Organic Food Market Segmentation in Lebanon

Science.gov (United States)

Tleis, Malak; Roma, Rocco; Callieris, Roberta

2015-04-01

Organic farming in Lebanon is not a new concept. It started with the efforts of the private sector more than a decade ago and is still present even with the limited agricultural production. The local market is quite developed in comparison to neighboring countries, depending mainly on imports. Few studies were addressed to organic consumption in Lebanon, were none of them dealt with organic consumers analysis. Therefore, our objectives were to identify the profiles of Lebanese organic consumer and non organic consumer and to propose appropriate marketing strategies for each segment of consumer with the final aim of developing the Lebanese organic market. A survey, based on the use of closed-ended questionnaire, was addressed to 400 consumers in the capital, Beirut, from the end of February till the end of March 2014. Data underwent descriptive analyses, principal component analyses (PCA) and cluster analyses (k-means method) through the statistical software SPSS. Four cluster were obtained based on psychographic characteristics and willingness to pay (WTP) for the principal organic products purchased. "Localists" and "Health conscious" clusters constituted the largest proportion of the selected sample, thus were the most critical to be addressed by specific marketing strategies emphasizing the combination of local and organic food and the healthy properties of organic products. "Rational" and "Irregular" cluster were relatively small groups, addressed by pricing and promotional strategies. This study showed a positive attitude among Lebanese consumer towards organic food, where egoistic motives are prevailing over altruistic motives. High prices of organic commodities and low trust in organic farming, remain a constraint to levitating organic consumption. The combined efforts of the public and the private sector are required to spread the knowledge about positive environmental payback of organic agriculture and for the promotion of locally produced organic goods.

User Interaction in Semi-Automatic Segmentation of Organs at Risk: a Case Study in Radiotherapy

NARCIS (Netherlands)

A. Ramkumar (Anjana); J. Dolz (Jose); H.A. Kirisli (Hortense); S. Adebahr (Sonja); T. Schimek-Jasch (Tanja); U. Nestle (Ursula); L. Massoptier (Laurent); E. Varga (Edit); P.J. Stappers (P.); W.J. Niessen (Wiro); Y. Song (Yu)

2016-01-01

textabstractAccurate segmentation of organs at risk is an important step in radiotherapy planning. Manual segmentation being a tedious procedure and prone to inter- and intra-observer variability, there is a growing interest in automated segmentation methods. However, automatic methods frequently

User Interaction in Semi-Automatic Segmentation of Organs at Risk : A Case Study in Radiotherapy

NARCIS (Netherlands)

Ramkumar, A.; Dolz, J.; Kirisli, H.A.; Adebahr, S.; Schimek-Jasch, T.; Nestle, U.; Massoptier, L.; Varga, E.; Stappers, P.J.; Niessen, W.J.; Song, Y.

2015-01-01

Accurate segmentation of organs at risk is an important step in radiotherapy planning. Manual segmentation being a tedious procedure and prone to inter- and intra-observer variability, there is a growing interest in automated segmentation methods. However, automatic methods frequently fail to

Segmental, synaptic actions of commissural interneurons in the mouse spinal cord

DEFF Research Database (Denmark)

Quinlan, Katharina A.; Kiehn, Ole

2007-01-01

outlines the basic connectivity pattern of CINs in the mouse spinal cord on a segmental level. Our study suggests that, based on observed synaptic connectivity, both short- and long-range CINs are likely involved in segmental left-right coordination and that the CIN system is organized into a dual......-inhibitory and single-excitatory system. These systems are organized in a way that they could provide appropriate coordination during locomotion....

Language, copyright and geographic segmentation in the EU Digital Single Market for music and film

OpenAIRE

Estrella Gomez Herrera; Bertin Martens

2015-01-01

The EU seeks to create a seamless online Digital Single Market for media products such as digital music and film. The territoriality of the copyright regime is often perceived as an obstacle that induces geographical segmentation. This paper provides empirical evidence on the extent of market segmentation in the EU on the supply and demand side and measures the contribution of several drivers of this market segmentation. We use data from the Apple iTunes country stores in 27 EU Member States ...

AUDIT DISCLOSURE OF MATERIAL INFORMATION ON OPERATING SEGMENTS THE ACTIVITIES OF THE ORGANIZATIONS OF TOURIST SPHERE

Directory of Open Access Journals (Sweden)

Екатерина Николаевна Скорикова

2013-04-01

Full Text Available In modern conditions market economy for take decisions of use services tourist organizations, users not enough relevant information of financial result activities.The article considered audit disclosure relevant information on operating segments activities, for example tourist organizations.In result research considered operating segments on current and discontinued activities, and their impact on disclosure relevant information of financial result.Proposed option disclosure relevant information on operating segments activities in explanatory Note to the annual financial statements.Received results prove, that information on operating segments activities essential in all aspects.Results research has as theoretical so and practical significance, and can used at further development theoretical and practical questions on disclosure relevant information of activities organizations of tourist sphere.DOI: http://dx.doi.org/10.12731/2218-7405-2013-1-2

SU-F-J-113: Multi-Atlas Based Automatic Organ Segmentation for Lung Radiotherapy Planning

International Nuclear Information System (INIS)

Kim, J; Han, J; Ailawadi, S; Baker, J; Hsia, A; Xu, Z; Ryu, S

2016-01-01

Purpose: Normal organ segmentation is one time-consuming and labor-intensive step for lung radiotherapy treatment planning. The aim of this study is to evaluate the performance of a multi-atlas based segmentation approach for automatic organs at risk (OAR) delineation. Methods: Fifteen Lung stereotactic body radiation therapy patients were randomly selected. Planning CT images and OAR contours of the heart - HT, aorta - AO, vena cava - VC, pulmonary trunk - PT, and esophagus – ES were exported and used as reference and atlas sets. For automatic organ delineation for a given target CT, 1) all atlas sets were deformably warped to the target CT, 2) the deformed sets were accumulated and normalized to produce organ probability density (OPD) maps, and 3) the OPD maps were converted to contours via image thresholding. Optimal threshold for each organ was empirically determined by comparing the auto-segmented contours against their respective reference contours. The delineated results were evaluated by measuring contour similarity metrics: DICE, mean distance (MD), and true detection rate (TD), where DICE=(intersection volume/sum of two volumes) and TD = {1.0 - (false positive + false negative)/2.0}. Diffeomorphic Demons algorithm was employed for CT-CT deformable image registrations. Results: Optimal thresholds were determined to be 0.53 for HT, 0.38 for AO, 0.28 for PT, 0.43 for VC, and 0.31 for ES. The mean similarity metrics (DICE[%], MD[mm], TD[%]) were (88, 3.2, 89) for HT, (79, 3.2, 82) for AO, (75, 2.7, 77) for PT, (68, 3.4, 73) for VC, and (51,2.7, 60) for ES. Conclusion: The investigated multi-atlas based approach produced reliable segmentations for the organs with large and relatively clear boundaries (HT and AO). However, the detection of small and narrow organs with diffused boundaries (ES) were challenging. Sophisticated atlas selection and multi-atlas fusion algorithms may further improve the quality of segmentations.

SU-F-J-113: Multi-Atlas Based Automatic Organ Segmentation for Lung Radiotherapy Planning

Energy Technology Data Exchange (ETDEWEB)

Kim, J; Han, J; Ailawadi, S; Baker, J; Hsia, A; Xu, Z; Ryu, S [Stony Brook University Hospital, Stony Brook, NY (United States)

2016-06-15

Purpose: Normal organ segmentation is one time-consuming and labor-intensive step for lung radiotherapy treatment planning. The aim of this study is to evaluate the performance of a multi-atlas based segmentation approach for automatic organs at risk (OAR) delineation. Methods: Fifteen Lung stereotactic body radiation therapy patients were randomly selected. Planning CT images and OAR contours of the heart - HT, aorta - AO, vena cava - VC, pulmonary trunk - PT, and esophagus – ES were exported and used as reference and atlas sets. For automatic organ delineation for a given target CT, 1) all atlas sets were deformably warped to the target CT, 2) the deformed sets were accumulated and normalized to produce organ probability density (OPD) maps, and 3) the OPD maps were converted to contours via image thresholding. Optimal threshold for each organ was empirically determined by comparing the auto-segmented contours against their respective reference contours. The delineated results were evaluated by measuring contour similarity metrics: DICE, mean distance (MD), and true detection rate (TD), where DICE=(intersection volume/sum of two volumes) and TD = {1.0 - (false positive + false negative)/2.0}. Diffeomorphic Demons algorithm was employed for CT-CT deformable image registrations. Results: Optimal thresholds were determined to be 0.53 for HT, 0.38 for AO, 0.28 for PT, 0.43 for VC, and 0.31 for ES. The mean similarity metrics (DICE[%], MD[mm], TD[%]) were (88, 3.2, 89) for HT, (79, 3.2, 82) for AO, (75, 2.7, 77) for PT, (68, 3.4, 73) for VC, and (51,2.7, 60) for ES. Conclusion: The investigated multi-atlas based approach produced reliable segmentations for the organs with large and relatively clear boundaries (HT and AO). However, the detection of small and narrow organs with diffused boundaries (ES) were challenging. Sophisticated atlas selection and multi-atlas fusion algorithms may further improve the quality of segmentations.

Single versus double-layer uterine closure at cesarean: impact on lower uterine segment thickness at next pregnancy.

Science.gov (United States)

Vachon-Marceau, Chantale; Demers, Suzanne; Bujold, Emmanuel; Roberge, Stephanie; Gauthier, Robert J; Pasquier, Jean-Charles; Girard, Mario; Chaillet, Nils; Boulvain, Michel; Jastrow, Nicole

2017-07-01

Uterine rupture is a potential life-threatening complication during a trial of labor after cesarean delivery. Single-layer closure of the uterus at cesarean delivery has been associated with an increased risk of uterine rupture compared with double-layer closure. Lower uterine segment thickness measurement by ultrasound has been used to evaluate the quality of the uterine scar after cesarean delivery and is associated with the risk of uterine rupture. To estimate the impact of previous uterine closure on lower uterine segment thickness. Women with a previous single low-transverse cesarean delivery were recruited at 34-38 weeks' gestation. Transabdominal and transvaginal ultrasound evaluation of the lower uterine segment thickness was performed by a sonographer blinded to clinical data. Previous operative reports were reviewed to obtain the type of previous uterine closure. Third-trimester lower uterine segment thickness at the next pregnancy was compared according to the number of layers sutured and according to the type of thread for uterine closure, using weighted mean differences and multivariate logistic regression analyses. Of 1613 women recruited, with operative reports available, 495 (31%) had a single-layer and 1118 (69%) had a double-layer closure. The mean third-trimester lower uterine segment thickness was 3.3 ± 1.3 mm and the proportion with lower uterine segment thickness cesarean delivery is associated with a thicker third-trimester lower uterine segment and a reduced risk of lower uterine segment thickness <2.0 mm in the next pregnancy. The type of thread for uterine closure has no significant impact on lower uterine segment thickness. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

Bertrand, Sarah; Cerutti, Guillaume; Tougne, Laure

2018-04-01

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

Single-stage posterior transforaminal lumbar interbody fusion, debridement, limited decompression, 3-column reconstruction, and posterior instrumentation in surgical treatment for single-segment lumbar spinal tuberculosis.

Science.gov (United States)

Zeng, Hao; Wang, Xiyang; Zhang, Penghui; Peng, Wei; Liu, Zheng; Zhang, Yupeng

2015-01-01

The aim of this study is to determine the feasibility and efficacy of surgical management of single-segment lumbar spinal tuberculosis (TB) by using single-stage posterior transforaminal lumbar interbody fusion, debridement, limited decompression, 3-column reconstruction, and posterior instrumentation. Seventeen cases of single-segment lumbar TB were treated with single-stage posterior transforaminal lumbar interbody fusion, debridement, limited decompression, 3-column reconstruction, and posterior instrumentation. The mean follow-up was 36.9 months (range: 24-62 months). The kyphotic angle ranged from 15.2-35.1° preoperatively, with an average measurement of 27.8°. The American Spinal Injury Association (ASIA) score system was used to evaluate the neurological deficits and erythrocyte sedimentation rate (ESR) used to judge the activity of TB. Spinal TB was completely cured in all 17 patients. There was no recurrent TB infection. The postoperative kyphotic angle was 6.6-10.2°, 8.1° in average, and there was no significant loss of the correction at final follow-up. Solid fusion was achieved in all cases. Neurological condition in all patients was improved after surgery. Single-stage posterior transforaminal lumbar interbody fusion, debridement, limited decompression, 3-column reconstruction, and posterior instrumentation can be a feasible and effective method the in treatment of single-segment lumbar spinal TB.

Performance evaluation of 2D and 3D deep learning approaches for automatic segmentation of multiple organs on CT images

Science.gov (United States)

Zhou, Xiangrong; Yamada, Kazuma; Kojima, Takuya; Takayama, Ryosuke; Wang, Song; Zhou, Xinxin; Hara, Takeshi; Fujita, Hiroshi

2018-02-01

The purpose of this study is to evaluate and compare the performance of modern deep learning techniques for automatically recognizing and segmenting multiple organ regions on 3D CT images. CT image segmentation is one of the important task in medical image analysis and is still very challenging. Deep learning approaches have demonstrated the capability of scene recognition and semantic segmentation on nature images and have been used to address segmentation problems of medical images. Although several works showed promising results of CT image segmentation by using deep learning approaches, there is no comprehensive evaluation of segmentation performance of the deep learning on segmenting multiple organs on different portions of CT scans. In this paper, we evaluated and compared the segmentation performance of two different deep learning approaches that used 2D- and 3D deep convolutional neural networks (CNN) without- and with a pre-processing step. A conventional approach that presents the state-of-the-art performance of CT image segmentation without deep learning was also used for comparison. A dataset that includes 240 CT images scanned on different portions of human bodies was used for performance evaluation. The maximum number of 17 types of organ regions in each CT scan were segmented automatically and compared to the human annotations by using ratio of intersection over union (IU) as the criterion. The experimental results demonstrated the IUs of the segmentation results had a mean value of 79% and 67% by averaging 17 types of organs that segmented by a 3D- and 2D deep CNN, respectively. All the results of the deep learning approaches showed a better accuracy and robustness than the conventional segmentation method that used probabilistic atlas and graph-cut methods. The effectiveness and the usefulness of deep learning approaches were demonstrated for solving multiple organs segmentation problem on 3D CT images.

Segmentation of color images by chromaticity features using self-organizing maps

Directory of Open Access Journals (Sweden)

Farid García-Lamont

2016-05-01

Full Text Available Usually, the segmentation of color images is performed using cluster-based methods and the RGB space to represent the colors. The drawback with these methods is the a priori knowledge of the number of groups, or colors, in the image; besides, the RGB space issensitive to the intensity of the colors. Humans can identify different sections within a scene by the chromaticity of its colors of, as this is the feature humans employ to tell them apart. In this paper, we propose to emulate the human perception of color by training a self-organizing map (SOM with samples of chromaticity of different colors. The image to process is mapped to the HSV space because in this space the chromaticity is decoupled from the intensity, while in the RGB space this is not possible. Our proposal does not require knowing a priori the number of colors within a scene, and non-uniform illumination does not significantly affect the image segmentation. We present experimental results using some images from the Berkeley segmentation database by employing SOMs with different sizes, which are segmented successfully using only chromaticity features.

Colour segmentation of multi variants tuberculosis sputum images using self organizing map

Science.gov (United States)

Rulaningtyas, Riries; Suksmono, Andriyan B.; Mengko, Tati L. R.; Saptawati, Putri

2017-05-01

Lung tuberculosis detection is still identified from Ziehl-Neelsen sputum smear images in low and middle countries. The clinicians decide the grade of this disease by counting manually the amount of tuberculosis bacilli. It is very tedious for clinicians with a lot number of patient and without standardization for sputum staining. The tuberculosis sputum images have multi variant characterizations in colour, because of no standardization in staining. The sputum has more variants colour and they are difficult to be identified. For helping the clinicians, this research examined the Self Organizing Map method for colouring image segmentation in sputum images based on colour clustering. This method has better performance than k-means clustering which also tried in this research. The Self Organizing Map could segment the sputum images with y good result and cluster the colours adaptively.

A whole body atlas for segmentation and delineation of organs for radiation therapy planning

International Nuclear Information System (INIS)

Qatarneh, S.M.; Crafoord, J.; Kramer, E.L.; Maguire, G.Q.; Brahme, A.; Noz, M.E.; Hyoedynmaa, S.

2001-01-01

A semi-automatic procedure for delineation of organs to be used as the basis of a whole body atlas database for radiation therapy planning was developed. The Visible Human Male Computed Tomography (CT)-data set was used as a 'standard man' reference. The organ of interest was outlined manually and then transformed by a polynomial warping algorithm onto a clinical patient CT. This provided an initial contour, which was then adjusted and refined by the semi-automatic active contour model to find the final organ outline. The liver was used as a test organ for evaluating the performance of the procedure. Liver outlines obtained by the segmentation algorithm on six patients were compared to those manually drawn by a radiologist. The combination of warping and semi-automatic active contour model generally provided satisfactory segmentation results, but the procedure has to be extended to three dimensions

Automated torso organ segmentation from 3D CT images using structured perceptron and dual decomposition

Science.gov (United States)

Nimura, Yukitaka; Hayashi, Yuichiro; Kitasaka, Takayuki; Mori, Kensaku

2015-03-01

This paper presents a method for torso organ segmentation from abdominal CT images using structured perceptron and dual decomposition. A lot of methods have been proposed to enable automated extraction of organ regions from volumetric medical images. However, it is necessary to adjust empirical parameters of them to obtain precise organ regions. This paper proposes an organ segmentation method using structured output learning. Our method utilizes a graphical model and binary features which represent the relationship between voxel intensities and organ labels. Also we optimize the weights of the graphical model by structured perceptron and estimate the best organ label for a given image by dynamic programming and dual decomposition. The experimental result revealed that the proposed method can extract organ regions automatically using structured output learning. The error of organ label estimation was 4.4%. The DICE coefficients of left lung, right lung, heart, liver, spleen, pancreas, left kidney, right kidney, and gallbladder were 0.91, 0.95, 0.77, 0.81, 0.74, 0.08, 0.83, 0.84, and 0.03, respectively.

User Interaction in Semi-Automatic Segmentation of Organs at Risk: a Case Study in Radiotherapy.

Science.gov (United States)

Ramkumar, Anjana; Dolz, Jose; Kirisli, Hortense A; Adebahr, Sonja; Schimek-Jasch, Tanja; Nestle, Ursula; Massoptier, Laurent; Varga, Edit; Stappers, Pieter Jan; Niessen, Wiro J; Song, Yu

2016-04-01

Accurate segmentation of organs at risk is an important step in radiotherapy planning. Manual segmentation being a tedious procedure and prone to inter- and intra-observer variability, there is a growing interest in automated segmentation methods. However, automatic methods frequently fail to provide satisfactory result, and post-processing corrections are often needed. Semi-automatic segmentation methods are designed to overcome these problems by combining physicians' expertise and computers' potential. This study evaluates two semi-automatic segmentation methods with different types of user interactions, named the "strokes" and the "contour", to provide insights into the role and impact of human-computer interaction. Two physicians participated in the experiment. In total, 42 case studies were carried out on five different types of organs at risk. For each case study, both the human-computer interaction process and quality of the segmentation results were measured subjectively and objectively. Furthermore, different measures of the process and the results were correlated. A total of 36 quantifiable and ten non-quantifiable correlations were identified for each type of interaction. Among those pairs of measures, 20 of the contour method and 22 of the strokes method were strongly or moderately correlated, either directly or inversely. Based on those correlated measures, it is concluded that: (1) in the design of semi-automatic segmentation methods, user interactions need to be less cognitively challenging; (2) based on the observed workflows and preferences of physicians, there is a need for flexibility in the interface design; (3) the correlated measures provide insights that can be used in improving user interaction design.

Clinical evaluation of single-shot and readout-segmented diffusion-weighted imaging in stroke patients at 3 T

International Nuclear Information System (INIS)

Morelli, John; Porter, David; Ai, Fei

2013-01-01

Background: Diffusion-weighted imaging (DWI) magnetic resonance imaging (MRI) is most commonly performed utilizing a single-shot echo-planar imaging technique (ss-EPI). Susceptibility artifact and image blur are severe when this sequence is utilized at 3 T. Purpose: To evaluate a readout-segmented approach to DWI MR in comparison with single-shot echo planar imaging for brain MRI. Material and Methods: Eleven healthy volunteers and 14 patients with acute and early subacute infarctions underwent DWI MR examinations at 1.5 and 3T with ss-EPI and readout-segmented echo-planar (rs-EPI) DWI at equal nominal spatial resolutions. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) calculations were made, and two blinded readers ranked the scans in terms of high signal intensity bulk susceptibility artifact, spatial distortions, image blur, overall preference, and motion artifact. Results: SNR and CNR were greatest with rs-EPI (8.1 ± 0.2 SNR vs. 6.0 ± 0.2; P -4 at 3T). Spatial distortions were greater with single-shot (0.23 ± 0.03 at 3T; P <0.001) than with rs-EPI (0.12 ± 0.02 at 3T). Combined with blur and artifact reduction, this resulted in a qualitative preference for the readout-segmented scans overall. Conclusion: Substantial image quality improvements are possible with readout-segmented vs. single-shot EPI - the current clinical standard for DWI - regardless of field strength (1.5 or 3 T). This results in improved image quality secondary to greater real spatial resolution and reduced artifacts from susceptibility in MR imaging of the brain

Fabrication and characterization of single segment CoNiP and multisegment CoNiP/Au nanowires

International Nuclear Information System (INIS)

Luu Van Thiem; Le Tuan Tu

2014-01-01

This paper presents the fabrication of CoNiP single segment and CoNiP/Au multisegment nanowires. We have fabricated these nanowires by electrodeposition method into polycarbonate templates with a nominal pore diameter about 100 nm. The hysteresis loops were measured with the applied magnetic field parallel and perpendicular to the wire axis using a vibrating sample magnetometer (VSM). The structure morphology was observed by Scanning Electron Microscopy (SEM) and the element composition of CoNiP/Au multisegment nanowires were analyzed by EDS. The results show that nanowires are very uniform with the diameter of 100 nm. The observed coercivity (H C ) and squareness (Mr/Ms) of CoNiP single segment nanowires are larger than the CoNiP/Au multisegment nanowires. (author)

Automatic segmentation of abdominal organs and adipose tissue compartments in water-fat MRI: Application to weight-loss in obesity.

