnet arrays with ferromagnetic materials

Science.gov (United States)

Lee, Jaewook; Yoon, Minho; Nomura, Tsuyoshi; Dede, Ercan M.

2018-03-01

This paper presents multi-material topology optimization for the co-design of permanent magnet segments and iron material. Specifically, a co-design methodology is proposed to find an optimal border of permanent magnet segments, a pattern of magnetization directions, and an iron shape. A material interpolation scheme is proposed for material property representation among air, permanent magnet, and iron materials. In this scheme, the permanent magnet strength and permeability are controlled by density design variables, and permanent magnet magnetization directions are controlled by angle design variables. In addition, a scheme to penalize intermediate magnetization direction is proposed to achieve segmented permanent magnet arrays with discrete magnetization directions. In this scheme, permanent magnet strength is controlled depending on magnetization direction, and consequently the final permanent magnet design converges into permanent magnet segments having target discrete directions. To validate the effectiveness of the proposed approach, three design examples are provided. The examples include the design of a dipole Halbach cylinder, magnetic system with arbitrarily-shaped cavity, and multi-objective problem resembling a magnetic refrigeration device.

Segmentation-less Digital Rock Physics

Science.gov (United States)

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

2017-12-01

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

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

Prediction of Optimal Daily Step Count Achievement from Segmented School Physical Activity

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Ryan D. Burns

2015-01-01

Full Text Available Optimizing physical activity in childhood is needed for prevention of disease and for healthy social and psychological development. There is limited research examining how segmented school physical activity patterns relate to a child achieving optimal physical activity levels. The purpose of this study was to examine the predictive relationship between step counts during specific school segments and achieving optimal school (6,000 steps/day and daily (12,000 steps/day step counts in children. Participants included 1,714 school-aged children (mean age = 9.7±1.0 years recruited across six elementary schools. Physical activity was monitored for one week using pedometers. Generalized linear mixed effects models were used to determine the adjusted odds ratios (ORs of achieving both school and daily step count standards for every 1,000 steps taken during each school segment. The school segment that related in strongest way to a student achieving 6,000 steps during school hours was afternoon recess (OR = 40.03; P<0.001 and for achieving 12,000 steps for the entire day was lunch recess (OR = 5.03; P<0.001. School segments including lunch and afternoon recess play an important role for optimizing daily physical activity in children.

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

Hox genes require homothorax and extradenticle for body wall identity specification but not for appendage identity specification during metamorphosis of Tribolium castaneum.

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Smith, Frank W; Jockusch, Elizabeth L

2014-11-01

The establishment of segment identity is a key developmental process that allows for divergence along the anteroposterior body axis in arthropods. In Drosophila, the identity of a segment is determined by the complement of Hox genes it expresses. In many contexts, Hox transcription factors require the protein products of extradenticle (exd) and homothorax (hth) as cofactors to perform their identity specification functions. In holometabolous insects, segment identity may be specified twice, during embryogenesis and metamorphosis. To glean insight into the relationship between embryonic and metamorphic segmental identity specification, we have compared these processes in the flour beetle Tribolium castaneum, which develops ventral appendages during embryogenesis that later metamorphose into adult appendages with distinct morphologies. At metamorphosis, comparisons of RNAi phenotypes indicate that Hox genes function jointly with Tc-hth and Tc-exd to specify several region-specific aspects of the adult body wall. On the other hand, Hox genes specify appendage identities along the anteroposterior axis independently of Tc-hth/Tc-exd and Tc-hth/Tc-exd specify proximal vs. distal identity within appendages independently of Hox genes during this stage. During embryogenesis, Tc-hth and Tc-exd play a broad role in the segmentation process and are required for specification of body wall identities in the thorax; however, contrasting with results from other species, we did not obtain homeotic transformations of embryonic appendages in response to Tc-hth or Tc-exd RNAi. In general, the homeotic effects of interference with the function of Hox genes and Tc-hth/Tc-exd during metamorphosis did not match predictions based on embryonic roles of these genes. Comparing metamorphic patterning in T. castaneum to embryonic and post-embryonic development in hemimetabolous insects suggests that holometabolous metamorphosis combines patterning processes of both late embryogenesis and

Effects of Strike-Slip Fault Segmentation on Earthquake Energy and Seismic Hazard

Science.gov (United States)

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

2014-12-01

for further slip and for subsequent earthquakes. This suite of models reveals that efficiency may be a useful tool for determining the relative seismic hazard of different segmented fault systems, while accounting for coseismic damage zone production is critical in assessing fault interactions and the associated energy budgets of specific systems.

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)

Consumer segmentation based on food-related lifestyles and analysis of rabbit meat consumption

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J. Buitrago-Vera

2016-09-01

Full Text Available Market segmentation divides the market into small groups of consumers who share similar characteristics. As all consumers within the same group have a common profile, marketing strategies can be adapted to target a specific type of consumer. Owing to the rapid changes in today’s society, consumer lifestyle has become the ideal criterion for market segmentation. In this study, we employed the food-related lifestyle model, which scholars have shown to be suitable and valid in several countries. Using data from a survey (with 3.53% error, we segmented the Spanish food market based on consumers’ food-related lifestyles. For each segment, we identified the consumer profile and analysed consumers’ consumption of rabbit meat. Factor analysis and cluster analysis yielded 4 segments: (i ‘Unconcerned’ (36.8% of the sample mainly consists of male consumers. Consumers in this segment value neither the freshness nor the price/quality ratio of their food items and consume rabbit meat rarely (39.4% or sporadically (29.3%. (ii ‘Cooks’ (18.4% predominantly consists of middle-aged women. Consumers in this segment are highly demanding and critical of the quality of food products. They like cooking and are regular consumers of rabbit meat (40.6%. (iii ‘Out-of-home consumers and convenience shoppers’ (28.6% mostly consists of consumers aged between 25 and 34 y old and contains a large proportion of upper-class consumers. Consumers in this segment prefer to eat out and consume convenience products. This segment has the second highest percentage of regular consumers of rabbit meat (36.9%. The segment also has the second highest percentage of consumers who rarely or never eat rabbit meat (43.9%. (iv ‘Rational purchaser with little interest in cooking’ (16.2% has the highest proportion of consumers aged 55 to 74 y old. Consumers in this segment have the least interest in cooking, the most interest in the purchasing process, and the lowest

Database on Aims and Visions in the COINCO Corridor

DEFF Research Database (Denmark)

2005-01-01

This database contains aims and visions regarding overall regional development as well as more specific aims and visions related to transport and infrastructure in the Corridor Oslo-Göteborg-Copenhagen-Berlin. The sources used for this database are the most essential planning documents from Denmark...

The Hinge Segment of Human NADPH-Cytochrome P450 Reductase in Conformational Switching: The Critical Role of Ionic Strength

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