Science.gov (United States)

Shen, Jun; Baum, Thomas; Cordes, Christian; Ott, Beate; Skurk, Thomas; Kooijman, Hendrik; Rummeny, Ernst J; Hauner, Hans; Menze, Bjoern H; Karampinos, Dimitrios C

2016-09-01

To develop a fully automatic algorithm for abdominal organs and adipose tissue compartments segmentation and to assess organ and adipose tissue volume changes in longitudinal water-fat magnetic resonance imaging (MRI) data. Axial two-point Dixon images were acquired in 20 obese women (age range 24-65, BMI 34.9±3.8kg/m(2)) before and after a four-week calorie restriction. Abdominal organs, subcutaneous adipose tissue (SAT) compartments (abdominal, anterior, posterior), SAT regions along the feet-head direction and regional visceral adipose tissue (VAT) were assessed by a fully automatic algorithm using morphological operations and a multi-atlas-based segmentation method. The accuracy of organ segmentation represented by Dice coefficients ranged from 0.672±0.155 for the pancreas to 0.943±0.023 for the liver. Abdominal SAT changes were significantly greater in the posterior than the anterior SAT compartment (-11.4%±5.1% versus -9.5%±6.3%, pabdominal adipose tissue and organ segmentation, and allowed the detection of SAT and VAT subcompartments changes during weight loss. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Application of single- and dual-energy CT brain tissue segmentation to PET monitoring of proton therapy

Science.gov (United States)

Berndt, Bianca; Landry, Guillaume; Schwarz, Florian; Tessonnier, Thomas; Kamp, Florian; Dedes, George; Thieke, Christian; Würl, Matthias; Kurz, Christopher; Ganswindt, Ute; Verhaegen, Frank; Debus, Jürgen; Belka, Claus; Sommer, Wieland; Reiser, Maximilian; Bauer, Julia; Parodi, Katia

2017-03-01

The purpose of this work was to evaluate the ability of single and dual energy computed tomography (SECT, DECT) to estimate tissue composition and density for usage in Monte Carlo (MC) simulations of irradiation induced β + activity distributions. This was done to assess the impact on positron emission tomography (PET) range verification in proton therapy. A DECT-based brain tissue segmentation method was developed for white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF). The elemental composition of reference tissues was assigned to closest CT numbers in DECT space (DECTdist). The method was also applied to SECT data (SECTdist). In a validation experiment, the proton irradiation induced PET activity of three brain equivalent solutions (BES) was compared to simulations based on different tissue segmentations. Five patients scanned with a dual source DECT scanner were analyzed to compare the different segmentation methods. A single magnetic resonance (MR) scan was used for comparison with an established segmentation toolkit. Additionally, one patient with SECT and post-treatment PET scans was investigated. For BES, DECTdist and SECTdist reduced differences to the reference simulation by up to 62% when compared to the conventional stoichiometric segmentation (SECTSchneider). In comparison to MR brain segmentation, Dice similarity coefficients for WM, GM and CSF were 0.61, 0.67 and 0.66 for DECTdist and 0.54, 0.41 and 0.66 for SECTdist. MC simulations of PET treatment verification in patients showed important differences between DECTdist/SECTdist and SECTSchneider for patients with large CSF areas within the treatment field but not in WM and GM. Differences could be misinterpreted as PET derived range shifts of up to 4 mm. DECTdist and SECTdist yielded comparable activity distributions, and comparison of SECTdist to a measured patient PET scan showed improved agreement when compared to SECTSchneider. The agreement between predicted and measured PET

Segmentation of Natural Gas Customers in Industrial Sector Using Self-Organizing Map (SOM) Method

Science.gov (United States)

Masbar Rus, A. M.; Pramudita, R.; Surjandari, I.

2018-03-01

The usage of the natural gas which is non-renewable energy, needs to be more efficient. Therefore, customer segmentation becomes necessary to set up a marketing strategy to be right on target or to determine an appropriate fee. This research was conducted at PT PGN using one of data mining method, i.e. Self-Organizing Map (SOM). The clustering process is based on the characteristic of its customers as a reference to create the customer segmentation of natural gas customers. The input variables of this research are variable of area, type of customer, the industrial sector, the average usage, standard deviation of the usage, and the total deviation. As a result, 37 cluster and 9 segment from 838 customer data are formed. These 9 segments then employed to illustrate the general characteristic of the natural gas customer of PT PGN.

Spherical Projection Based Straight Line Segment Extraction for Single Station Terrestrial Laser Point Cloud

Directory of Open Access Journals (Sweden)

ZHANG Fan

2015-06-01

Full Text Available Due to the discrete distribution computing errors and lack of adaptability are ubiquitous in the current straight line extraction for TLS data methods. A 3D straight line segment extraction method is proposed based on spherical projection for single station terrestrial laser point clouds. Firstly, horizontal and vertical angles of each laser point are calculated by means of spherical coordinates, intensity panoramic image according to the two angles is generated. Secondly, edges which include straight line features are detected from intensity panoramic image by using of edge detection algorithm. Thirdly, great circles are detected from edges of panoramic image using spherical Hough transform. According to the axiom that a straight line segment in 3D space is a spherical great circle after spherical projection, detecting great circles from spherical projected data sets is essentially detecting straight line segments from 3D data sets without spherical projection. Finally, a robust 3D straight line fitting method is employed to fitting the straight lines and calculating parameters of the straight line segments. Experiments using different data sets and comparison with other methods show the accuracy and applicability of the proposed method.

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.)

Regeneration of Surgically Excised Segments of Dog Esophagus using Biodegradable PLA Hollow Organ Grafts,

Science.gov (United States)

1980-06-01

7 AG 396 ARMY INST OF DENTAL RESEARCH WASHINGTON DC FIG 6/5 REGENERATION OF SURGICALLY EXCISED SEGMENTS OF DOG ESOPHAGUS US-ETC(W) U15 G’OE UN8 N F...the graft; infection; inadequate blood supply; difficulties in suture retention; leakage at the anastomatic sites; stenosis of the anasto- mosis...excised segment of the dog esophagus. On a conceptual L- J basis, the use of a biodegradable polymer to fabricate a successful J hollow organ graft holds

Organic field-effect transistors using single crystals

International Nuclear Information System (INIS)

Hasegawa, Tatsuo; Takeya, Jun

2009-01-01

Organic field-effect transistors using small-molecule organic single crystals are developed to investigate fundamental aspects of organic thin-film transistors that have been widely studied for possible future markets for 'plastic electronics'. In reviewing the physics and chemistry of single-crystal organic field-effect transistors (SC-OFETs), the nature of intrinsic charge dynamics is elucidated for the carriers induced at the single crystal surfaces of molecular semiconductors. Materials for SC-OFETs are first reviewed with descriptions of the fabrication methods and the field-effect characteristics. In particular, a benchmark carrier mobility of 20-40 cm 2 Vs -1 , achieved with thin platelets of rubrene single crystals, demonstrates the significance of the SC-OFETs and clarifies material limitations for organic devices. In the latter part of this review, we discuss the physics of microscopic charge transport by using SC-OFETs at metal/semiconductor contacts and along semiconductor/insulator interfaces. Most importantly, Hall effect and electron spin resonance (ESR) measurements reveal that interface charge transport in molecular semiconductors is properly described in terms of band transport and localization by charge traps. (topical review)

Computer-aided liver volumetry: performance of a fully-automated, prototype post-processing solution for whole-organ and lobar segmentation based on MDCT imaging.

Science.gov (United States)

Fananapazir, Ghaneh; Bashir, Mustafa R; Marin, Daniele; Boll, Daniel T

2015-06-01

To evaluate the performance of a prototype, fully-automated post-processing solution for whole-liver and lobar segmentation based on MDCT datasets. A polymer liver phantom was used to assess accuracy of post-processing applications comparing phantom volumes determined via Archimedes' principle with MDCT segmented datasets. For the IRB-approved, HIPAA-compliant study, 25 patients were enrolled. Volumetry performance compared the manual approach with the automated prototype, assessing intraobserver variability, and interclass correlation for whole-organ and lobar segmentation using ANOVA comparison. Fidelity of segmentation was evaluated qualitatively. Phantom volume was 1581.0 ± 44.7 mL, manually segmented datasets estimated 1628.0 ± 47.8 mL, representing a mean overestimation of 3.0%, automatically segmented datasets estimated 1601.9 ± 0 mL, representing a mean overestimation of 1.3%. Whole-liver and segmental volumetry demonstrated no significant intraobserver variability for neither manual nor automated measurements. For whole-liver volumetry, automated measurement repetitions resulted in identical values; reproducible whole-organ volumetry was also achieved with manual segmentation, p(ANOVA) 0.98. For lobar volumetry, automated segmentation improved reproducibility over manual approach, without significant measurement differences for either methodology, p(ANOVA) 0.95-0.99. Whole-organ and lobar segmentation results from manual and automated segmentation showed no significant differences, p(ANOVA) 0.96-1.00. Assessment of segmentation fidelity found that segments I-IV/VI showed greater segmentation inaccuracies compared to the remaining right hepatic lobe segments. Automated whole-liver segmentation showed non-inferiority of fully-automated whole-liver segmentation compared to manual approaches with improved reproducibility and post-processing duration; automated dual-seed lobar segmentation showed slight tendencies for underestimating the right hepatic lobe

Multiatlas segmentation of thoracic and abdominal anatomy with level set-based local search.

Science.gov (United States)

Schreibmann, Eduard; Marcus, David M; Fox, Tim

2014-07-08

Segmentation of organs at risk (OARs) remains one of the most time-consuming tasks in radiotherapy treatment planning. Atlas-based segmentation methods using single templates have emerged as a practical approach to automate the process for brain or head and neck anatomy, but pose significant challenges in regions where large interpatient variations are present. We show that significant changes are needed to autosegment thoracic and abdominal datasets by combining multi-atlas deformable registration with a level set-based local search. Segmentation is hierarchical, with a first stage detecting bulk organ location, and a second step adapting the segmentation to fine details present in the patient scan. The first stage is based on warping multiple presegmented templates to the new patient anatomy using a multimodality deformable registration algorithm able to cope with changes in scanning conditions and artifacts. These segmentations are compacted in a probabilistic map of organ shape using the STAPLE algorithm. Final segmentation is obtained by adjusting the probability map for each organ type, using customized combinations of delineation filters exploiting prior knowledge of organ characteristics. Validation is performed by comparing automated and manual segmentation using the Dice coefficient, measured at an average of 0.971 for the aorta, 0.869 for the trachea, 0.958 for the lungs, 0.788 for the heart, 0.912 for the liver, 0.884 for the kidneys, 0.888 for the vertebrae, 0.863 for the spleen, and 0.740 for the spinal cord. Accurate atlas segmentation for abdominal and thoracic regions can be achieved with the usage of a multi-atlas and perstructure refinement strategy. To improve clinical workflow and efficiency, the algorithm was embedded in a software service, applying the algorithm automatically on acquired scans without any user interaction.

The evaluation of single-view and multi-view fusion 3D echocardiography using image-driven segmentation and tracking.

Science.gov (United States)

Rajpoot, Kashif; Grau, Vicente; Noble, J Alison; Becher, Harald; Szmigielski, Cezary

2011-08-01

Real-time 3D echocardiography (RT3DE) promises a more objective and complete cardiac functional analysis by dynamic 3D image acquisition. Despite several efforts towards automation of left ventricle (LV) segmentation and tracking, these remain challenging research problems due to the poor-quality nature of acquired images usually containing missing anatomical information, speckle noise, and limited field-of-view (FOV). Recently, multi-view fusion 3D echocardiography has been introduced as acquiring multiple conventional single-view RT3DE images with small probe movements and fusing them together after alignment. This concept of multi-view fusion helps to improve image quality and anatomical information and extends the FOV. We now take this work further by comparing single-view and multi-view fused images in a systematic study. In order to better illustrate the differences, this work evaluates image quality and information content of single-view and multi-view fused images using image-driven LV endocardial segmentation and tracking. The image-driven methods were utilized to fully exploit image quality and anatomical information present in the image, thus purposely not including any high-level constraints like prior shape or motion knowledge in the analysis approaches. Experiments show that multi-view fused images are better suited for LV segmentation and tracking, while relatively more failures and errors were observed on single-view images. Copyright © 2011 Elsevier B.V. All rights reserved.

Organic field-effect transistors using single crystals

Directory of Open Access Journals (Sweden)

Tatsuo Hasegawa and Jun Takeya

2009-01-01

Full Text Available Organic field-effect transistors using small-molecule organic single crystals are developed to investigate fundamental aspects of organic thin-film transistors that have been widely studied for possible future markets for 'plastic electronics'. In reviewing the physics and chemistry of single-crystal organic field-effect transistors (SC-OFETs, the nature of intrinsic charge dynamics is elucidated for the carriers induced at the single crystal surfaces of molecular semiconductors. Materials for SC-OFETs are first reviewed with descriptions of the fabrication methods and the field-effect characteristics. In particular, a benchmark carrier mobility of 20–40 cm2 Vs−1, achieved with thin platelets of rubrene single crystals, demonstrates the significance of the SC-OFETs and clarifies material limitations for organic devices. In the latter part of this review, we discuss the physics of microscopic charge transport by using SC-OFETs at metal/semiconductor contacts and along semiconductor/insulator interfaces. Most importantly, Hall effect and electron spin resonance (ESR measurements reveal that interface charge transport in molecular semiconductors is properly described in terms of band transport and localization by charge traps.

Lifestyle segmentation of US food shoppers to examine organic and local food consumption.

Science.gov (United States)

Nie, Cong; Zepeda, Lydia

2011-08-01

The food related lifestyle (FRL) model, widely used on European data, is applied to US data using a modified survey instrument to examine organic and local food consumption. Since empirical studies indicate these shoppers are motivated by environmental and health concerns and limited by access, the conceptual framework employs an environmental behavior model, Attitude Behavior Context (ABC), which is consistent with means-end chain theory, the Health Belief (HB) model, and the FRL model. ABC theory incorporates contextual factors that may limit consumers' ability to act on their intentions. US food shopper data was collected in 2003 (n=956) utilizing an instrument with variables adapted from the FRL, ABC, and HB models. Cluster analysis segmented food shoppers into four FRL groups: rational, adventurous, careless, and a fourth segment that had some characteristics of both conservative and uninvolved consumers. The segments exhibited significant differences in organic and local food consumption. These were correlated with consumers' environmental concerns, knowledge and practices, health concerns and practices, as well as some demographic characteristics (race, gender, age, education), income, and variables that measured access to these foods. Implications for marketing and public policy strategies to promote organic and local foods include: emphasizing taste, nutrition, value, children, and enjoyment of cooking for rational consumers; and emphasizing health, fitness, and freshness, and providing ethnic foods for adventurous consumers. While both careless and conservative/uninvolved consumers valued convenience, the former tended to be in the highest income group, while the latter were in the lowest, were more likely to be either in the youngest or oldest age groups, and were very concerned about food safety and health. Copyright © 2011 Elsevier Ltd. All rights reserved.

Heterogeneous Monolithic Integration of Single-Crystal Organic Materials.

Science.gov (United States)

Park, Kyung Sun; Baek, Jangmi; Park, Yoonkyung; Lee, Lynn; Hyon, Jinho; Koo Lee, Yong-Eun; Shrestha, Nabeen K; Kang, Youngjong; Sung, Myung Mo

2017-02-01

Manufacturing high-performance organic electronic circuits requires the effective heterogeneous integration of different nanoscale organic materials with uniform morphology and high crystallinity in a desired arrangement. In particular, the development of high-performance organic electronic and optoelectronic devices relies on high-quality single crystals that show optimal intrinsic charge-transport properties and electrical performance. Moreover, the heterogeneous integration of organic materials on a single substrate in a monolithic way is highly demanded for the production of fundamental organic electronic components as well as complex integrated circuits. Many of the various methods that have been designed to pattern multiple heterogeneous organic materials on a substrate and the heterogeneous integration of organic single crystals with their crystal growth are described here. Critical issues that have been encountered in the development of high-performance organic integrated electronics are also addressed. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Analysis on the use of Multi-Sequence MRI Series for Segmentation of Abdominal Organs

International Nuclear Information System (INIS)

Selver, M A; Selvi, E; Kavur, E; Dicle, O

2015-01-01

Segmentation of abdominal organs from MRI data sets is a challenging task due to various limitations and artefacts. During the routine clinical practice, radiologists use multiple MR sequences in order to analyze different anatomical properties. These sequences have different characteristics in terms of acquisition parameters (such as contrast mechanisms and pulse sequence designs) and image properties (such as pixel spacing, slice thicknesses and dynamic range). For a complete understanding of the data, computational techniques should combine the information coming from these various MRI sequences. These sequences are not acquired in parallel but in a sequential manner (one after another). Therefore, patient movements and respiratory motions change the position and shape of the abdominal organs. In this study, the amount of these effects is measured using three different symmetric surface distance metrics performed to three dimensional data acquired from various MRI sequences. The results are compared to intra and inter observer differences and discussions on using multiple MRI sequences for segmentation and the necessities for registration are presented

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...

CMEIAS color segmentation: an improved computing technology to process color images for quantitative microbial ecology studies at single-cell resolution.

Science.gov (United States)

Gross, Colin A; Reddy, Chandan K; Dazzo, Frank B

2010-02-01

Quantitative microscopy and digital image analysis are underutilized in microbial ecology largely because of the laborious task to segment foreground object pixels from background, especially in complex color micrographs of environmental samples. In this paper, we describe an improved computing technology developed to alleviate this limitation. The system's uniqueness is its ability to edit digital images accurately when presented with the difficult yet commonplace challenge of removing background pixels whose three-dimensional color space overlaps the range that defines foreground objects. Image segmentation is accomplished by utilizing algorithms that address color and spatial relationships of user-selected foreground object pixels. Performance of the color segmentation algorithm evaluated on 26 complex micrographs at single pixel resolution had an overall pixel classification accuracy of 99+%. Several applications illustrate how this improved computing technology can successfully resolve numerous challenges of complex color segmentation in order to produce images from which quantitative information can be accurately extracted, thereby gain new perspectives on the in situ ecology of microorganisms. Examples include improvements in the quantitative analysis of (1) microbial abundance and phylotype diversity of single cells classified by their discriminating color within heterogeneous communities, (2) cell viability, (3) spatial relationships and intensity of bacterial gene expression involved in cellular communication between individual cells within rhizoplane biofilms, and (4) biofilm ecophysiology based on ribotype-differentiated radioactive substrate utilization. The stand-alone executable file plus user manual and tutorial images for this color segmentation computing application are freely available at http://cme.msu.edu/cmeias/ . This improved computing technology opens new opportunities of imaging applications where discriminating colors really matter most

Doses to organs at cerebral risks: optimization by robotized stereotaxic radiotherapy and automatic segmentation atlas versus three dimensional conformal radiotherapy

International Nuclear Information System (INIS)

Bondiau, P.Y.; Thariat, J.; Benezery, K.; Herault, J.; Dalmasso, C.; Marcie, S.; Malandain, G.

2007-01-01

The stereotaxic radiotherapy robotized by 'Cyberknife fourth generation' allows a dosimetric optimization with a high conformity index on the tumor and radiation doses limited on organs at risk. A cerebral automatic anatomic segmentation atlas of organs at risk are used in routine in three dimensions. This study evaluated the superiority of the stereotaxic radiotherapy in comparison with the three dimensional conformal radiotherapy on the preservation of organs at risk in regard of the delivered dose to tumors justifying an accelerated hypo fractionation and a dose escalation. This automatic segmentation atlas should allow to establish correlations between anatomy and cerebral dosimetry; This atlas allows to underline the dosimetry optimization by stereotaxic radiotherapy robotized for organs at risk. (N.C.)

The Importance of Marketing Segmentation

Science.gov (United States)

Martin, Gillian

2011-01-01

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

Failed back surgery syndrome: the role of symptomatic segmental single-level instability after lumbar microdiscectomy.

Science.gov (United States)

Schaller, B

2004-05-01

Segmental instability represents one of several different factors that may cause or contribute to the failed back surgery syndrome after lumbar microdiscectomy. As segmental lumbar instability poses diagnostic problems by lack of clear radiological and clinical criteria, only little is known about the occurrence of this phenomenon following primary microdiscectomy. Retrospectively, the records of 2,353 patients were reviewed according to postoperative symptomatic segmental single-level instability after lumbar microdiscectomy between 1989 and 1997. Progressive neurological deficits increased (mean of 24 months; SD: 12, range 1-70) after the initial surgical procedure in 12 patients. The mean age of the four men and eight women was 43 years (SD: 6, range 40-77). The main symptoms and signs of secondary neurological deterioration were radicular pain in 9 of 12 patients, increased motor weakness in 6 of 12 patients and sensory deficits in 4 of 12 patients. All 12 symptomatic patients had radiological evidence of segmental changes correlating with the clinical symptoms and signs. All but one patient showed a decrease in the disc height greater than 30% at the time of posterior spondylodesis compared with the preoperative images before lumbar microdiscectomy. All patients underwent secondary laminectomy and posterior lumbar sponylodesis. Postoperatively, pain improved in 8 of 9 patients, motor weakness in 3 of 6 patients, and sensory deficits in 2 of 4 patients. During the follow-up period of 72+/-7 months, one patient required a third operation to alleviate spinal stenosis at the upper end of the laminectomy. Patients with secondary segmental instability following microdiscectomy were mainly in their 40s. Postoperative narrowing of the intervertebral space following lumbar microdiscectomy is correlated to the degree of intervertebral disc resection. It can therefore be concluded that (1) patients in their 40s are prone to postoperative narrowing of the intervertebral

Segmental-dependent membrane permeability along the intestine following oral drug administration: Evaluation of a triple single-pass intestinal perfusion (TSPIP) approach in the rat.

Science.gov (United States)

Dahan, Arik; West, Brady T; Amidon, Gordon L

2009-02-15

In this paper we evaluate a modified approach to the traditional single-pass intestinal perfusion (SPIP) rat model in investigating segmental-dependent permeability along the intestine following oral drug administration. Whereas in the traditional model one single segment of the intestine is perfused, we have simultaneously perfused three individual segments of each rat intestine: proximal jejunum, mid-small intestine and distal ileum, enabling to obtain tripled data from each rat compared to the traditional model. Three drugs, with different permeabilities, were utilized to evaluate the model: metoprolol, propranolol and cimetidine. Data was evaluated in comparison to the traditional method. Metoprolol and propranolol showed similar P(eff) values in the modified model in all segments. Segmental-dependent permeability was obtained for cimetidine, with lower P(eff) in the distal parts. Similar P(eff) values for all drugs were obtained in the traditional method, illustrating that the modified model is as accurate as the traditional, throughout a wide range of permeability characteristics, whether the permeability is constant or segment-dependent along the intestine. Three-fold higher statistical power to detect segmental-dependency was obtained in the modified approach, as each subject serves as his own control. In conclusion, the Triple SPIP model can reduce the number of animals utilized in segmental-dependent permeability research without compromising the quality of the data obtained.

SU-E-J-208: Fast and Accurate Auto-Segmentation of Abdominal Organs at Risk for Online Adaptive Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

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

2014-06-01

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

SU-E-J-208: Fast and Accurate Auto-Segmentation of Abdominal Organs at Risk for Online Adaptive Radiotherapy

International Nuclear Information System (INIS)

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

2014-01-01

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

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…

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.

How clonal is clonal? Genome plasticity across multicellular segments of a "Candidatus Marithrix sp." filament from sulfidic, briny seafloor sediments in the Gulf of Mexico

Directory of Open Access Journals (Sweden)

Verena Salman-Carvalho

2016-08-01

Full Text Available Candidatus Marithrix is a recently described lineage within the group of large sulfur bacteria (Beggiatoaceae, Gammaproteobacteria. This group of bacteria comprises vacuolated, attached-living filaments that inhabit the sediment surface around vent and seep sites in the marine environment. A single filament is ca. 100 µm in diameter, several millimeters long, and consists of hundreds of clonal cells, which are considered highly polyploid. Based on these characteristics, Candidatus Marithrix was used as a model organism for the assessment of genomic plasticity along segments of a single filament using next generation sequencing to possibly identify hotspots of microevolution. Using six consecutive segments of a single filament sampled from a mud volcano in the Gulf of Mexico, we recovered ca. 90% of the Candidatus Marithrix genome in each segment. There was a high level of genome conservation along the filament with average nucleotide identities between 99.98-100%. Different approaches to assemble all reads into a complete consensus genome could not fill the gaps. Each of the six segment datasets encoded merely a few hundred unique nucleotides and 5 or less unique genes - the residual content was redundant in all datasets. Besides the overall high genomic identity, we identified a similar number of single nucleotide polymorphisms (SNPs between the clonal segments, which are comparable to numbers reported for other clonal organisms. An increase of SNPs with greater distance of filament segments was not observed. The polyploidy of the cells was apparent when analyzing the heterogeneity of reads within a segment. Here, a strong increase in single nucleotide variants, or 'intrasegmental sequence heterogeneity' (ISH events, was observed. These sites may represent hotspots for genome plasticity, and possibly microevolution, since two thirds of these variants were not co-localized across the genome copies of the multicellular filament.

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

Segmenting health maintenance organizations to study productivity and profitability.

Science.gov (United States)

Sobol, M G

2000-01-01

As the decade ended, health maintenance organizations (HMOs) were increasing in popularity as a means of health care delivery. These groups take many forms, so it is important for the analyst to see if the efficiency and financial results for these different forms vary. The four major forms are profit vs. not-for-profit, chain vs. non-chain, group/staff vs. individual practice association (IPA), and federally qualified vs. non-federally qualified. Using a nationwide database of all the HMOs in the United States, the article compares liquidity rates, leverage ratios, profitability ratios, marketing, and per member ratios across the four groups using paired t tests. The two classifications that showed the most differences were group/staff vs. IPA and federally qualified vs. non-federally qualified. IPAs have a better liquidity position and lower leverage ratios than group/staff but their administrative costs are higher and the time to receive payments and to pay debts is higher. Non-federally qualified have somewhat higher liquidity ratios and higher profitability ratios. These significant differences in financial outcomes indicate that studies of HMOs should segment different major forms of organizations and study them separately before trying to show the effects of different policies on HMO efficiency and effectiveness.

Multi-organ segmentation from multi-phase abdominal CT via 4D graphs using enhancement, shape and location optimization.

Science.gov (United States)

Linguraru, Marius George; Pura, John A; Chowdhury, Ananda S; Summers, Ronald M

2010-01-01

The interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis (CAD) applications. Diagnosis also relies on the comprehensive analysis of multiple organs and quantitative measures of soft tissue. An automated method optimized for medical image data is presented for the simultaneous segmentation of four abdominal organs from 4D CT data using graph cuts. Contrast-enhanced CT scans were obtained at two phases: non-contrast and portal venous. Intra-patient data were spatially normalized by non-linear registration. Then 4D erosion using population historic information of contrast-enhanced liver, spleen, and kidneys was applied to multi-phase data to initialize the 4D graph and adapt to patient specific data. CT enhancement information and constraints on shape, from Parzen windows, and location, from a probabilistic atlas, were input into a new formulation of a 4D graph. Comparative results demonstrate the effects of appearance and enhancement, and shape and location on organ segmentation.

Atlas-based automatic segmentation of head and neck organs at risk and nodal target volumes: a clinical validation

International Nuclear Information System (INIS)

Daisne, Jean-François; Blumhofer, Andreas

2013-01-01

Intensity modulated radiotherapy for head and neck cancer necessitates accurate definition of organs at risk (OAR) and clinical target volumes (CTV). This crucial step is time consuming and prone to inter- and intra-observer variations. Automatic segmentation by atlas deformable registration may help to reduce time and variations. We aim to test a new commercial atlas algorithm for automatic segmentation of OAR and CTV in both ideal and clinical conditions. The updated Brainlab automatic head and neck atlas segmentation was tested on 20 patients: 10 cN0-stages (ideal population) and 10 unselected N-stages (clinical population). Following manual delineation of OAR and CTV, automatic segmentation of the same set of structures was performed and afterwards manually corrected. Dice Similarity Coefficient (DSC), Average Surface Distance (ASD) and Maximal Surface Distance (MSD) were calculated for “manual to automatic” and “manual to corrected” volumes comparisons. In both groups, automatic segmentation saved about 40% of the corresponding manual segmentation time. This effect was more pronounced for OAR than for CTV. The edition of the automatically obtained contours significantly improved DSC, ASD and MSD. Large distortions of normal anatomy or lack of iodine contrast were the limiting factors. The updated Brainlab atlas-based automatic segmentation tool for head and neck Cancer patients is timesaving but still necessitates review and corrections by an expert

Atlas-based automatic segmentation of head and neck organs at risk and nodal target volumes: a clinical validation.

Science.gov (United States)

Daisne, Jean-François; Blumhofer, Andreas

2013-06-26

Intensity modulated radiotherapy for head and neck cancer necessitates accurate definition of organs at risk (OAR) and clinical target volumes (CTV). This crucial step is time consuming and prone to inter- and intra-observer variations. Automatic segmentation by atlas deformable registration may help to reduce time and variations. We aim to test a new commercial atlas algorithm for automatic segmentation of OAR and CTV in both ideal and clinical conditions. The updated Brainlab automatic head and neck atlas segmentation was tested on 20 patients: 10 cN0-stages (ideal population) and 10 unselected N-stages (clinical population). Following manual delineation of OAR and CTV, automatic segmentation of the same set of structures was performed and afterwards manually corrected. Dice Similarity Coefficient (DSC), Average Surface Distance (ASD) and Maximal Surface Distance (MSD) were calculated for "manual to automatic" and "manual to corrected" volumes comparisons. In both groups, automatic segmentation saved about 40% of the corresponding manual segmentation time. This effect was more pronounced for OAR than for CTV. The edition of the automatically obtained contours significantly improved DSC, ASD and MSD. Large distortions of normal anatomy or lack of iodine contrast were the limiting factors. The updated Brainlab atlas-based automatic segmentation tool for head and neck Cancer patients is timesaving but still necessitates review and corrections by an expert.

Multi-granularity synthesis segmentation for high spatial resolution Remote sensing images

International Nuclear Information System (INIS)

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

2014-01-01

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

Mixed segmentation

DEFF Research Database (Denmark)

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

content analysis and audience segmentation in a single-source perspective. The aim is to explain and understand target groups in relation to, on the one hand, emotional response to commercials or other forms of audio-visual communication and, on the other hand, living preferences and personality traits...

Review of segmentation process in consumer markets

OpenAIRE

Veronika Jadczaková

2013-01-01

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

Deep learning of the sectional appearances of 3D CT images for anatomical structure segmentation based on an FCN voting method.

Science.gov (United States)

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

2017-10-01

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

Single- and dual energy QCT around acetabular cups in total hip arthroplasty using 3-dimensional segmentation

DEFF Research Database (Denmark)

Mussmann, Bo Redder; Andersen, Poul Erik; Torfing, Trine

of segmentation software and to compare bone mineral density (BMD) measurements in single- and dual energy CT (SECT and DECT) Materials and Methods: 24 male patients with total hip arthroplasty (12 cemented and 12 uncemented) were scanned and rescanned using SECT and virtual monochromatic DECT images. 3D- ROIs......Background: Bone density measurements around hip implants are challenged by artifacts and the complex anatomy of the acetabulum. We developed 3D segmentation software and used dual energy CT to reduce artifacts. Purpose / Aim of Study: To test the between-scan agreement and reliability...... the cemented cup the mean BMD for SECT was 523 mg/ccm with a between-scan difference of 14 mg/ccm, p=0.25 and 186 mg/ccm in DECT with a difference of 6 mg/ccm, p=0.15. ICC was >0.95 with more narrow limits of agreement in DECT compared with SECT. Computed tomography dose index (CTDI) was 25% higher with DECT...

Volume measurements of individual muscles in human quadriceps femoris using atlas-based segmentation approaches.

Science.gov (United States)

Le Troter, Arnaud; Fouré, Alexandre; Guye, Maxime; Confort-Gouny, Sylviane; Mattei, Jean-Pierre; Gondin, Julien; Salort-Campana, Emmanuelle; Bendahan, David

2016-04-01

Atlas-based segmentation is a powerful method for automatic structural segmentation of several sub-structures in many organs. However, such an approach has been very scarcely used in the context of muscle segmentation, and so far no study has assessed such a method for the automatic delineation of individual muscles of the quadriceps femoris (QF). In the present study, we have evaluated a fully automated multi-atlas method and a semi-automated single-atlas method for the segmentation and volume quantification of the four muscles of the QF and for the QF as a whole. The study was conducted in 32 young healthy males, using high-resolution magnetic resonance images (MRI) of the thigh. The multi-atlas-based segmentation method was conducted in 25 subjects. Different non-linear registration approaches based on free-form deformable (FFD) and symmetric diffeomorphic normalization algorithms (SyN) were assessed. Optimal parameters of two fusion methods, i.e., STAPLE and STEPS, were determined on the basis of the highest Dice similarity index (DSI) considering manual segmentation (MSeg) as the ground truth. Validation and reproducibility of this pipeline were determined using another MRI dataset recorded in seven healthy male subjects on the basis of additional metrics such as the muscle volume similarity values, intraclass coefficient, and coefficient of variation. Both non-linear registration methods (FFD and SyN) were also evaluated as part of a single-atlas strategy in order to assess longitudinal muscle volume measurements. The multi- and the single-atlas approaches were compared for the segmentation and the volume quantification of the four muscles of the QF and for the QF as a whole. Considering each muscle of the QF, the DSI of the multi-atlas-based approach was high 0.87 ± 0.11 and the best results were obtained with the combination of two deformation fields resulting from the SyN registration method and the STEPS fusion algorithm. The optimal variables for FFD

Segmenting hospitals for improved management strategy.

Science.gov (United States)

Malhotra, N K

1989-09-01

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

Integrated readout of organic scintillator and ZnS:Ag/6LiF for segmented antineutrino detectors

International Nuclear Information System (INIS)

Kiff, Scott D.; Reyna, David; Monahan, James; Bowden, Nathaniel S.

2010-01-01

Antineutrino detection using inverse beta decay conversion has demonstrated the capability to measure nuclear reactor power and fissile material content for nuclear safeguards. Current efforts focus on aboveground deployment scenarios, for which highly efficient capture and identification of neutrons is needed to measure the anticipated antineutrino event rates in an elevated background environment. In this submission, we report on initial characterization of a new scintillation-based segmented design that uses layers of ZnS:Ag/ 6 LiF and an integrated readout technique to capture and identify neutrons created in the inverse beta decay reaction. Laboratory studies with multiple organic scintillator and ZnS:Ag/ 6 LiF configurations reliably identify 6 Li neutron captures in 60 cm-long segments using pulse shape discrimination.

Wedged-shaped, segmental changes in the liver caused by occlusion of a single hepatic vein

International Nuclear Information System (INIS)

Kanazawa, Susumu; Akaki, Shiro; Yasui, Kotaro; Tanaka, Akio; Hiraki, Yoshio

1997-01-01

We evaluated wedged-shaped, segmental changes in the liver caused by occlusion of a single hepatic vein in seven patients. The causes of occlusion were due to liver tumors in three patients, metastasis of the right adrenal gland in one, and postoperative changes in three. Changes included low attenuating on unenhanced CT, high attenuation on enhanced CT, low signal intensity on T1-weighted MRI, high signal intensity on T2-weighted MRI, high signal intensity on enhanced MRI, dense hepatogram and retrograde arterioportal shunt on hepatic arteriography. MRI and hepatic arteriography are more sensitive than CT in demonstration of those changes. (author)

NMR relaxation of the orientation of single segments in semiflexible dendrimers

International Nuclear Information System (INIS)

Markelov, Denis A.; Gotlib, Yuli Ya.; Dolgushev, Maxim; Blumen, Alexander

2014-01-01

We study the orientational properties of labeled segments in semiflexible dendrimers making use of the viscoelastic approach of Dolgushev and Blumen [J. Chem. Phys. 131, 044905 (2009)]. We focus on the segmental orientational autocorrelation functions (ACFs), which are fundamental for the frequency-dependent spin-lattice relaxation times T 1 (ω). We show that semiflexibility leads to an increase of the contribution of large-scale motions to the ACF. This fact influences the position of the maxima of the [1/T 1 ]-functions. Thus, going from outer to inner segments, the maxima shift to lower frequencies. Remarkably, this feature is not obtained in the classical bead-spring model of flexible dendrimers, although many experiments on dendrimers manifest such a behavior

Light emission from organic single crystals operated by electrolyte doping

Science.gov (United States)

Matsuki, Keiichiro; Sakanoue, Tomo; Yomogida, Yohei; Hotta, Shu; Takenobu, Taishi

2018-03-01

Light-emitting devices based on electrolytes, such as light-emitting electrochemical cells (LECs) and electric double-layer transistors (EDLTs), are solution-processable devices with a very simple structure. Therefore, it is necessary to apply this device structure into highly fluorescent organic materials for future printed applications. However, owing to compatibility problems between electrolytes and organic crystals, electrolyte-based single-crystal light-emitting devices have not yet been demonstrated. Here, we report on light-emitting devices based on organic single crystals and electrolytes. As the fluorescent materials, α,ω-bis(biphenylyl)terthiophene (BP3T) and 5,6,11,12-tetraphenylnaphthacene (rubrene) single crystals were selected. Using ionic liquids as electrolytes, we observed clear light emission from BP3T LECs and rubrene EDLTs.

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.

WATERSHED ALGORITHM BASED SEGMENTATION FOR HANDWRITTEN TEXT IDENTIFICATION

Directory of Open Access Journals (Sweden)

P. Mathivanan

2014-02-01

Full Text Available In this paper we develop a system for writer identification which involves four processing steps like preprocessing, segmentation, feature extraction and writer identification using neural network. In the preprocessing phase the handwritten text is subjected to slant removal process for segmentation and feature extraction. After this step the text image enters into the process of noise removal and gray level conversion. The preprocessed image is further segmented by using morphological watershed algorithm, where the text lines are segmented into single words and then into single letters. The segmented image is feature extracted by Daubechies’5/3 integer wavelet transform to reduce training complexity [1, 6]. This process is lossless and reversible [10], [14]. These extracted features are given as input to our neural network for writer identification process and a target image is selected for each training process in the 2-layer neural network. With the several trained output data obtained from different target help in text identification. It is a multilingual text analysis which provides simple and efficient text segmentation.

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.

Proposal of a novel ensemble learning based segmentation with a shape prior and its application to spleen segmentation from a 3D abdominal CT volume

International Nuclear Information System (INIS)

Shindo, Kiyo; Shimizu, Akinobu; Kobatake, Hidefumi; Nawano, Shigeru; Shinozaki, Kenji

2010-01-01

An organ segmentation learned by a conventional ensemble learning algorithm suffers from unnatural errors because each voxel is classified independently in the segmentation process. This paper proposes a novel ensemble learning algorithm that can take into account global shape and location of organs. It estimates the shape and location of an organ from a given image by combining an intermediate segmentation result with a statistical shape model. Once an ensemble learning algorithm could not improve the segmentation performance in the iterative learning process, it estimates the shape and location by finding an optimal model parameter set with maximum degree of correspondence between a statistical shape model and the intermediate segmentation result. Novel weak classifiers are generated based on a signed distance from a boundary of the estimated shape and a distance from a barycenter of the intermediate segmentation result. Subsequently it continues the learning process with the novel weak classifiers. This paper presents experimental results where the proposed ensemble learning algorithm generates a segmentation process that can extract a spleen from a 3D CT image more precisely than a conventional one. (author)

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

Polarimetric Segmentation Using Wishart Test Statistic

DEFF Research Database (Denmark)

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

2002-01-01

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

Single-Molecule FISH Reveals Non-selective Packaging of Rift Valley Fever Virus Genome Segments

NARCIS (Netherlands)

Wichgers Schreur, Paul J.; Kortekaas, Jeroen

2016-01-01

The bunyavirus genome comprises a small (S), medium (M), and large (L) RNA segment of negative polarity. Although genome segmentation confers evolutionary advantages by enabling genome reassortment events with related viruses, genome segmentation also complicates genome replication and packaging.

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

Self-Structured Organizing Single-Input CMAC Control for Robot Manipulator

Directory of Open Access Journals (Sweden)

ThanhQuyen Ngo

2011-09-01

Full Text Available This paper represents a self-structured organizing single-input control system based on differentiable cerebellar model articulation controller (CMAC for an n-link robot manipulator to achieve the high-precision position tracking. In the proposed scheme, the single-input CMAC controller is solely used to control the plant, so the input space dimension of CMAC can be simplified and no conventional controller is needed. The structure of single-input CMAC will also be self-organized; that is, the layers of single-input CMAC will grow or prune systematically and their receptive functions can be automatically adjusted. The online tuning laws of single-input CMAC parameters are derived in gradient-descent learning method and the discrete-type Lyapunov function is applied to determine the learning rates of proposed control system so that the stability of the system can be guaranteed. The simulation results of robot manipulator are provided to verify the effectiveness of the proposed control methodology.

Unconditional and Conditional QTL Mapping for Tiller Numbers at Various Stages with Single Segment Substitution Lines in Rice (Oryza sativa L.)

Institute of Scientific and Technical Information of China (English)

ZHAO Fang-ming; LIU Gui-fu; ZHU Hai-tao; DING Xiao-hua; ZENG Rui-zhen; ZHANG Ze-min; LI Wen-tao; ZHANG Gui-quan

2008-01-01

Tiller is one of the most important agronomic traits which influences quantity and quality of effective panicles and finally influences yield in rice.It is important to understand "static" and "dynamic" information of the QTLs for tillers in rice.This work was the first time to simultaneously map unconditional and conditional QTLs for tiller numbers at various stages by using single segment substitution lines in rice.Fourteen QTLs for tiller number,distributing on the corresponding substitution segments of chromosomes 1,2,3,4,6,7 and 8 were detected.Both the number and the effect of the QTLs for tiller number were various at different stages,from 6 to 9 in the number and from 1.49 to 3.49 in the effect,respectively. Tiller number QTLs expressed in a time order,mainly detected at three stages of 0-7d,14-21d and 35-42d after transplanting with 6 positive,9 random and 6 negative expressing QTLs,respectively.Each of the QTLs expressed one time at least during the whole duration of rice.The tiller number at a specific stage was determined by sum of QTL effects estimated by the unconditional method,while the increasing or decreasing number in a given time interval was controlled by the total of QTL effects estimated by the conditional method.These results demonstrated that it is highly effective and accurate for mapping of the QTLs by using single segment substitution lines and the conditional analysis methodology.

Ordered macro-microporous metal-organic framework single crystals

KAUST Repository

Shen, Kui

2018-01-16

We constructed highly oriented and ordered macropores within metal-organic framework (MOF) single crystals, opening up the area of three-dimensional-ordered macro-microporous materials (that is, materials containing both macro- and micropores) in single-crystalline form. Our methodology relies on the strong shaping effects of a polystyrene nanosphere monolith template and a double-solvent-induced heterogeneous nucleation approach. This process synergistically enabled the in situ growth of MOFs within ordered voids, rendering a single crystal with oriented and ordered macro-microporous structure. The improved mass diffusion properties of such hierarchical frameworks, together with their robust single-crystalline nature, endow them with superior catalytic activity and recyclability for bulky-molecule reactions, as compared with conventional, polycrystalline hollow, and disordered macroporous ZIF-8.

Ordered macro-microporous metal-organic framework single crystals

Science.gov (United States)

Shen, Kui; Zhang, Lei; Chen, Xiaodong; Liu, Lingmei; Zhang, Daliang; Han, Yu; Chen, Junying; Long, Jilan; Luque, Rafael; Li, Yingwei; Chen, Banglin

2018-01-01

We constructed highly oriented and ordered macropores within metal-organic framework (MOF) single crystals, opening up the area of three-dimensional–ordered macro-microporous materials (that is, materials containing both macro- and micropores) in single-crystalline form. Our methodology relies on the strong shaping effects of a polystyrene nanosphere monolith template and a double-solvent–induced heterogeneous nucleation approach. This process synergistically enabled the in situ growth of MOFs within ordered voids, rendering a single crystal with oriented and ordered macro-microporous structure. The improved mass diffusion properties of such hierarchical frameworks, together with their robust single-crystalline nature, endow them with superior catalytic activity and recyclability for bulky-molecule reactions, as compared with conventional, polycrystalline hollow, and disordered macroporous ZIF-8.

Ordered macro-microporous metal-organic framework single crystals

KAUST Repository

Shen, Kui; Zhang, Lei; Chen, Xiaodong; Liu, Lingmei; Zhang, Daliang; Han, Yu; Chen, Junying; Long, Jilan; Luque, Rafael; Li, Yingwei; Chen, Banglin

2018-01-01

We constructed highly oriented and ordered macropores within metal-organic framework (MOF) single crystals, opening up the area of three-dimensional-ordered macro-microporous materials (that is, materials containing both macro- and micropores) in single-crystalline form. Our methodology relies on the strong shaping effects of a polystyrene nanosphere monolith template and a double-solvent-induced heterogeneous nucleation approach. This process synergistically enabled the in situ growth of MOFs within ordered voids, rendering a single crystal with oriented and ordered macro-microporous structure. The improved mass diffusion properties of such hierarchical frameworks, together with their robust single-crystalline nature, endow them with superior catalytic activity and recyclability for bulky-molecule reactions, as compared with conventional, polycrystalline hollow, and disordered macroporous ZIF-8.

ADVANCED CLUSTER BASED IMAGE SEGMENTATION

Directory of Open Access Journals (Sweden)

D. Kesavaraja

2011-11-01

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

Promotion of organic food in Serbia: Implications from organic food consumers' profile research

Directory of Open Access Journals (Sweden)

Đokić Ines

2014-01-01

Full Text Available The article presents the results of the research of organic food frequency of consumption (in general, conducted in Serbia in June 2013 (n=300. Respondents were classified into low-frequent organic food consumers' segment and high-frequent organic food consumers' segment. Socio-demographic characteristics of respondents were also investigated, thus allowing comparing two segments regarding consumers' profile. The organic food high-frequent consumers' segment consisted of more women, more educated people, more married respondents and respondents living with children and having larger households, as well as of consumers with higher self-assessed household income in comparison to organic food low-frequent consumers' segment. Having in mind the results of the research and the level of domestic market development when choosing which segment to target, as well as starting from understanding promotion in the context of integrated marketing communication and the means-end approach to consumer behavior, recommendations for organic food promotion were given.

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.)

Solution-grown organic single-crystalline p-n junctions with ambipolar charge transport.

Science.gov (United States)

Fan, Congcheng; Zoombelt, Arjan P; Jiang, Hao; Fu, Weifei; Wu, Jiake; Yuan, Wentao; Wang, Yong; Li, Hanying; Chen, Hongzheng; Bao, Zhenan

2013-10-25

Organic single-crystalline p-n junctions are grown from mixed solutions. First, C60 crystals (n-type) form and, subsequently, C8-BTBT crystals (p-type) nucleate heterogeneously on the C60 crystals. Both crystals continue to grow simultaneously into single-crystalline p-n junctions that exhibit ambipolar charge transport characteristics. This work provides a platform to study organic single-crystalline p-n junctions. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Figure-ground segmentation can occur without attention.

Science.gov (United States)

Kimchi, Ruth; Peterson, Mary A

2008-07-01

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

Azeotropic binary solvent mixtures for preparation of organic single crystals

NARCIS (Netherlands)

Li, X.; Kjellander, B.K.C.; Anthony, J.E.; Bastiaansen, C.W.M.; Broer, D.J.; Gelinck, G.H.

2009-01-01

Here, a new approach is introduced to prepare large single crystals of π-conjugated organic molecules from solution. Utilizing the concept of azeotropism, single crystals of tri-isopropylsilylethynyl pentacene (TIPS-PEN) with dimensions up to millimeters are facilely self-assembled from homogeneous

Azeotropic binary solvent mixtures for preparation of organic single crystals

NARCIS (Netherlands)

Li, X.; Kjellander, B.K.C.; Anthony, J.E.; Bastiaansen, C.W.M.; Broer, D.J.; Gelinck, G.H.

2009-01-01

Here, a new approach is introduced to prepare large single crystals of p-conjugated organic molecules from solution. Utilizing the concept of azeotropism, single crystals of tri-isopropylsilylethynyl pentacene (TIPS-PEN) with dimensions up to millimeters are facilely self-assembled from homogeneous

Single locus affects embryonic segment polarity and multiple aspects of an adult evolutionary novelty

Directory of Open Access Journals (Sweden)

Saenko Suzanne V

2010-08-01

Full Text Available Abstract Background The characterization of the molecular changes that underlie the origin and diversification of morphological novelties is a key challenge in evolutionary developmental biology. The evolution of such traits is thought to rely largely on co-option of a toolkit of conserved developmental genes that typically perform multiple functions. Mutations that affect both a universal developmental process and the formation of a novelty might shed light onto the genetics of traits not represented in model systems. Here we describe three pleiotropic mutations with large effects on a novel trait, butterfly eyespots, and on a conserved stage of embryogenesis, segment polarity. Results We show that three mutations affecting eyespot size and/or colour composition in Bicyclus anynana butterflies occurred in the same locus, and that two of them are embryonic recessive lethal. Using surgical manipulations and analysis of gene expression patterns in developing wings, we demonstrate that the effects on eyespot morphology are due to changes in the epidermal response component of eyespot induction. Our analysis of morphology and of gene expression in mutant embryos shows that they have a typical segment polarity phenotype, consistent with the mutant locus encoding a negative regulator of Wingless signalling. Conclusions This study characterizes the segregation and developmental effects of alleles at a single locus that controls the morphology of a lineage-specific trait (butterfly eyespots and a conserved process (embryonic segment polarity and, specifically, the regulation of Wingless signalling. Because no gene with such function was found in the orthologous, highly syntenic genomic regions of two other lepidopterans, we hypothesize that our locus is a yet undescribed, possibly lineage-specific, negative regulator of the conserved Wnt/Wg pathway. Moreover, the fact that this locus interferes with multiple aspects of eyespot morphology and maps to a

Medical image segmentation using genetic algorithms.

Science.gov (United States)

Maulik, Ujjwal

2009-03-01

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

Crosstalk corrections for improved energy resolution with highly segmented HPGe-detectors

International Nuclear Information System (INIS)

Bruyneel, Bart; Reiter, Peter; Wiens, Andreas; Eberth, Juergen; Hess, Herbert; Pascovici, Gheorghe; Warr, Nigel; Aydin, Sezgin; Bazzacco, Dino; Recchia, Francesco

2009-01-01

Crosstalk effects of 36-fold segmented, large volume AGATA HPGe detectors cause shifts in the γ-ray energy measured by the inner core and outer segments as function of segment multiplicity. The positions of the segment sum energy peaks vary approximately linearly with increasing segment multiplicity. The resolution of these peaks deteriorates also linearly as a function of segment multiplicity. Based on single event treatment, two methods were developed in the AGATA Collaboration to correct for the crosstalk induced effects by employing a linear transformation. The matrix elements are deduced from coincidence measurements of γ-rays of various energies as recorded with digital electronics. A very efficient way to determine the matrix elements is obtained by measuring the base line shifts of untriggered segments using γ-ray detection events in which energy is deposited in a single segment. A second approach is based on measuring segment energy values for γ-ray interaction events in which energy is deposited in only two segments. After performing crosstalk corrections, the investigated detector shows a good fit between the core energy and the segment sum energy at all multiplicities and an improved energy resolution of the segment sum energy peaks. The corrected core energy resolution equals the segment sum energy resolution which is superior at all folds compared to the individual uncorrected energy resolutions. This is achieved by combining the two independent energy measurements with the core contact on the one hand and the segment contacts on the other hand.

Benefit segmentation of the fitness market.

Science.gov (United States)

Brown, J D

1992-01-01

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

Review of segmentation process in consumer markets

Directory of Open Access Journals (Sweden)

Veronika Jadczaková

2013-01-01

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

Deformable M-Reps for 3D Medical Image Segmentation

Science.gov (United States)

Pizer, Stephen M.; Fletcher, P. Thomas; Joshi, Sarang; Thall, Andrew; Chen, James Z.; Fridman, Yonatan; Fritsch, Daniel S.; Gash, Graham; Glotzer, John M.; Jiroutek, Michael R.; Lu, Conglin; Muller, Keith E.; Tracton, Gregg; Yushkevich, Paul; Chaney, Edward L.

2013-01-01

M-reps (formerly called DSLs) are a multiscale medial means for modeling and rendering 3D solid geometry. They are particularly well suited to model anatomic objects and in particular to capture prior geometric information effectively in deformable models segmentation approaches. The representation is based on figural models, which define objects at coarse scale by a hierarchy of figures – each figure generally a slab representing a solid region and its boundary simultaneously. This paper focuses on the use of single figure models to segment objects of relatively simple structure. A single figure is a sheet of medial atoms, which is interpolated from the model formed by a net, i.e., a mesh or chain, of medial atoms (hence the name m-reps), each atom modeling a solid region via not only a position and a width but also a local figural frame giving figural directions and an object angle between opposing, corresponding positions on the boundary implied by the m-rep. The special capability of an m-rep is to provide spatial and orientational correspondence between an object in two different states of deformation. This ability is central to effective measurement of both geometric typicality and geometry to image match, the two terms of the objective function optimized in segmentation by deformable models. The other ability of m-reps central to effective segmentation is their ability to support segmentation at multiple levels of scale, with successively finer precision. Objects modeled by single figures are segmented first by a similarity transform augmented by object elongation, then by adjustment of each medial atom, and finally by displacing a dense sampling of the m-rep implied boundary. While these models and approaches also exist in 2D, we focus on 3D objects. The segmentation of the kidney from CT and the hippocampus from MRI serve as the major examples in this paper. The accuracy of segmentation as compared to manual, slice-by-slice segmentation is reported. PMID

Algorithms for Cytoplasm Segmentation of Fluorescence Labelled Cells

Directory of Open Access Journals (Sweden)

Carolina Wählby

2002-01-01

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

An Improved Random Walker with Bayes Model for Volumetric Medical Image Segmentation

Directory of Open Access Journals (Sweden)

Chunhua Dong

2017-01-01

Full Text Available Random walk (RW method has been widely used to segment the organ in the volumetric medical image. However, it leads to a very large-scale graph due to a number of nodes equal to a voxel number and inaccurate segmentation because of the unavailability of appropriate initial seed point setting. In addition, the classical RW algorithm was designed for a user to mark a few pixels with an arbitrary number of labels, regardless of the intensity and shape information of the organ. Hence, we propose a prior knowledge-based Bayes random walk framework to segment the volumetric medical image in a slice-by-slice manner. Our strategy is to employ the previous segmented slice to obtain the shape and intensity knowledge of the target organ for the adjacent slice. According to the prior knowledge, the object/background seed points can be dynamically updated for the adjacent slice by combining the narrow band threshold (NBT method and the organ model with a Gaussian process. Finally, a high-quality image segmentation result can be automatically achieved using Bayes RW algorithm. Comparing our method with conventional RW and state-of-the-art interactive segmentation methods, our results show an improvement in the accuracy for liver segmentation (p<0.001.

Three-dimensional charge transport in organic semiconductor single crystals.

Science.gov (United States)

He, Tao; Zhang, Xiying; Jia, Jiong; Li, Yexin; Tao, Xutang

2012-04-24

Three-dimensional charge transport anisotropy in organic semiconductor single crystals - both plates and rods (above and below, respectively, in the figure) - is measured in well-performing organic field-effect transistors for the first time. The results provide an excellent model for molecular design and device preparation that leads to good performance. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Segmenting patients and physicians using preferences from discrete choice experiments.

Science.gov (United States)

Deal, Ken

2014-01-01

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

A simple method for microtuber production in dioscorea opposita using single nodal segments

International Nuclear Information System (INIS)

Li, M.; Wang, Y; Liu, W.; Li, S.

2015-01-01

Dioscorea opposita Thunb. (Chinese yam) is an important tuber crop in East Asia because of its dual benefits edible and medicinal properties. Microtubers may provide a feasible alternative to in-vitro-grown plantlets as a means of micropropagation and a way to exchange healthy planting material. In this study, we have developed a simplified culture method for In vitro production of microtubers from D. opposita cv. Tiegun. In this method, microtubers formed in 98% of the internodes of single nodal segments after four weeks of dark-incubation when cultured in MS medium supplemented with 60 g sucrose 1-1 with shaking. Anatomical observations strongly supported the process of tuberization. We also found that 66% of the microtubers produced In vitro sprouted two months after transfer to vermiculite. The protocol presented here provides a simple model for studying the physiological, biochemical, and molecular mechanisms of tuberization in D. opposita, and shows good potential for large-scale production of microtubers as well. (author)

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

Robust medical image segmentation for hyperthermia treatment planning

International Nuclear Information System (INIS)

Neufeld, E.; Chavannes, N.; Kuster, N.; Samaras, T.

2005-01-01

complexity of medical images and their often low quality, automatic techniques rarely yield satisfactory results. While they can be used to extract simple structures (e.g., bones) they do not work when confronted with structures that lack clear borders or homogeneous characteristics. Therefore it is recommended to apply them for simple structures only (as found in the leg), while otherwise relying on interactive methods. Both competitive seeded methods (this includes the interactive watershed transformation) and live-wire seem to be well suited for the interactive segmentation. Ideal segmentation routines should make use of both region and boundary information. For most techniques only 2D segmentation of individual slices is feasible within a reasonable amount of time. 3D segmentation can only be performed for the simplest methods. It is planned to couple interpolation to level-set methods or live-wire, so that the interactive segmentation need not to be performed on every single slice. The user should combine the various methods to quickly obtain satisfactory results and correctly use the power provided by the toolbox. (A possible step-by-step procedure could include the following steps: pre-processing, then an automatic method to distinguish fat, muscle and bone, followed by interactive methods to outline various organs, possibly using interpolation to reduce the amount of interaction.) A standard procedure thus needs to be established which physicians can follow. The implemented toolbox offers a good environment to quickly prototype new segmentation techniques and combine them flexibly with the large number of existing techniques. This is needed to generate very detailed patient models. The ability of the toolbox to work with various competing tissues at the same time increases its robustness. The presence of both automatic and semi-automatic, interactive methods gives the user a high degree of flexibility. (author)

Unfolding Implementation in Industrial Market Segmentation

DEFF Research Database (Denmark)

Bøjgaard, John; Ellegaard, Chris

2011-01-01

to pave the way towards closing this gap. The extent of implementation coverage is assessed and various notions of implementation are identified. Implementation as the task of converting segmentation plans into action (referred to as execution) is identified as a particularly beneficial focus area...... for marketing management. Three key elements and challenges connected to execution of market segmentation are identified — organization, motivation, and adaptation....

Threshold and maximum power evolution of stimulated Brillouin scattering and Rayleigh backscattering in a single mode fiber segment

International Nuclear Information System (INIS)

Sanchez-Lara, R; Alvarez-Chavez, J A; Mendez-Martinez, F; De la Cruz-May, L; Perez-Sanchez, G G

2015-01-01

The behavior of stimulated Brillouin scattering (SBS) and Rayleigh backscattering phenomena, which limit the forward transmission power in modern, ultra-long haul optical communication systems such as dense wavelength division multiplexing systems is analyzed via simulation and experimental investigation of threshold and maximum power. Evolution of SBS, Rayleigh scattering and forward powers are experimentally investigated with a 25 km segment of single mode fiber. Also, a simple algorithm to predict the generation of SBS is proposed where two criteria of power thresholds was used for comparison with experimental data. (paper)

Evaluation of an automatic segmentation algorithm for definition of head and neck organs at risk.

Science.gov (United States)

Thomson, David; Boylan, Chris; Liptrot, Tom; Aitkenhead, Adam; Lee, Lip; Yap, Beng; Sykes, Andrew; Rowbottom, Carl; Slevin, Nicholas

2014-08-03

The accurate definition of organs at risk (OARs) is required to fully exploit the benefits of intensity-modulated radiotherapy (IMRT) for head and neck cancer. However, manual delineation is time-consuming and there is considerable inter-observer variability. This is pertinent as function-sparing and adaptive IMRT have increased the number and frequency of delineation of OARs. We evaluated accuracy and potential time-saving of Smart Probabilistic Image Contouring Engine (SPICE) automatic segmentation to define OARs for salivary-, swallowing- and cochlea-sparing IMRT. Five clinicians recorded the time to delineate five organs at risk (parotid glands, submandibular glands, larynx, pharyngeal constrictor muscles and cochleae) for each of 10 CT scans. SPICE was then used to define these structures. The acceptability of SPICE contours was initially determined by visual inspection and the total time to modify them recorded per scan. The Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm created a reference standard from all clinician contours. Clinician, SPICE and modified contours were compared against STAPLE by the Dice similarity coefficient (DSC) and mean/maximum distance to agreement (DTA). For all investigated structures, SPICE contours were less accurate than manual contours. However, for parotid/submandibular glands they were acceptable (median DSC: 0.79/0.80; mean, maximum DTA: 1.5 mm, 14.8 mm/0.6 mm, 5.7 mm). Modified SPICE contours were also less accurate than manual contours. The utilisation of SPICE did not result in time-saving/improve efficiency. Improvements in accuracy of automatic segmentation for head and neck OARs would be worthwhile and are required before its routine clinical implementation.

Application of maximum entropy to statistical inference for inversion of data from a single track segment.

Science.gov (United States)

Stotts, Steven A; Koch, Robert A

2017-08-01

In this paper an approach is presented to estimate the constraint required to apply maximum entropy (ME) for statistical inference with underwater acoustic data from a single track segment. Previous algorithms for estimating the ME constraint require multiple source track segments to determine the constraint. The approach is relevant for addressing model mismatch effects, i.e., inaccuracies in parameter values determined from inversions because the propagation model does not account for all acoustic processes that contribute to the measured data. One effect of model mismatch is that the lowest cost inversion solution may be well outside a relatively well-known parameter value's uncertainty interval (prior), e.g., source speed from track reconstruction or towed source levels. The approach requires, for some particular parameter value, the ME constraint to produce an inferred uncertainty interval that encompasses the prior. Motivating this approach is the hypothesis that the proposed constraint determination procedure would produce a posterior probability density that accounts for the effect of model mismatch on inferred values of other inversion parameters for which the priors might be quite broad. Applications to both measured and simulated data are presented for model mismatch that produces minimum cost solutions either inside or outside some priors.

Modeling the Sedimentary Infill of Lakes in the East African Rift: A Case Study of Multiple versus Single Rift Basin Segments

Science.gov (United States)

Zhang, C.; Scholz, C. A.

2016-12-01

The sedimentary basins in the East African Rift are considered excellent modern examples for investigating sedimentary infilling and evolution of extensional systems. Some lakes in the western branch of the rift have formed within single-segment systems, and include Lake Albert and Lake Edward. The largest and oldest lakes developed within multi-segment systems, and these include Lake Tanganyika and Lake Malawi. This research aims to explore processes of erosion and sedimentary infilling of the catchment area in single-segment rift (SSR) and multi-segment rift (MSR) systems. We consider different conditions of regional precipitation and evaporation, and assess the resulting facies architecture through forward modeling, using state-of-the-art commercial basin modeling software. Dionisos is a three-dimensional numerical stratigraphic forward modeling software program, which simulates basin-scale sediment transport based on empirical water- and gravity-driven diffusion equations. It was classically used to quantify the sedimentary architecture and basin infilling of both marine siliciclastic and carbonate environments. However, we apply this approach to continental rift basin environments. In this research, two scenarios are developed, one for a MSR and the other for a SSR. The modeled systems simulate the ratio of drainage area and lake surface area observed in modern Lake Tanganyika and Lake Albert, which are examples of MSRs and SSRs, respectively. The main parameters, such as maximum subsidence rate, water- and gravity-driven diffusion coefficients, rainfall, and evaporation, are approximated using these real-world examples. The results of 5 million year model runs with 50,000 year time steps show that MSRs are characterized by a deep water lake with relatively modest sediment accumulation, while the SSRs are characterized by a nearly overfilled lake with shallow water depths and thick sediment accumulation. The preliminary modeling results conform to the features

Skin Segmentation Based on Graph Cuts

Institute of Scientific and Technical Information of China (English)

HU Zhilan; WANG Guijin; LIN Xinggang; YAN Hong

2009-01-01

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

Automatic segmentation of psoriasis lesions

Science.gov (United States)

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

2014-10-01

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

Image segmentation algorithm based on T-junctions cues

Science.gov (United States)

Qian, Yanyu; Cao, Fengyun; Wang, Lu; Yang, Xuejie

2016-03-01

To improve the over-segmentation and over-merge phenomenon of single image segmentation algorithm,a novel approach of combing Graph-Based algorithm and T-junctions cues is proposed in this paper. First, a method by L0 gradient minimization is applied to the smoothing of the target image eliminate artifacts caused by noise and texture detail; Then, the initial over-segmentation result of the smoothing image using the graph-based algorithm; Finally, the final results via a region fusion strategy by t-junction cues. Experimental results on a variety of images verify the new approach's efficiency in eliminating artifacts caused by noise,segmentation accuracy and time complexity has been significantly improved.

Multiple Segmentation of Image Stacks

DEFF Research Database (Denmark)

Smets, Jonathan; Jaeger, Manfred

2014-01-01

We propose a method for the simultaneous construction of multiple image segmentations by combining a recently proposed “convolution of mixtures of Gaussians” model with a multi-layer hidden Markov random field structure. The resulting method constructs for a single image several, alternative...

Assembly of Nanoscale Organic Single-Crystal Cross-Wire Circuits

DEFF Research Database (Denmark)

Bjørnholm, Thomas

2009-01-01

Organic single-crystal transistors and circuits can be assembled by nanomechanical manipulation of nanowires of CuPc, F(16)CuPc, and SnO(2):Sb. The crossed bar devices have low operational voltage, high mobility and are stable in air. They can be combined into circuits, providing varied functions...... including inverters and NOR and NAND logic gates, opening new opportunities for organic nanoelectronics and highly sophisticated integrated logic devices....

29 CFR 779.223 - Control where ownership vested in individual or single organization.

Science.gov (United States)

2010-07-01

... single business organization. Ownership sufficient to exercise “control” exist also where there is more... in individual or single organization. Ownership, sufficient to exercise “control,” of course, exists... “control” may exist with much more limited ownership, and, in certain cases exists in the absence of any...

Forming a three-dimensional porous organic network via solid-state explosion of organic single crystals.

Science.gov (United States)

Bae, Seo-Yoon; Kim, Dongwook; Shin, Dongbin; Mahmood, Javeed; Jeon, In-Yup; Jung, Sun-Min; Shin, Sun-Hee; Kim, Seok-Jin; Park, Noejung; Lah, Myoung Soo; Baek, Jong-Beom

2017-11-17

Solid-state reaction of organic molecules holds a considerable advantage over liquid-phase processes in the manufacturing industry. However, the research progress in exploring this benefit is largely staggering, which leaves few liquid-phase systems to work with. Here, we show a synthetic protocol for the formation of a three-dimensional porous organic network via solid-state explosion of organic single crystals. The explosive reaction is realized by the Bergman reaction (cycloaromatization) of three enediyne groups on 2,3,6,7,14,15-hexaethynyl-9,10-dihydro-9,10-[1,2]benzenoanthracene. The origin of the explosion is systematically studied using single-crystal X-ray diffraction and differential scanning calorimetry, along with high-speed camera and density functional theory calculations. The results suggest that the solid-state explosion is triggered by an abrupt change in lattice energy induced by release of primer molecules in the 2,3,6,7,14,15-hexaethynyl-9,10-dihydro-9,10-[1,2]benzenoanthracene crystal lattice.

Self-assembling segmented coiled tubing

Science.gov (United States)

Raymond, David W.

2016-09-27

Self-assembling segmented coiled tubing is a concept that allows the strength of thick-wall rigid pipe, and the flexibility of thin-wall tubing, to be realized in a single design. The primary use is for a drillstring tubular, but it has potential for other applications requiring transmission of mechanical loads (forces and torques) through an initially coiled tubular. The concept uses a spring-loaded spherical `ball-and-socket` type joint to interconnect two or more short, rigid segments of pipe. Use of an optional snap ring allows the joint to be permanently made, in a `self-assembling` manner.

Whole-organ and segmental stiffness measured with liver magnetic resonance elastography in healthy adults: significance of the region of interest.

Science.gov (United States)

Rusak, Grażyna; Zawada, Elżbieta; Lemanowicz, Adam; Serafin, Zbigniew

2015-04-01

MR elastography (MRE) is a recent non-invasive technique that provides in vivo data on the viscoelasticity of the liver. Since the method is not well established, several different protocols were proposed that differ in results. The aim of the study was to analyze the variability of stiffness measurements in different regions of the liver. Twenty healthy adults aged 24-45 years were recruited. The examination was performed using a mechanical excitation of 64 Hz. MRE images were fused with axial T2WI breath-hold images (thickness 10 mm, spacing 10 mm). Stiffness was measured as a mean value of each cross section of the whole liver, on a single largest cross section, in the right lobe, and in ROIs (50 pix.) placed in the center of the left lobe, segments 5/6, 7, 8, and the parahilar region. Whole-liver stiffness ranged from 1.56 to 2.75 kPa. Mean segmental stiffness differed significantly between the tested regions (range from 1.55 ± 0.28 to 2.37 ± 0.32 kPa; P < 0.0001, ANOVA). Within-method variability of measurements ranged from 14 % for whole liver and segment 8-26 % for segment 7. Within-subject variability ranged from 13 to 31 %. Results of measurement within segment 8 were closest to the whole-liver method (ICC, 0.84). Stiffness of the liver presented significant variability depending on the region of measurement. The most reproducible method is averaging of cross sections of the whole liver. There was significant variability between stiffness in subjects considered healthy, which requires further investigation.

Remote sensing image segmentation based on Hadoop cloud platform

Science.gov (United States)

Li, Jie; Zhu, Lingling; Cao, Fubin

2018-01-01

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

The head problem. The organizational significance of segmentation in head development.

Science.gov (United States)

Horder, Tim J; Presley, Robert; Slípka, Jaroslav

2010-01-01

This review argues for the segmental basis of chordate head organization which, like somite-based segmental organization in the trunk, takes its origin from early mesodermal development. The review builds on, and brings up to date, Goodrich's well-known scheme of head organization. It surveys recent data in support of this scheme and shows how evidence and arguments supposedly in conflict with it can be accommodated. Many of the arguments revolve around matters of methodology; the limitations of older LM, SEM (on which the concept of "somitomeres" is based) and recent molecular evidence (which has sometimes been seen as allocating the central role in head organization to the CNS and the neural crest) are highlighted and shown to explain a number of claims contrary to Goodrich's. We provide (in Part 2) a new, comparative survey of the best available evidence most directly relevant to the Goodrich Bauplan, with a special emphasis on stem chordates. The postotic region has commonly been seen as segmentally organized: the critical issues concern the preotic region. There are many reasons why Goodrich's three preotic segments may become specialized during evolution and why the underlying initial segmental organization may be overridden in later stages during embryonic development; we refer to a number of these. We conclude that the preotic segmental Bauplan is remarkably conserved and most explicitly demonstrated among stem forms, but we also suggest that the concept of the prechordal plate requires careful reexamination. Central to our overall analysis is the importance of the epigenetic nature of embryogenesis; its implications are made clear. Finally we speculate on evolutionary implications for the origin of the head and its specialized features. The review is intended to serve as a resource giving access to references to a wealth of now neglected, older data on anamniote embryology.

Evaluation of an atlas-based automatic segmentation software for the delineation of brain organs at risk in a radiation therapy clinical context

International Nuclear Information System (INIS)

Isambert, Aurelie; Dhermain, Frederic; Bidault, Francois; Commowick, Olivier; Bondiau, Pierre-Yves; Malandain, Gregoire; Lefkopoulos, Dimitri

2008-01-01

Background and purpose: Conformal radiation therapy techniques require the delineation of volumes of interest, a time-consuming and operator-dependent task. In this work, we aimed to evaluate the potential interest of an atlas-based automatic segmentation software (ABAS) of brain organs at risk (OAR), when used under our clinical conditions. Materials and methods: Automatic and manual segmentations of the eyes, optic nerves, optic chiasm, pituitary gland, brain stem and cerebellum of 11 patients on T1-weighted magnetic resonance, 3-mm thick slice images were compared using the Dice similarity coefficient (DSC). The sensitivity and specificity of the ABAS were also computed and analysed from a radiotherapy point of view by splitting the ROC (Receiver Operating Characteristic) space into four sub-regions. Results: Automatic segmentation of OAR was achieved in 7-8 min. Excellent agreement was obtained between automatic and manual delineations for organs exceeding 7 cm 3 : the DSC was greater than 0.8. For smaller structures, the DSC was lower than 0.41. Conclusions: These tests demonstrated that this ABAS is a robust and reliable tool for automatic delineation of large structures under clinical conditions in our daily practice, even though the small structures must continue to be delineated manually by an expert

Rotational manipulation of single cells and organisms using acoustic waves.

Science.gov (United States)

Ahmed, Daniel; Ozcelik, Adem; Bojanala, Nagagireesh; Nama, Nitesh; Upadhyay, Awani; Chen, Yuchao; Hanna-Rose, Wendy; Huang, Tony Jun

2016-03-23

The precise rotational manipulation of single cells or organisms is invaluable to many applications in biology, chemistry, physics and medicine. In this article, we describe an acoustic-based, on-chip manipulation method that can rotate single microparticles, cells and organisms. To achieve this, we trapped microbubbles within predefined sidewall microcavities inside a microchannel. In an acoustic field, trapped microbubbles were driven into oscillatory motion generating steady microvortices which were utilized to precisely rotate colloids, cells and entire organisms (that is, C. elegans). We have tested the capabilities of our method by analysing reproductive system pathologies and nervous system morphology in C. elegans. Using our device, we revealed the underlying abnormal cell fusion causing defective vulval morphology in mutant worms. Our acoustofluidic rotational manipulation (ARM) technique is an easy-to-use, compact, and biocompatible method, permitting rotation regardless of optical, magnetic or electrical properties of the sample under investigation.

Single Shell Tank Waste Characterization Project for Tank B-110, Core 9 - data package and PNL validation summary report

International Nuclear Information System (INIS)

Pool, K.N.; Jones, T.E.; McKinley, S.G.; Tingey, J.M.; Longaker, T.M.; Gibson, J.A.

1990-01-01

This Data Package contains results obtained by Pacific Northwest Laboratory (PNL) staff in the characterization and analyses of Core 9 segments taken from the Single-Shell Tank (SST) 110B. The characterization and analysis of Core 9 segments are outlined in the Waste Characterization Plan for Hanford Site Single-Shell Tanks and in the Pacific Northwest Laboratory (PNL) Single-Shell Tank Waste Characterization Support FY 89/90 Statement of Work (SOW), Rev. 1 dated March, 1990. Specific analyses for each sub-sample taken from a segment are delineated in Test Instructions prepared by the PNL Single-Shell Tank Waste Characterization Project Management Office (SST Project) in accordance with procedures contained in the SST Waste Characterization Procedure Compendium (PNL-MA-599). Analytical procedures used in the characterization activities are also included in PNL-MA-599. Core 9 included five segments although segment 1 did not have sufficient material for characterization. The five samplers were received from Westinghouse Hanford Company (WHC) on 11/21-22/89. Each segment was contained in a sampler and was enclosed in a shipping cask. The shipping cask was butted up to the 325-A hot cell and the sampler moved into the hot cell. The material in the sampler (i.e., the segment) was extruded from the sampler, limited physical characteristics assessed, and photographed. At this point samples were taken for particle size and volatile organic analyses. Each segment was then homogenized. Sub-samples were taken for required analyses as delineated in the appropriate Test Instruction. Table 1 includes sample numbers assigned to Core 9 segment materials being transferred from 325-A Hot Cell. Sample numbers 90-0298, 90-0299, 90-0302, and 90-0303 were included in Table 1 although no analyses were requested for these samples. Table 2 lists Core 9 sub-sample numbers per sample preparation method

Possible words and fixed stress in the segmentation of Slovak speech.

Science.gov (United States)

Hanulíková, Adriana; McQueen, James M; Mitterer, Holger

2010-03-01

The possible-word constraint (PWC; Norris, McQueen, Cutler, & Butterfield, 1997) has been proposed as a language-universal segmentation principle: Lexical candidates are disfavoured if the resulting segmentation of continuous speech leads to vowelless residues in the input-for example, single consonants. Three word-spotting experiments investigated segmentation in Slovak, a language with single-consonant words and fixed stress. In Experiment 1, Slovak listeners detected real words such as ruka "hand" embedded in prepositional-consonant contexts (e.g., /gruka/) faster than those in nonprepositional-consonant contexts (e.g., /truka/) and slowest in syllable contexts (e.g., /dugruka/). The second experiment controlled for effects of stress. Responses were still fastest in prepositional-consonant contexts, but were now slowest in nonprepositional-consonant contexts. In Experiment 3, the lexical and syllabic status of the contexts was manipulated. Responses were again slowest in nonprepositional-consonant contexts but equally fast in prepositional-consonant, prepositional-vowel, and nonprepositional-vowel contexts. These results suggest that Slovak listeners use fixed stress and the PWC to segment speech, but that single consonants that can be words have a special status in Slovak segmentation. Knowledge about what constitutes a phonologically acceptable word in a given language therefore determines whether vowelless stretches of speech are or are not treated as acceptable parts of the lexical parse.

Improving image segmentation by learning region affinities

Energy Technology Data Exchange (ETDEWEB)

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

2010-11-03

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

Digging deeper: How do different types of organic consumers influence the increasing organic market share?

DEFF Research Database (Denmark)

Andersen, Laura Mørch; Lund, Thomas Bøker

2014-01-01

Purpose – This article aims to investigate how sub-markets with different degrees of maturity develop during a period of general organic growth, and how different consumer segments behave on these sub-markets. Design/methodology/approach – This paper uses actual purchasing behaviour of six consumer...... segments with different attitudes towards food in general, and organic production and products in particular. The data is from the Danish market for organic foods, which is one of the most mature markets in the world. Findings – The segmentation splits consumers into a positive and a non-positive half......, each half consisting of three different segments. The estimations show that the development in general organic consumption varies between segments, and that their behaviour varies between sub-markets. The positive half of the population has driven the overall growth in organic budget share...

Evolution of segmental anesthesia for Laparo-Endoscopic Single Site (LESS) cholecystectomy.

Science.gov (United States)

Ross, S B; Mangar, D; Karlnoski, R; Patel, R S; Camporesi, E M; Barry, L K; Luberice, K; Sprenker, C J; Rosemurgy, A S

2012-06-01

Transumbilical Laparo-Endoscopic Single Site (LESS) surgery promises improved cosmesis, quick recovery, reduced postoperative pain and shorter length of hospital stay. Since only a simple umbilical incision is used, LESS surgery can be completed with segmental epidural anesthesia. This study describes the evolution of our technique of LESS cholecystectomy from a combination of spinal and epidural anesthesia to thoracic epidural alone and presents our experience with its safety, the observed morbidity, and the reported patient satisfaction. In August 2009, a prospective evaluation of LESS cholecystectomy with regional anesthesia was undertaken. We recruited patients with chronic cholecystitis or symptomatic cholelithasis. Blood loss, operative time, complications, and length of hospital stay were measured. Preoperatively and 14 days postoperatively, outcome and symptom resolution were scored. Fifteen consecutive patients underwent LESS cholecystectomy; first with combined spinal-epidural (CSE), and then with thoracic epidural anesthesia alone. Immediate postoperative pain and discomfort were well tolerated. VAS scores upon admission to PACU were 0.4 (1.7±2.2). At postoperative day 14, the patients scored high values for "Satisfaction", 10 (10±1.0) and "Cosmesis", 10 (9.3±1.5). LESS cholecystectomy with epidural anesthesia can be undertaken safely. Patient satisfaction and cosmesis are particularly prominent amongst our patients. Our experience supports further utilization of epidural anesthesia for selected patients undergoing LESS cholecystectomy.

Optical responses in single-crystalline organic microcavities

International Nuclear Information System (INIS)

Kondo, H.; Yamamoto, Y.; Takeda, A.; Yamamoto, S.; Kurisu, H.

2008-01-01

The anisotropic response of cavity polaritons is investigated in an organic microcavity composed of a single-crystalline anthracene film sandwiched between two distributed Bragg reflectors. Upper and lower cavity polariton modes are observed as sharp spectral peaks in the transmission spectra. Dispersion relation for cavity polaritons is obtained as a function of thickness of the thin film. Using this relation, the vacuum Rabi splitting energy for this system is estimated to be 340 meV

Optical responses in single-crystalline organic microcavities

Energy Technology Data Exchange (ETDEWEB)

Kondo, H. [Department of Physics, Ehime University, Matsuyama, 2-5 Bunkyo-cho, Matsuyama 790-8577 (Japan)], E-mail: kondo@phys.sci.ehime-u.ac.jp; Yamamoto, Y.; Takeda, A. [Department of Physics, Ehime University, Matsuyama, 2-5 Bunkyo-cho, Matsuyama 790-8577 (Japan); Yamamoto, S.; Kurisu, H. [Department of Advanced Materials Science and Engineering, Yamaguchi University, Ube, Yamaguchi 755-8611 (Japan)

2008-05-15

The anisotropic response of cavity polaritons is investigated in an organic microcavity composed of a single-crystalline anthracene film sandwiched between two distributed Bragg reflectors. Upper and lower cavity polariton modes are observed as sharp spectral peaks in the transmission spectra. Dispersion relation for cavity polaritons is obtained as a function of thickness of the thin film. Using this relation, the vacuum Rabi splitting energy for this system is estimated to be 340 meV.

Single-session endoscopic resection and focal radiofrequency ablation for short-segment Barrett's esophagus with early neoplasia.

Science.gov (United States)

Barret, Maximilien; Belghazi, Kamar; Weusten, Bas L A M; Bergman, Jacques J G H M; Pouw, Roos E

2016-07-01

The management of early neoplasia in Barrett's esophagus (BE) requires endoscopic resection of visible lesions, followed by radiofrequency ablation (RFA) of the remaining BE. We evaluated the safety and efficacy of combining endoscopic resection and focal RFA in a single endoscopic session in patients with early BE neoplasia. This was a retrospective analysis of patients with early BE neoplasia and a visible lesion undergoing combined endoscopic resection and focal RFA in a single session. Consecutive ablation procedures were performed every 8 to 12 weeks until complete endoscopic and histologic eradication of dysplasia and intestinal metaplasia were reached. Forty patients were enrolled, with a median C1M2 BE segment, a visible lesion with a median diameter of 15 mm, and invasive carcinoma in 68% of cases. Endoscopic resection was performed by using the multiband mucosectomy technique in 80% of cases, and the Barrx(90) catheter (Barrx Medical, Sunnyvale, Calif) was used for focal ablation. When an intention-to-treat analysis was used, both complete remission of all neoplasia and intestinal metaplasia were 95% after a median follow-up of 19 months. Stenoses occurred in 33% of cases and were successfully managed with a median number of 2 dilations. In 43% of patients, 1 single-session treatment resulted in complete histologic remission of intestinal metaplasia. Combining endoscopic resection and focal RFA in a single session appears to be effective. Less-aggressive RFA regimens could limit the adverse event rates. Copyright © 2016 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

FBIH financial market segmentation on the basis of image factors

Directory of Open Access Journals (Sweden)

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.

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

Automatic segmentation of anatomical structures in medical images is a valuable tool for efficient computer-aided radiotherapy and surgery planning and an enabling technology for dynamic adaptive radiotherapy. This paper presents the design, algorithms and validation of new software for the automatic segmentation of CT images used for radiotherapy treatment planning. A coarse to fine approach is followed that consists of presegmentation, anatomic orientation and structure segmentation. No user input or a priori information about the image content is required. In presegmentation, the body outline, the bones and lung equivalent tissue are detected. Anatomic orientation recognizes the patient's position, orientation and gender and creates an elastic mapping of the slice positions to a reference scale. Structure segmentation is divided into localization, outlining and refinement, performed by procedures with implicit anatomic knowledge using standard image processing operations. The presented version of algorithms automatically segments the body outline and bones in any gender and patient position, the prostate, bladder and femoral heads for male pelvis in supine position, and the spinal canal, lungs, heart and trachea in supine position. The software was developed and tested on a collection of over 600 clinical radiotherapy planning CT stacks. In a qualitative validation on this test collection, anatomic orientation correctly detected gender, patient position and body region in 98% of the cases, a correct mapping was produced for 89% of thorax and 94% of pelvis cases. The average processing time for the entire segmentation of a CT stack was less than 1 min on a standard personal computer. Two independent retrospective studies were carried out for clinical validation. Study I was performed on 66 cases (30 pelvis, 36 thorax) with dosimetrists, study II on 52 cases (39 pelvis, 13 thorax) with radio-oncologists as experts. The experts rated the automatically produced

Organic carbon in Hanford single-shell tank waste

International Nuclear Information System (INIS)

Toth, J.J.; Willingham, C.E.; Heasler, P.G.; Whitney, P.D.

1994-04-01

Safety of Hanford single-shell tanks (SSTs) containing organic carbon is a concern because the carbon in the presence of oxidizers (NO 3 or NO 2 ) is combustible when sufficiently concentrated and exposed to elevated temperatures. A propagating chemical reaction could potentially occur at high temperature (above 200 C). The rapid increase in temperature and pressure within a tank might result in the release of radioactive waste constituents to the environment. The purpose of this study is to gather available laboratory information about the organic carbon waste inventories stored in the Hanford SSTs. Specifically, the major objectives of this investigation are: Review laboratory analytical data and measurements for SST composite core and supernatant samples for available organic data; Assess the correlation of organic carbon estimated utilizing the TRAC computer code compared to laboratory measurements; and From the laboratory analytical data, estimate the TOC content with confidence levels for each of the 149 SSTs

Anatomical surgical arterial segments of the kidneys of Santa Inês ovines

Directory of Open Access Journals (Sweden)

Antônio Chaves de Assis Neto

2007-03-01

Full Text Available The main goal of the study was describe the distribution of the renal arteries of the renal parenchyma and the proportional area of the arterial vascular system. The renal arterial vascularization in Santa Ines ovines was analyzed in fifteen pairs of organs of male adult animal, after attainment of vascular models through the techniques of corrosion and arteriography. The renal artery always appeared single, and before reaching the renal hilus, it bifurcated into sectorial dorsal and ventral arteries, giving rise to the segmentary arteries which varied from 6 to 10 in number in the right kidney and 7 to 11 in the left kidney. These vessels vascularized independent areas in each renal sector, the renal arterial segments, separated by non-vascularized planes. Bilateral symmetry of the arterial segmentation was found in 13.33% of cases. In accordance with the arterial characterization, the realization of setoriectomy and segmentectomy on the kidneys of Santa Ines ovines is therefore deemed possible.

Deficit in figure-ground segmentation following closed head injury.

Science.gov (United States)

Baylis, G C; Baylis, L L

1997-08-01

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

Possible words and fixed stress in the segmentation of Slovak speech

NARCIS (Netherlands)

Hanuliková, A.; McQueen, J.M.; Mitterer, H.A.

2010-01-01

The possible-word constraint (PWC; Norris, McQueen, Cutler, & Butterfield, 1997) has been proposed as a language-universal segmentation principle: Lexical candidates are disfavoured if the resulting segmentation of continuous speech leads to vowelless residues in the input—for example, single

Automatic lithofacies segmentation from well-logs data. A comparative study between the Self-Organizing Map (SOM) and Walsh transform

Science.gov (United States)

Aliouane, Leila; Ouadfeul, Sid-Ali; Rabhi, Abdessalem; Rouina, Fouzi; Benaissa, Zahia; Boudella, Amar

2013-04-01

The main goal of this work is to realize a comparison between two lithofacies segmentation techniques of reservoir interval. The first one is based on the Kohonen's Self-Organizing Map neural network machine. The second technique is based on the Walsh transform decomposition. Application to real well-logs data of two boreholes located in the Algerian Sahara shows that the Self-organizing map is able to provide more lithological details that the obtained lithofacies model given by the Walsh decomposition. Keywords: Comparison, Lithofacies, SOM, Walsh References: 1)Aliouane, L., Ouadfeul, S., Boudella, A., 2011, Fractal analysis based on the continuous wavelet transform and lithofacies classification from well-logs data using the self-organizing map neural network, Arabian Journal of geosciences, doi: 10.1007/s12517-011-0459-4 2) Aliouane, L., Ouadfeul, S., Djarfour, N., Boudella, A., 2012, Petrophysical Parameters Estimation from Well-Logs Data Using Multilayer Perceptron and Radial Basis Function Neural Networks, Lecture Notes in Computer Science Volume 7667, 2012, pp 730-736, doi : 10.1007/978-3-642-34500-5_86 3)Ouadfeul, S. and Aliouane., L., 2011, Multifractal analysis revisited by the continuous wavelet transform applied in lithofacies segmentation from well-logs data, International journal of applied physics and mathematics, Vol01 N01. 4) Ouadfeul, S., Aliouane, L., 2012, Lithofacies Classification Using the Multilayer Perceptron and the Self-organizing Neural Networks, Lecture Notes in Computer Science Volume 7667, 2012, pp 737-744, doi : 10.1007/978-3-642-34500-5_87 5) Weisstein, Eric W. "Fast Walsh Transform." From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/FastWalshTransform.html

Deceased donor organ transplantation with expanded criteria donors: a single-center experience from India.

Science.gov (United States)

Goplani, K R; Firoz, A; Ramakrishana, P; Shah, P R; Gumber, M R; Patel, H V; Vanikar, A V; Trivedi, H L

2010-01-01

Deceased donor organ transplantation (DDOT) accounts for DKT) and 19 single (SKT). Fourteen donors had hypertension, a cerebrovascular accident as the cause of death, 9 had both, and 4 had diabetes. Mean donor age was 70.3 +/- 8.9 years. Decisions on the procedure were based upon frozen section biopsy in 13 of 21 donors. Mean DKT donor age was 76 +/- 9.7 years versu 64 +/- 5.7 years of SKT donors. The native kidney diseases were chronic glomerulonephritis (n = 14), diabetic nephropathy (n = 7), tubulointerstitial nephritis (n = 4) and polycystic kidney disease, focal segmental glomerulosclerosis, lupus nephritis and patchy cortical necrosis, (n = 1 each). Mean recipient age of DKT versus SKT was 43.5 versus 42.3 years. All recipients received rabbit anti-thymocyte globulin, followed by steroid, mycophenolate mofetil/calcinueurin inhibitor. Over a mean follow-up of 341 days, the mean serum creatinine (SCr) of 25/29 patients was 1.60 mg/dL (range, 1.0-2.6). The mean SCr of SKT patients was 1.59 +/- 0.63 mg/dL and of DKT, 1.62 +/- 0.48 mg/dL. Ten patients had delayed graft function and 11 had biopsy proven acute tubular necrosis. Seven (24%) patients had rejection (grade 3 Banff update '05, type IA; 4, type 2A); 6 responded to antirejection; 1 graft was lost at 7 months due to chronic rejection. Three (10.3%) patients were lost, 1 each due to AMI, sepsis, and CMV disease. In the circumstances of organ shortage, DDOT with expanded criteria donor is a feasible option.

Identification of the segmental artery feeding the anterior spinal artery. Correlation between helical CT and angiography

International Nuclear Information System (INIS)

Nishimura, Jun-ichi; Lee, Jin; Koike, Shigeomi

2005-01-01

We investigated whether identification of the segmental artery feeding the anterior spinal artery (ASA) is possible by single-slice helical CT. Enhanced CT and angiography were performed in 14 patients with retroperitoneal, liver, or bone tumor. A single-slice helical CT scanner with 7 mm collimation and a 1.0 helical pitch was used. Scanning was started 25 to 30 sec after an intravenous injection of 100 ml of contrast medium at a rate of 3.0 ml/sec. We predicted the segmental artery feeding the ASA in all 14 patients using enhanced CT images. In 12 of the 14 patients, the segmental artery feeding the ASA was angiographically identified. In 7 of these 12 patients, the level of the segmental artery feeding the ASA identified on segmental arteriogram was the same level as that predicted by enhanced CT. In the remaining 5 patients, the level of the segmental artery feeding the ASA identified on segmental arteriogram was one level higher or lower than the predicted spinal level. We could identify the segmental artery feeding the ASA by detailed examination and interpretation of single-slice helical CT images. (author)

Effect of the average soft-segment length on the morphology and properties of segmented polyurethane nanocomposites

International Nuclear Information System (INIS)

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

2006-01-01

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

A Novel Approach of Cardiac Segmentation In CT Image Based On Spline Interpolation

International Nuclear Information System (INIS)

Gao Yuan; Ma Pengcheng

2011-01-01

Organ segmentation in CT images is the basis of organ model reconstruction, thus precisely detecting and extracting the organ boundary are keys for reconstruction. In CT image the cardiac are often adjacent to the surrounding tissues and gray gradient between them is too slight, which cause the difficulty of applying classical segmentation method. We proposed a novel algorithm for cardiac segmentation in CT images in this paper, which combines the gray gradient methods and the B-spline interpolation. This algorithm can perfectly detect the boundaries of cardiac, at the same time it could well keep the timeliness because of the automatic processing.

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

An argument for the use of multiple segment stents in curved arteries.

Science.gov (United States)

Kasiri, Saeid; Kelly, Daniel J

2011-08-01

Stenting of curved arteries is generally perceived to be more challenging than straight vessels. Conceptually implanting multiple shorter stents rather than a single longer stent into such a curved artery represents a promising concept, but little is known about the impact of such an approach. The objective of this study is to evaluate the effectiveness of using a multiple segment stent rather than a single long stent to dilate a curved artery using the finite element method. A double segment stent (DSS) and a single segment stent (SSS) were modeled. The stents were compared when expanded into a model of a curved artery. The model predicts that the DSS provides higher flexibility, more conformity, and lower recoil in comparison to the SSS. The volume of arterial tissue experiencing high levels of stress due to stent implantation is also reduced for the DSS. It is suggested that a multiple segment stenting system is a potential solution to the problem of higher rates of in-stent restenosis in curved arteries and mechanically challenging environments.

Structural and electronic properties of single molecules and organic layers on surfaces

NARCIS (Netherlands)

Sotthewes, Kai

2016-01-01

Single molecules and organic layers on well-defined solid surfaces have attracted tremendous attention owing to their interesting physical and chemical properties. The ultimate utility of single molecules or self-assembled monolayers (SAMs) for potential applications is critically dependent on the

Timing Embryo Segmentation: Dynamics and Regulatory Mechanisms of the Vertebrate Segmentation Clock

Science.gov (United States)

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

2014-01-01

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

Efficient and bright organic light-emitting diodes on single-layer graphene electrodes

Science.gov (United States)

Li, Ning; Oida, Satoshi; Tulevski, George S.; Han, Shu-Jen; Hannon, James B.; Sadana, Devendra K.; Chen, Tze-Chiang

2013-08-01

Organic light-emitting diodes are emerging as leading technologies for both high quality display and lighting. However, the transparent conductive electrode used in the current organic light-emitting diode technologies increases the overall cost and has limited bendability for future flexible applications. Here we use single-layer graphene as an alternative flexible transparent conductor, yielding white organic light-emitting diodes with brightness and efficiency sufficient for general lighting. The performance improvement is attributed to the device structure, which allows direct hole injection from the single-layer graphene anode into the light-emitting layers, reducing carrier trapping induced efficiency roll-off. By employing a light out-coupling structure, phosphorescent green organic light-emitting diodes exhibit external quantum efficiency >60%, while phosphorescent white organic light-emitting diodes exhibit external quantum efficiency >45% at 10,000 cd m-2 with colour rendering index of 85. The power efficiency of white organic light-emitting diodes reaches 80 lm W-1 at 3,000 cd m-2, comparable to the most efficient lighting technologies.

Measurements on a prototype segmented Clover detector

CERN Document Server

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

1999-01-01

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

Measurement of Na-K-ATPase-mediated rubidium influx in single segments of rat nephron

Energy Technology Data Exchange (ETDEWEB)

Cheval, L.; Doucet, A. (Centre National de la Recherche Scientifique, Paris (France))

1990-07-01

To determine the functioning rate of Na-K-ATPase in the rat nephron, a micromethod was developed to measure the rate of rubidium uptake in single nephron segments microdissected from collagenase-treated kidneys. Because the hydrolytic activity of Na-K-ATPase displayed the same apparent affinity for K and Rb ions, whereas the Vmax elicited by K was higher than that in the presence of Rb, experiments were performed in the presence of cold Rb plus 86Rb. Before the assay, tubules were preincubated for 10 min at 37 degrees C to restore the normal transmembrane cation gradients. 86Rb uptake was measured after washing out extracellular cations by rinsing the tubules in ice-cold choline chloride solution containing Ba2+. Rb uptake increased quasi-linearly as a function of incubation time up to 30 s in the thick ascending limb, 1 min in the proximal convoluted tubule, and 5 min in the collecting tubule, and reached an equilibrium after 5-30 min. The initial rates of Rb uptake increased in a saturable fashion as Rb concentration in the medium rose from 0.25 to 5 mM. In medullary thick ascending limb, the initial rate of Rb uptake was inhibited by greater than 90% by 2.5 mM ouabain and by 10(-5) M of the metabolic inhibitor carbonyl cyanide trifluoromethoxyphenylhydrazone. Correlation of Na-K-ATPase hydrolytic activity at Vmax and initial rates of ouabain-sensitive Rb uptake in the successive segments of nephron indicates that in intact cells the pump works at approximately 20-30% of its Vmax. Increasing intracellular Na concentration by tubule preincubation in a Rb- and K-free medium increased the initial rates of Rb intake up to the Vmax of the hydrolytic activity of the pump.

Measurement of Na-K-ATPase-mediated rubidium influx in single segments of rat nephron

International Nuclear Information System (INIS)

Cheval, L.; Doucet, A.

1990-01-01

To determine the functioning rate of Na-K-ATPase in the rat nephron, a micromethod was developed to measure the rate of rubidium uptake in single nephron segments microdissected from collagenase-treated kidneys. Because the hydrolytic activity of Na-K-ATPase displayed the same apparent affinity for K and Rb ions, whereas the Vmax elicited by K was higher than that in the presence of Rb, experiments were performed in the presence of cold Rb plus 86Rb. Before the assay, tubules were preincubated for 10 min at 37 degrees C to restore the normal transmembrane cation gradients. 86Rb uptake was measured after washing out extracellular cations by rinsing the tubules in ice-cold choline chloride solution containing Ba2+. Rb uptake increased quasi-linearly as a function of incubation time up to 30 s in the thick ascending limb, 1 min in the proximal convoluted tubule, and 5 min in the collecting tubule, and reached an equilibrium after 5-30 min. The initial rates of Rb uptake increased in a saturable fashion as Rb concentration in the medium rose from 0.25 to 5 mM. In medullary thick ascending limb, the initial rate of Rb uptake was inhibited by greater than 90% by 2.5 mM ouabain and by 10(-5) M of the metabolic inhibitor carbonyl cyanide trifluoromethoxyphenylhydrazone. Correlation of Na-K-ATPase hydrolytic activity at Vmax and initial rates of ouabain-sensitive Rb uptake in the successive segments of nephron indicates that in intact cells the pump works at approximately 20-30% of its Vmax. Increasing intracellular Na concentration by tubule preincubation in a Rb- and K-free medium increased the initial rates of Rb intake up to the Vmax of the hydrolytic activity of the pump

Active contour based segmentation of resected livers in CT images

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Oelmann, Simon; Oyarzun Laura, Cristina; Drechsler, Klaus; Wesarg, Stefan

2015-03-01

The majority of state of the art segmentation algorithms are able to give proper results in healthy organs but not in pathological ones. However, many clinical applications require an accurate segmentation of pathological organs. The determination of the target boundaries for radiotherapy or liver volumetry calculations are examples of this. Volumetry measurements are of special interest after tumor resection for follow up of liver regrow. The segmentation of resected livers presents additional challenges that were not addressed by state of the art algorithms. This paper presents a snakes based algorithm specially developed for the segmentation of resected livers. The algorithm is enhanced with a novel dynamic smoothing technique that allows the active contour to propagate with different speeds depending on the intensities visible in its neighborhood. The algorithm is evaluated in 6 clinical CT images as well as 18 artificial datasets generated from additional clinical CT images.

Segmentation: Identification of consumer segments

DEFF Research Database (Denmark)

Høg, Esben

2005-01-01

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

Multi-atlas pancreas segmentation: Atlas selection based on vessel structure.

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Karasawa, Ken'ichi; Oda, Masahiro; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Chu, Chengwen; Zheng, Guoyan; Rueckert, Daniel; Mori, Kensaku

2017-07-01

Automated organ segmentation from medical images is an indispensable component for clinical applications such as computer-aided diagnosis (CAD) and computer-assisted surgery (CAS). We utilize a multi-atlas segmentation scheme, which has recently been used in different approaches in the literature to achieve more accurate and robust segmentation of anatomical structures in computed tomography (CT) volume data. Among abdominal organs, the pancreas has large inter-patient variability in its position, size and shape. Moreover, the CT intensity of the pancreas closely resembles adjacent tissues, rendering its segmentation a challenging task. Due to this, conventional intensity-based atlas selection for pancreas segmentation often fails to select atlases that are similar in pancreas position and shape to those of the unlabeled target volume. In this paper, we propose a new atlas selection strategy based on vessel structure around the pancreatic tissue and demonstrate its application to a multi-atlas pancreas segmentation. Our method utilizes vessel structure around the pancreas to select atlases with high pancreatic resemblance to the unlabeled volume. Also, we investigate two types of applications of the vessel structure information to the atlas selection. Our segmentations were evaluated on 150 abdominal contrast-enhanced CT volumes. The experimental results showed that our approach can segment the pancreas with an average Jaccard index of 66.3% and an average Dice overlap coefficient of 78.5%. Copyright © 2017 Elsevier B.V. All rights reserved.

Detection of single quantum dots in model organisms with sheet illumination microscopy

Energy Technology Data Exchange (ETDEWEB)

Friedrich, Mike; Nozadze, Revaz; Gan, Qiang; Zelman-Femiak, Monika; Ermolayev, Vladimir [Molecular Microscopy Group, Rudolf Virchow Center, University of Wuerzburg, Versbacher Str. 9, D-97078 Wuerzburg (Germany); Wagner, Toni U. [Institute of Physiological Chemistry I, Biocenter, University of Wuerzburg, Am Hubland, D-97074 Wuerzburg (Germany); Harms, Gregory S., E-mail: gregory.harms@virchow.uni-wuerzburg.de [Molecular Microscopy Group, Rudolf Virchow Center, University of Wuerzburg, Versbacher Str. 9, D-97078 Wuerzburg (Germany)

2009-12-18

Single-molecule detection and tracking is important for observing biomolecule interactions in the microenvironment. Here we report selective plane illumination microscopy (SPIM) with single-molecule detection in living organisms, which enables fast imaging and single-molecule tracking and optical penetration beyond 300 {mu}m. We detected single nanocrystals in Drosophila larvae and zebrafish embryo. We also report our first tracking of single quantum dots during zebrafish development, which displays a transition from flow to confined motion prior to the blastula stage. The new SPIM setup represents a new technique, which enables fast single-molecule imaging and tracking in living systems.

Detection of single quantum dots in model organisms with sheet illumination microscopy

International Nuclear Information System (INIS)

Friedrich, Mike; Nozadze, Revaz; Gan, Qiang; Zelman-Femiak, Monika; Ermolayev, Vladimir; Wagner, Toni U.; Harms, Gregory S.

2009-01-01

Single-molecule detection and tracking is important for observing biomolecule interactions in the microenvironment. Here we report selective plane illumination microscopy (SPIM) with single-molecule detection in living organisms, which enables fast imaging and single-molecule tracking and optical penetration beyond 300 μm. We detected single nanocrystals in Drosophila larvae and zebrafish embryo. We also report our first tracking of single quantum dots during zebrafish development, which displays a transition from flow to confined motion prior to the blastula stage. The new SPIM setup represents a new technique, which enables fast single-molecule imaging and tracking in living systems.

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.

Responsiveness of culture-based segmentation of organizational buyers

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Veronika Jadczaková

2013-01-01

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

Segmentation and profiling consumers in a multi-channel environment using a combination of self-organizing maps (SOM method, and logistic regression

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Seyed Ali Akbar Afjeh

2014-05-01

Full Text Available Market segmentation plays essential role on understanding the behavior of people’s interests in purchasing various products and services through various channels. This paper presents an empirical investigation to shed light on consumer’s purchasing attitude as well as gathering information in multi-channel environment. The proposed study of this paper designed a questionnaire and distributed it among 800 people who were at least 18 years of age and had some experiences on purchasing goods and services on internet, catalog or regular shopping centers. Self-organizing map, SOM, clustering technique was performed based on consumer’s interest in gathering information as well as purchasing products through internet, catalog and shopping centers and determined four segments. There were two types of questions for the proposed study of this paper. The first group considered participants’ personal characteristics such as age, gender, income, etc. The second group of questions was associated with participants’ psychographic characteristics including price consciousness, quality consciousness, time pressure, etc. Using multinominal logistic regression technique, the study determines consumers’ behaviors in each four segments.

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

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

2014-12-01

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

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

Sequence analysis of the PIP5K locus in Eimeria maxima provides further evidence for eimerian genome plasticity and segmental organization.

Science.gov (United States)

Song, B K; Pan, M Z; Lau, Y L; Wan, K L

2014-07-29

Commercial flocks infected by Eimeria species parasites, including Eimeria maxima, have an increased risk of developing clinical or subclinical coccidiosis; an intestinal enteritis associated with increased mortality rates in poultry. Currently, infection control is largely based on chemotherapy or live vaccines; however, drug resistance is common and vaccines are relatively expensive. The development of new cost-effective intervention measures will benefit from unraveling the complex genetic mechanisms that underlie host-parasite interactions, including the identification and characterization of genes encoding proteins such as phosphatidylinositol 4-phosphate 5-kinase (PIP5K). We previously identified a PIP5K coding sequence within the E. maxima genome. In this study, we analyzed two bacterial artificial chromosome clones presenting a ~145-kb E. maxima (Weybridge strain) genomic region spanning the PIP5K gene locus. Sequence analysis revealed that ~95% of the simple sequence repeats detected were located within regions comparable to the previously described feature-rich segments of the Eimeria tenella genome. Comparative sequence analysis with the orthologous E. maxima (Houghton strain) region revealed a moderate level of conserved synteny. Unique segmental organizations and telomere-like repeats were also observed in both genomes. A number of incomplete transposable elements were detected and further scrutiny of these elements in both orthologous segments revealed interesting nesting events, which may play a role in facilitating genome plasticity in E. maxima. The current analysis provides more detailed information about the genome organization of E. maxima and may help to reveal genotypic differences that are important for expression of traits related to pathogenicity and virulence.

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

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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.

Osmotic and Heat Stress Effects on Segmentation.

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Julian Weiss

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

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.

Customer segmentation model based on value generation for marketing strategies formulation

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Alvaro Julio Cuadros

2014-01-01

Full Text Available When deciding in which segment to invest or how to distribute the marketing budget, managers generally take risks in making decisions without considering the real impact every client or segment has over organizational profits. In this paper, a segmentation framework is proposed that considers, firstly, the calculation of customer lifetime value, the current value, and client loyalty, and then the building of client segments by self-organized maps. The effectiveness of the proposed method is demonstrated with an empirical study in a cane sugar mill where a total of 9 segments of interest were identified for decision making.

Effect of grain boundary on the field-effect mobility of microrod single crystal organic transistors.

Science.gov (United States)

Kim, Jaekyun; Kang, Jingu; Cho, Sangho; Yoo, Byungwook; Kim, Yong-Hoon; Park, Sung Kyu

2014-11-01

High-performance microrod single crystal organic transistors based on a p-type 2,7-dioctyl[1]benzothieno[3,2-b][1]benzothiophene (C8-BTBT) semiconductor are fabricated and the effects of grain boundaries on the carrier transport have been investigated. The spin-coating of C8-BTBT and subsequent solvent vapor annealing process enabled the formation of organic single crystals with high aspect ratio in the range of 10 - 20. It was found that the organic field-effect transistors (OFETs) based on these single crystals yield a field-effect mobility and an on/off current ratio of 8.04 cm2/Vs and > 10(5), respectively. However, single crystal OFETs with a kink, in which two single crystals are fused together, exhibited a noticeable drop of field-effect mobility, and we claim that this phenomenon results from the carrier scattering at the grain boundary.

Evaluation of image quality on a per-patient, per-vessel, and per-segment basis by noninvasive coronary angiography with 64-section computed tomography. Dual-source versus single-source computed tomography

International Nuclear Information System (INIS)

Nakashima, Yoshiteru; Okada, Munemasa; Washida, Yasuo; Miura, Toshiro; Fujimura, Tatsuo; Nao, Tomoko; Matsunaga, Naofumi

2011-01-01

The purpose of this study was to evaluate the image quality (IQ) of dual-source CT (DSCT) versus single-source CT (SSCT). A total of 100 patients underwent 64-section CT coronary angiography (50 DSCT, 50 SSCT). Three observers evaluated the IQ of each coronary segment using a four-point scale (1, excellent; 2, good; 3, fair; 4, no assessment). The IQ of DSCT coronary angiography was compared with SSCT coronary angiography on a per-patient, per-vessel, and per-segment basis using the chi-squared test. The DSCT image quality score (IQS) was significantly lower on a per-patient basis and per-vessel basis for all vessels and on a per-segment basis for some segments (1, 2, 4PD, 4AV, 7, 9, 11, 12, 13) compared with SSCT. The DSCT IQS was significantly lower for certain segments (2, 4PD, 11, 13) with high heart rates (≥70 beats/min). The DSCT IQS was significantly lower for certain segments (1, 2, 3, 4PD, 4AV, 7, 8, 9, 10, 12, 13) with low heart rates (<70 beats/min). DSCT showed a significantly better IQ than SSCT, especially in patients with low heart rates. (author)

Ontology-Based Knowledge Organization for the Radiograph Images Segmentation

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MATEI, O.

2008-04-01

Full Text Available The quantity of thoracic radiographies in the medical field is ever growing. An automated system for segmenting the images would help doctors enormously. Some approaches are knowledge-based; therefore we propose here an ontology for this purpose. Thus it is machine oriented, rather than human-oriented. That is all the structures visible on a thoracic image are described from a technical point of view.

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...

Exploratory analysis of genomic segmentations with Segtools

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Buske Orion J

2011-10-01

Full Text Available Abstract Background As genome-wide experiments and annotations become more prevalent, researchers increasingly require tools to help interpret data at this scale. Many functional genomics experiments involve partitioning the genome into labeled segments, such that segments sharing the same label exhibit one or more biochemical or functional traits. For example, a collection of ChlP-seq experiments yields a compendium of peaks, each labeled with one or more associated DNA-binding proteins. Similarly, manually or automatically generated annotations of functional genomic elements, including cis-regulatory modules and protein-coding or RNA genes, can also be summarized as genomic segmentations. Results We present a software toolkit called Segtools that simplifies and automates the exploration of genomic segmentations. The software operates as a series of interacting tools, each of which provides one mode of summarization. These various tools can be pipelined and summarized in a single HTML page. We describe the Segtools toolkit and demonstrate its use in interpreting a collection of human histone modification data sets and Plasmodium falciparum local chromatin structure data sets. Conclusions Segtools provides a convenient, powerful means of interpreting a genomic segmentation.

Graph run-length matrices for histopathological image segmentation.

Science.gov (United States)

Tosun, Akif Burak; Gunduz-Demir, Cigdem

2011-03-01

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

Validation of clinical acceptability of an atlas-based segmentation algorithm for the delineation of organs at risk in head and neck cancer

Energy Technology Data Exchange (ETDEWEB)

Hoang Duc, Albert K., E-mail: albert.hoangduc.ucl@gmail.com; McClelland, Jamie; Modat, Marc; Cardoso, M. Jorge; Mendelson, Alex F. [Center for Medical Image Computing, University College London, London WC1E 6BT (United Kingdom); Eminowicz, Gemma; Mendes, Ruheena; Wong, Swee-Ling; D’Souza, Derek [Radiotherapy Department, University College London Hospitals, 235 Euston Road, London NW1 2BU (United Kingdom); Veiga, Catarina [Department of Medical Physics and Bioengineering, University College London, London WC1E 6BT (United Kingdom); Kadir, Timor [Mirada Medical UK, Oxford Center for Innovation, New Road, Oxford OX1 1BY (United Kingdom); Ourselin, Sebastien [Centre for Medical Image Computing, University College London, London WC1E 6BT (United Kingdom)

2015-09-15

Purpose: The aim of this study was to assess whether clinically acceptable segmentations of organs at risk (OARs) in head and neck cancer can be obtained automatically and efficiently using the novel “similarity and truth estimation for propagated segmentations” (STEPS) compared to the traditional “simultaneous truth and performance level estimation” (STAPLE) algorithm. Methods: First, 6 OARs were contoured by 2 radiation oncologists in a dataset of 100 patients with head and neck cancer on planning computed tomography images. Each image in the dataset was then automatically segmented with STAPLE and STEPS using those manual contours. Dice similarity coefficient (DSC) was then used to compare the accuracy of these automatic methods. Second, in a blind experiment, three separate and distinct trained physicians graded manual and automatic segmentations into one of the following three grades: clinically acceptable as determined by universal delineation guidelines (grade A), reasonably acceptable for clinical practice upon manual editing (grade B), and not acceptable (grade C). Finally, STEPS segmentations graded B were selected and one of the physicians manually edited them to grade A. Editing time was recorded. Results: Significant improvements in DSC can be seen when using the STEPS algorithm on large structures such as the brainstem, spinal canal, and left/right parotid compared to the STAPLE algorithm (all p < 0.001). In addition, across all three trained physicians, manual and STEPS segmentation grades were not significantly different for the brainstem, spinal canal, parotid (right/left), and optic chiasm (all p > 0.100). In contrast, STEPS segmentation grades were lower for the eyes (p < 0.001). Across all OARs and all physicians, STEPS produced segmentations graded as well as manual contouring at a rate of 83%, giving a lower bound on this rate of 80% with 95% confidence. Reduction in manual interaction time was on average 61% and 93% when automatic

An improved segmented gamma scanning for radioactive waste drums

International Nuclear Information System (INIS)

Liu Cheng; Wang Dezhong; Bai Yunfei; Qian Nan

2010-01-01

In this paper, the equivalent radius of radioactive sources in each segment is determined by analyzing the different responses of the two identical detectors, and an improved segmented gamma scanning is used to assay waste drums containing mainly organic materials, and proved by an established simulation model. The simulated radioactivity distributions in homogenous waste drum and an experimental heterogeneous waste drum were compared with those of traditional segmented gamma scanning. The results show that our method is good in performance and can be used for analyzing the waste drums. (authors)

Self-Paced Physics, Segments 28-31.

Science.gov (United States)

New York Inst. of Tech., Old Westbury.

Four study segments of the Self-Paced Physics Course materials are presented in this sixth problems and solutions book used as a part of student course work. The subject matter is related to electric currents, current densities, resistances, Ohm's law, voltages, Joule heating, electromotive forces, single loop circuits, series and parallel…

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

KAUST Repository

Khan, Naeemullah

2017-11-09

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

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

KAUST Repository

Khan, Naeemullah; Hong, Byung-Woo; Yezzi, Anthony; Sundaramoorthi, Ganesh

2017-01-01

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

Consumer perception of sustainability attributes in organic and local food.

Science.gov (United States)

Annunziata, Azzurra; Angela, Mariani

2017-12-14

Although sustainable food consumption is gaining growing importance on the international agenda, research on this subject is still quite fragmented and most studies analyse single aspects of sustainable food consumption with particular reference to environmental sustainability. In addition, the literature highlights the need to take account of the strong heterogeneity of consumers in studying sustainable behaviour. Identifying consumer segments with common profiles, needs and values is essential for developing effective communication strategies to promote sustainability in food consumption. Consumer segmentation based on the perception of the sustainability attributes of organic and local products was realized using descriptive data collected through a consumer online survey in southern Italy (Campania). K-means cluster analysis was performed to identify different consumer segments based on consumer perception of sustainable attributes in organic and local food. Results confirm the support of consumers for organic and local food as sustainable alternative in food choices even if occasional buying behaviour of these products still predominates. In addition, our results show that an egoistic approach prevails among consumers, who seem to attach more value to attributes related to quality and health than to environmental, social and economic sustainability. Segmentation proves the existence of three consumer segments that differ significantly in terms of perception of sustainability attributes: a large segment of individuals who seem more egocentric oriented, an environmental sustainability oriented segment and a small segment that includes sustainability oriented consumers. The existence of different levels of sensitivity to sustainability attributes in organic and local food among the identified segments could be duly considered by policy makers and other institutions in promoting sustainable consumption patterns. Consumers in the first cluster could be educated

Diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to cognitive change

Directory of Open Access Journals (Sweden)

Owen A. Williams

2017-01-01

DSEG θ is a powerful tool for characterising subtle brain change in SVD that has a negative impact on cognition and remains a significant predictor of cognitive change when other MRI markers of brain change are accounted for. DSEG provides an automatic segmentation of the whole cerebrum that is sensitive to a range of SVD related structural changes and successfully predicts cognitive change. Power analysis shows DSEG θ has potential as a monitoring tool in clinical trials. As such it may provide a marker of SVD severity from a single imaging modality (i.e. DTIs.

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

Self-organization of single filaments and diffusive plasmas during a single pulse in dielectric-barrier discharges

International Nuclear Information System (INIS)

Babaeva, Natalia Yu; Kushner, Mark J

2014-01-01

Self-organization of filaments in dielectric-barrier discharges (DBDs) probably has many origins. However, the dominant cause is proposed to be the accumulation of charge on the surfaces of the bounding dielectrics that reinforces successive discharge pulses to occur at the same locations. A secondary cause is the electrostatic repulsion of individual plasma filaments. Self-organization typically develops over many discharge pulses. In this paper, we discuss the results of a computational investigation of plasma filaments in overvoltage DBDs that, under select conditions, display self-organized patterns (SOPs) of plasma density during a single discharge pulse. (Overvoltage refers to the rapid application of a voltage in excess of the quasi-dc breakdown voltage.) The origin of the SOPs is a synergistic relationship between the speed of the surface-ionization waves that propagate along each dielectric and the rate at which avalanche occurs across the gap. For our test conditions, SOPs were not observed at lower voltages and gradually formed at higher voltages. The same conditions that result in SOPs, i.e. the application of an overvoltage, also produce more diffuse discharges. A transition from a single narrow filament to a more diffuse structure was observed as overvoltage was approached. The sensitivity of SOPs to the orientation and permittivity of the bounding dielectrics is discussed. (paper)

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.

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.

Angular Magnetoresistance of Nanowires with Alternating Cobalt and Nickel Segments

KAUST Repository

Mohammed, Hanan

2017-06-22

Magnetization reversal in segmented Co/Ni nanowires with varying number of segments was studied using angular Magnetoresistance (MR) measurements on isolated nanowires. The MR measurements offer an insight into the pinning of domain walls within the nanowires. Angular MR measurements were performed on nanowires with two and multiple segments by varying the angle between the applied magnetic field and nanowire (−90° ≤θ≤90°). The angular MR measurements reveal that at lower values of θ the switching fields are nearly identical for the multisegmented and two-segmented nanowires, whereas at higher values of θ, a decrease in the switching field is observed in the case of two segmented nanowires. The two segmented nanowires generally exhibit a single domain wall pinning event, whereas an increased number of pinning events are characteristic of the multisegmented nanowires at higher values of θ. In-situ magnetic force microscopy substantiates reversal by domain wall nucleation and propagation in multisegmented nanowires.

Angular Magnetoresistance of Nanowires with Alternating Cobalt and Nickel Segments

KAUST Repository

Mohammed, Hanan; Corte-Leon, H.; Ivanov, Yurii P.; Moreno, J. A.; Kazakova, O.; Kosel, Jü rgen

2017-01-01

Magnetization reversal in segmented Co/Ni nanowires with varying number of segments was studied using angular Magnetoresistance (MR) measurements on isolated nanowires. The MR measurements offer an insight into the pinning of domain walls within the nanowires. Angular MR measurements were performed on nanowires with two and multiple segments by varying the angle between the applied magnetic field and nanowire (−90° ≤θ≤90°). The angular MR measurements reveal that at lower values of θ the switching fields are nearly identical for the multisegmented and two-segmented nanowires, whereas at higher values of θ, a decrease in the switching field is observed in the case of two segmented nanowires. The two segmented nanowires generally exhibit a single domain wall pinning event, whereas an increased number of pinning events are characteristic of the multisegmented nanowires at higher values of θ. In-situ magnetic force microscopy substantiates reversal by domain wall nucleation and propagation in multisegmented nanowires.

Important factors in HMM-based phonetic segmentation

CSIR Research Space (South Africa)

Van Niekerk, DR

2007-11-01

Full Text Available , window and step sizes. Taking into account that the segmentation system trains and applies the HMM models on a single speaker only, our first con- cern was the applicability of the window and step sizes that are commonly used for speech recognition...

The emergence of diverse organic consumers

DEFF Research Database (Denmark)

Lund, Thomas Bøker; Andersen, Laura Mørch; Jensen, Katherine

polarised. It can also be said to have matured insofar as positively oriented segments that differ in their food involvement, shopping behaviour and levels of ethical concern have appeared, while marketing and distribution strategies have co-developed with these trends. We discuss the current relevance......This study uses qualitative and quantitative data as well as household panel data regarding actual purchases of organic food in order to examine organic consumer profiles and recent developments of organic demand in Denmark. Six different segments of Danish households are identified, of which three...... of segmenting organic consumers in mature markets with a view to improving strategies of production, distribution and marketing of organic foods....

Patterning solution-processed organic single-crystal transistors with high device performance

Directory of Open Access Journals (Sweden)

Yun Li

2011-06-01

Full Text Available We report on the patterning of organic single-crystal transistors with high device performance fabricated via a solution process under ambient conditions. The semiconductor was patterned on substrates via surface selective deposition. Subsequently, solvent-vapor annealing was performed to reorganize the semiconductor into single crystals. The transistors exhibited field-effect mobility (μFET of up to 3.5 cm2/V s. Good reliability under bias-stress conditions indicates low density of intrinsic defects in crystals and low density of traps at the active interfaces. Furthermore, the Y function method clearly suggests that the variation of μFET of organic crystal transistors was caused by contact resistance. Further improvement of the device with higher μFET with smaller variation can be expected when lower and more uniform contact resistance is achieved.

Adjustable Two-Tier Cache for IPTV Based on Segmented Streaming

Directory of Open Access Journals (Sweden)

Kai-Chun Liang

2012-01-01

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

Low-Threshold Lasing from 2D Homologous Organic-Inorganic Hybrid Ruddlesden-Popper Perovskite Single Crystals.

Science.gov (United States)

Raghavan, Chinnambedu Murugesan; Chen, Tzu-Pei; Li, Shao-Sian; Chen, Wei-Liang; Lo, Chao-Yuan; Liao, Yu-Ming; Haider, Golam; Lin, Cheng-Chieh; Chen, Chia-Chun; Sankar, Raman; Chang, Yu-Ming; Chou, Fang-Cheng; Chen, Chun-Wei

2018-05-09

Organic-inorganic hybrid two-dimensional (2D) perovskites have recently attracted great attention in optical and optoelectronic applications due to their inherent natural quantum-well structure. We report the growth of high-quality millimeter-sized single crystals belonging to homologous two-dimensional (2D) hybrid organic-inorganic Ruddelsden-Popper perovskites (RPPs) of (BA) 2 (MA) n-1 Pb n I 3 n+1 ( n = 1, 2, and 3) by a slow evaporation at a constant-temperature (SECT) solution-growth strategy. The as-grown 2D hybrid perovskite single crystals exhibit excellent crystallinity, phase purity, and spectral uniformity. Low-threshold lasing behaviors with different emission wavelengths at room temperature have been observed from the homologous 2D hybrid RPP single crystals. Our result demonstrates that solution-growth homologous organic-inorganic hybrid 2D perovskite single crystals open up a new window as a promising candidate for optical gain media.

Nearest neighbor 3D segmentation with context features

Science.gov (United States)

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

2018-03-01

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

Single Vs Mixed Organic Cation for Low Temperature Processed Perovskite Solar Cells

International Nuclear Information System (INIS)

Mahmud, Md Arafat; Elumalai, Naveen Kumar; Upama, Mushfika Baishakhi; Wang, Dian; Wright, Matthew; Chan, Kah Howe; Xu, Cheng; Haque, Faiazul; Uddin, Ashraf

2016-01-01

Highlights: • Low temperature processed ZnO based single & mixed organic cation perovskite device. • 37% higher PCE in mixed cation perovskite solar cells (PSCs) than single cation ones. • Mixed cation PSCs exhibit significantly reduced photocurrent hysteresis. • Mixed cation PSCs demonstrate three fold higher device stability than single cation PSCs. • Electronic properties are analyzed using Electrochemical Impedance Spectroscopy. - Abstract: The present work reports a comparative study between single and mixed organic cation based MAPbI 3 and MA 0.6 FA 0.4 PbI 3 perovskite devices fabricated in conjunction with low temperature processed (<150 °C) ZnO electron transport layers. MA 0.6 FA 0.4 PbI 3 perovskite devices demonstrate 37% higher power conversion efficiency compared to MAPbI 3 perovskite devices developed on the ZnO ETL. In addition, MA 0.6 FA 0.4 PbI 3 devices exhibit very low photocurrent hysteresis and they are three-fold more stable than conventional MAPbI 3 PSCs (perovskite solar cells). An in-depth analysis on the charge transport properties in both fresh and aged devices has been carried out using electrochemical impedance spectroscopy analysis to comprehend the enhanced device stability of the mixed perovskite devices developed on the ZnO ETL. The study also investigates into the interfacial charge transfer characteristics associated with the ZnO/mixed organic cation perovskite interface and concomitant influence on the inherent electronic properties.

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...

Flood Water Segmentation from Crowdsourced Images

Science.gov (United States)

Nguyen, J. K.; Minsker, B. S.

2017-12-01

In the United States, 176 people were killed by flooding in 2015. Along with the loss of human lives is the economic cost which is estimated to be $4.5 billion per flood event. Urban flooding has become a recent concern due to the increase in population, urbanization, and global warming. As more and more people are moving into towns and cities with infrastructure incapable of coping with floods, there is a need for more scalable solutions for urban flood management.The proliferation of camera-equipped mobile devices have led to a new source of information for flood research. In-situ photographs captured by people provide information at the local level that remotely sensed images fail to capture. Applications of crowdsourced images to flood research required understanding the content of the image without the need for user input. This paper addresses the problem of how to automatically segment a flooded and non-flooded region in crowdsourced images. Previous works require two images taken at similar angle and perspective of the location when it is flooded and when it is not flooded. We examine three different algorithms from the computer vision literature that are able to perform segmentation using a single flood image without these assumptions. The performance of each algorithm is evaluated on a collection of labeled crowdsourced flood images. We show that it is possible to achieve a segmentation accuracy of 80% using just a single image.

Theoretical analysis of the effect of charge-sharing on the Detective Quantum Efficiency of single-photon counting segmented silicon detectors

Energy Technology Data Exchange (ETDEWEB)

Marchal, J [Diamond Light Source Ltd, Harwell Science and Innovation Campus, Didcot, Oxfordshire OX11 0DE (United Kingdom)], E-mail: julien.marchal@diamond.ac.uk

2010-01-15

A detector cascaded model is proposed to describe charge-sharing effect in single-photon counting segmented silicon detectors. Linear system theory is applied to this cascaded model in order to derive detector performance parameters such as large-area gain, presampling Modulation Transfer Function (MTF), Noise Power Spectrum (NPS) and Detective Quantum Efficiency (DQE) as a function of energy detection threshold. This theory is used to model one-dimensional detectors (i.e. strip detectors) where X-ray-generated charge can be shared between two sampling elements, but the concepts developed in this article can be generalized to two-dimensional arrays of detecting elements (i.e. pixels detectors). The zero-frequency DQE derived from this model is consistent with expressions reported in the literature using a different method. The ability of this model to simulate the effect of charge sharing on image quality in the spatial frequency domain is demonstrated by applying it to a hypothetical one-dimensional single-photon counting detector illuminated with a typical mammography spectrum.

Deep convolutional networks for pancreas segmentation in CT imaging

Science.gov (United States)

Roth, Holger R.; Farag, Amal; Lu, Le; Turkbey, Evrim B.; Summers, Ronald M.

2015-03-01

Automatic organ segmentation is an important prerequisite for many computer-aided diagnosis systems. The high anatomical variability of organs in the abdomen, such as the pancreas, prevents many segmentation methods from achieving high accuracies when compared to state-of-the-art segmentation of organs like the liver, heart or kidneys. Recently, the availability of large annotated training sets and the accessibility of affordable parallel computing resources via GPUs have made it feasible for "deep learning" methods such as convolutional networks (ConvNets) to succeed in image classification tasks. These methods have the advantage that used classification features are trained directly from the imaging data. We present a fully-automated bottom-up method for pancreas segmentation in computed tomography (CT) images of the abdomen. The method is based on hierarchical coarse-to-fine classification of local image regions (superpixels). Superpixels are extracted from the abdominal region using Simple Linear Iterative Clustering (SLIC). An initial probability response map is generated, using patch-level confidences and a two-level cascade of random forest classifiers, from which superpixel regions with probabilities larger 0.5 are retained. These retained superpixels serve as a highly sensitive initial input of the pancreas and its surroundings to a ConvNet that samples a bounding box around each superpixel at different scales (and random non-rigid deformations at training time) in order to assign a more distinct probability of each superpixel region being pancreas or not. We evaluate our method on CT images of 82 patients (60 for training, 2 for validation, and 20 for testing). Using ConvNets we achieve maximum Dice scores of an average 68% +/- 10% (range, 43-80%) in testing. This shows promise for accurate pancreas segmentation, using a deep learning approach and compares favorably to state-of-the-art methods.

Analysis Of Segmental Duplications In The Pig Genome Based On Next-Generation Sequencing

DEFF Research Database (Denmark)

Fadista, João; Bendixen, Christian

Segmental duplications are >1kb segments of duplicated DNA present in a genome with high sequence identity (>90%). They are associated with genomic rearrangements and provide a significant source of gene and genome evolution within mammalian genomes. Although segmental duplications have been...... extensively studied in other organisms, its analysis in pig has been hampered by the lack of a complete pig genome assembly. By measuring the depth of coverage of Illumina whole-genome shotgun sequencing reads of the Tabasco animal aligned to the latest pig genome assembly (Sus scrofa 10 – based also...... and their associated copy number alterations, focusing on the global organization of these segments and their possible functional significance in porcine phenotypes. This work provides insights into mammalian genome evolution and generates a valuable resource for porcine genomics research...

PSNet: prostate segmentation on MRI based on a convolutional neural network.

Science.gov (United States)

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

2018-04-01

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

Graph-based unsupervised segmentation algorithm for cultured neuronal networks' structure characterization and modeling.

Science.gov (United States)

de Santos-Sierra, Daniel; Sendiña-Nadal, Irene; Leyva, Inmaculada; Almendral, Juan A; Ayali, Amir; Anava, Sarit; Sánchez-Ávila, Carmen; Boccaletti, Stefano

2015-06-01

Large scale phase-contrast images taken at high resolution through the life of a cultured neuronal network are analyzed by a graph-based unsupervised segmentation algorithm with a very low computational cost, scaling linearly with the image size. The processing automatically retrieves the whole network structure, an object whose mathematical representation is a matrix in which nodes are identified neurons or neurons' clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocytochemistry techniques, our non invasive measures entitle us to perform a longitudinal analysis during the maturation of a single culture. Such an analysis furnishes the way of individuating the main physical processes underlying the self-organization of the neurons' ensemble into a complex network, and drives the formulation of a phenomenological model yet able to describe qualitatively the overall scenario observed during the culture growth. © 2014 International Society for Advancement of Cytometry.

SEGMENTATION OF SME PORTFOLIO IN BANKING SYSTEM

Directory of Open Access Journals (Sweden)

Namolosu Simona Mihaela

2013-07-01

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

Solution-printed organic semiconductor blends exhibiting transport properties on par with single crystals

KAUST Repository

Niazi, Muhammad Rizwan; Li, Ruipeng; Li, Erqiang; Kirmani, Ahmad R.; Abdelsamie, Maged; Wang, Qingxiao; Pan, Wenyang; Payne, Marcia M.; Anthony, John E.; Smilgies, Detlef-M.; Thoroddsen, Sigurdur T; Giannelis, Emmanuel P.; Amassian, Aram

2015-01-01

Solution-printed organic semiconductors have emerged in recent years as promising contenders for roll-to-roll manufacturing of electronic and optoelectronic circuits. The stringent performance requirements for organic thin-film transistors (OTFTs) in terms of carrier mobility, switching speed, turn-on voltage and uniformity over large areas require performance currently achieved by organic single-crystal devices, but these suffer from scale-up challenges. Here we present a new method based on blade coating of a blend of conjugated small molecules and amorphous insulating polymers to produce OTFTs with consistently excellent performance characteristics (carrier mobility as high as 6.7 cm2 V−1 s−1, low threshold voltages of<1 V and low subthreshold swings <0.5 V dec−1). Our findings demonstrate that careful control over phase separation and crystallization can yield solution-printed polycrystalline organic semiconductor films with transport properties and other figures of merit on par with their single-crystal counterparts.

Solution-printed organic semiconductor blends exhibiting transport properties on par with single crystals

KAUST Repository

Niazi, Muhammad Rizwan

2015-11-23

Solution-printed organic semiconductors have emerged in recent years as promising contenders for roll-to-roll manufacturing of electronic and optoelectronic circuits. The stringent performance requirements for organic thin-film transistors (OTFTs) in terms of carrier mobility, switching speed, turn-on voltage and uniformity over large areas require performance currently achieved by organic single-crystal devices, but these suffer from scale-up challenges. Here we present a new method based on blade coating of a blend of conjugated small molecules and amorphous insulating polymers to produce OTFTs with consistently excellent performance characteristics (carrier mobility as high as 6.7 cm2 V−1 s−1, low threshold voltages of<1 V and low subthreshold swings <0.5 V dec−1). Our findings demonstrate that careful control over phase separation and crystallization can yield solution-printed polycrystalline organic semiconductor films with transport properties and other figures of merit on par with their single-crystal counterparts.

Solution-printed organic semiconductor blends exhibiting transport properties on par with single crystals.

Science.gov (United States)

Niazi, Muhammad R; Li, Ruipeng; Qiang Li, Er; Kirmani, Ahmad R; Abdelsamie, Maged; Wang, Qingxiao; Pan, Wenyang; Payne, Marcia M; Anthony, John E; Smilgies, Detlef-M; Thoroddsen, Sigurdur T; Giannelis, Emmanuel P; Amassian, Aram

2015-11-23

Solution-printed organic semiconductors have emerged in recent years as promising contenders for roll-to-roll manufacturing of electronic and optoelectronic circuits. The stringent performance requirements for organic thin-film transistors (OTFTs) in terms of carrier mobility, switching speed, turn-on voltage and uniformity over large areas require performance currently achieved by organic single-crystal devices, but these suffer from scale-up challenges. Here we present a new method based on blade coating of a blend of conjugated small molecules and amorphous insulating polymers to produce OTFTs with consistently excellent performance characteristics (carrier mobility as high as 6.7 cm(2) V(-1) s(-1), low threshold voltages oforganic semiconductor films with transport properties and other figures of merit on par with their single-crystal counterparts.

Discontinuity Preserving Image Registration through Motion Segmentation: A Primal-Dual Approach

Directory of Open Access Journals (Sweden)

Silja Kiriyanthan

2016-01-01

Full Text Available Image registration is a powerful tool in medical image analysis and facilitates the clinical routine in several aspects. There are many well established elastic registration methods, but none of them can so far preserve discontinuities in the displacement field. These discontinuities appear in particular at organ boundaries during the breathing induced organ motion. In this paper, we exploit the fact that motion segmentation could play a guiding role during discontinuity preserving registration. The motion segmentation is embedded in a continuous cut framework guaranteeing convexity for motion segmentation. Furthermore we show that a primal-dual method can be used to estimate a solution to this challenging variational problem. Experimental results are presented for MR images with apparent breathing induced sliding motion of the liver along the abdominal wall.

Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics

International Nuclear Information System (INIS)

Maroy, R.; Boisgard, R.; Comtat, C.; Dolle, F.; Trebossen, R.; Tavitian, B.; Frouin, V.; Cathier, P.; Duchesnay, E.; D; Nielsen, P.E.

2008-01-01

Positron emission tomography (PET) is a useful tool for pharmacokinetics studies in rodents during the preclinical phase of drug and tracer development. However, rodent organs are small as compared to the scanner's intrinsic resolution and are affected by physiological movements. We present a new method for the segmentation of rodent whole-body PET images that takes these two difficulties into account by estimating the pharmacokinetics far from organ borders. The segmentation method proved efficient on whole-body numerical rat phantom simulations, including 3-14 organs, together with physiological movements (heart beating, breathing, and bladder filling). The method was resistant to spillover and physiological movements, while other methods failed to obtain a correct segmentation. The radioactivity concentrations calculated with this method also showed an excellent correlation with the manual delineation of organs in a large set of preclinical images. In addition, it was faster, detected more organs, and extracted organs' mean time activity curves with a better confidence on the measure than manual delineation. (authors)

Fast iterative segmentation of high resolution medical images

International Nuclear Information System (INIS)

Hebert, T.J.

1996-01-01

Various applications in positron emission tomography (PET), single photon emission computed tomography (SPECT) and magnetic resonance imaging (MRI) require segmentation of 20 to 60 high resolution images of size 256x256 pixels in 3-9 seconds per image. This places particular constraints on the design of image segmentation algorithms. This paper examines the trade-offs in segmenting images based on fitting a density function to the pixel intensities using curve-fitting versus the maximum likelihood method. A quantized data representation is proposed and the EM algorithm for fitting a finite mixture density function to the quantized representation for an image is derived. A Monte Carlo evaluation of mean estimation error and classification error showed that the resulting quantized EM algorithm dramatically reduces the required computation time without loss of accuracy

High-dynamic-range imaging for cloud segmentation

Science.gov (United States)

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

2018-04-01

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

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.

Texture Segmentation Based on Wavelet and Kohonen Network for Remotely Sensed Images

NARCIS (Netherlands)

Chen, Z.; Feng, T.J.; Feng, T.J.; Houkes, Z.

1999-01-01

In this paper, an approach based on wavelet decomposition and Kohonen's self-organizing map is developed for image segmentation. After performing the 2D wavelet transform of image, some features are extracted for texture segmentation, and the Kohonen neural network is used to accomplish feature

Epitaxial Growth of an Organic p-n Heterojunction: C60 on Single-Crystal Pentacene.

Science.gov (United States)

Nakayama, Yasuo; Mizuno, Yuta; Hosokai, Takuya; Koganezawa, Tomoyuki; Tsuruta, Ryohei; Hinderhofer, Alexander; Gerlach, Alexander; Broch, Katharina; Belova, Valentina; Frank, Heiko; Yamamoto, Masayuki; Niederhausen, Jens; Glowatzki, Hendrik; Rabe, Jürgen P; Koch, Norbert; Ishii, Hisao; Schreiber, Frank; Ueno, Nobuo

2016-06-01

Designing molecular p-n heterojunction structures, i.e., electron donor-acceptor contacts, is one of the central challenges for further development of organic electronic devices. In the present study, a well-defined p-n heterojunction of two representative molecular semiconductors, pentacene and C60, formed on the single-crystal surface of pentacene is precisely investigated in terms of its growth behavior and crystallographic structure. C60 assembles into a (111)-oriented face-centered-cubic crystal structure with a specific epitaxial orientation on the (001) surface of the pentacene single crystal. The present experimental findings provide molecular scale insights into the formation mechanisms of the organic p-n heterojunction through an accurate structural analysis of the single-crystalline molecular contact.

Successful Recovery and Transplantation of 11 Organs Including Face, Bilateral Upper Extremities, and Thoracic and Abdominal Organs From a Single Deceased Organ Donor.

Science.gov (United States)

Tullius, Stefan G; Pomahac, Bohdan; Kim, Heung Bae; Carty, Matthew J; Talbot, Simon G; Nelson, Helen M; Delmonico, Francis L

2016-10-01

We report on the to date largest recovery of 11 organs from a single deceased donor with the transplantation of face, bilateral upper extremities, heart, 1 lung, liver (split for 2 recipients), kidneys, pancreas, and intestine. Although logistically challenging, this case demonstrates the feasibility and safety of the recovery of multiple thoracic and abdominal organs with multiple vascular composite allotransplants and tissues. Our experience of 8 additional successful multiple vascular composite allotransplants, thoracic, and abdominal organ recoveries suggests that such procedures are readily accomplishable from the same deceased donor.

Hysteretic features of Ising-type segmented nanostructure with alternating magnetic wires

International Nuclear Information System (INIS)

Kantar, Ersin

2016-01-01

In the present study, a theoretical approach to investigate the hysteresis behaviors in segmented nanowires is described and applied to spin-1/2 and spin-1 hexagonal nanowire. The hysteresis loop, coercive field and remanent magnetization of a segmented Ising nanowire (SIN) are obtained by using the effective-field theory with correlations. The effects of the temperature, crystal field and geometrical parameters of nanowires on the hysteresis behaviors of the system are investigated. A number of characteristic behaviors are found, such as the occurrence of single and triple hysteresis loops for appropriate values of the crystal field. The hysteresis behaviors are also strongly dependent on geometrical parameters. Comparisons between the obtained theoretical results and some experimental works of segmented nanowire arrays with hysteresis behaviors are made and a very good agreement is obtained. - Highlights: • The hysteresis behaviors of a segmented Ising nanowire are obtained. • The effective-field theory with correlations are used to calculations. • The effects of the temperature and crystal field on the system are investigated. • The geometrical parameters have a significant effect on the system are observed. • The single and triple loops for appropriate values of the crystal field are obtained.

Single Molecule Study of DNA Organization and Recombination

Science.gov (United States)

Xiao, Botao

We have studied five projects related to DNA organization and recombination using mainly single molecule force-spectroscopy and statistical tools. First, HU is one of the most abundant DNA-organizing proteins in bacterial chromosomes and participates in gene regulation. We report experiments that study the dependence of DNA condensation by HU on force, salt and HU concentration. A first important result is that at physiological salt levels, HU only bends DNA, resolving a previous paradox of why a chromosome-compacting protein should have a DNA-stiffening function. A second major result is quantitative demonstration of strong dependencies of HU-DNA dissociation on both salt concentration and force. Second, we have used a thermodynamic Maxwell relation to count proteins driven off large DNAs by tension, an effect important to understanding DNA organization. Our results compare well with estimates of numbers of proteins HU and Fis in previous studies. We have also shown that a semi-flexible polymer model describes our HU experimental data well. The force-dependent binding suggests mechano-chemical mechanisms for gene regulation. Third, the elusive role of protein H1 in chromatin has been clarified with purified H1 and Xenopus extracts. We find that H1 compacts DNA by both bending and looping. Addition of H1 enhances chromatin formation and maintains the plasticity of the chromatin. Fourth, the topology and mechanics of DNA twisting are critical to DNA organization and recombination. We have systematically measured DNA extension as a function of linking number density from 0.08 to -2 with holding forces from 0.2 to 2.4 pN. Unlike previous proposals, the DNA extension decreases with negative linking number. Finally, DNA recombination is a dynamic process starting from enzyme-DNA binding. We report that the Int-DBD domain of lambda integrase binds to DNA without compaction at low Int-DBD concentration. High concentration of Int-DBD loops DNA below a threshold force

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.

Efficient Algorithms for Analyzing Segmental Duplications, Deletions, and Inversions in Genomes

Science.gov (United States)

Kahn, Crystal L.; Mozes, Shay; Raphael, Benjamin J.

Segmental duplications, or low-copy repeats, are common in mammalian genomes. In the human genome, most segmental duplications are mosaics consisting of pieces of multiple other segmental duplications. This complex genomic organization complicates analysis of the evolutionary history of these sequences. Earlier, we introduced a genomic distance, called duplication distance, that computes the most parsimonious way to build a target string by repeatedly copying substrings of a source string. We also showed how to use this distance to describe the formation of segmental duplications according to a two-step model that has been proposed to explain human segmental duplications. Here we describe polynomial-time exact algorithms for several extensions of duplication distance including models that allow certain types of substring deletions and inversions. These extensions will permit more biologically realistic analyses of segmental duplications in genomes.

Pre-clinical evaluation of an inverse planning module for segmental MLC based IMRT delivery

International Nuclear Information System (INIS)

Georg, Dietmar; Kroupa, Bernhard

2002-01-01

Phantom tests are performed for pre-clinical evaluation of a commercial inverse planning system (HELAX TMS, V 6.0) for segmented multileaf collimator (MLC) intensity modulated radiotherapy (IMRT) delivery. The optimization module has available two optimization algorithms: the target primary feasibility and the weighted feasibility algorithm, only the latter allows the user to specify weights for structures. In the first series, single beam tests are performed to evaluate the outcome of inverse planning in terms of plausibility for the following situations: oblique incidence, presence of inhomogeneities, multiple targets at different depths and multiple targets with different desired doses. Additionally, for these tests a manual plan is made for comparison. In the absence of organs at risk, both the optimization algorithms are found to assign the highest priority to low dose constraints for targets. In the second series, tests resembling clinical relevant configurations (simultaneous boost and concave target with critical organ) are performed with multiple beam arrangements in order to determine the impact of the system's configuration on inverse planning. It is found that the definition of certain segment number and segment size limitations does not largely compromise treatment plans when using multiple beams. On the other hand, these limitations are important for delivery efficiency and dosimetry. For the number of iterations and voxels per volume of interest, standard values in the system's configuration are considered to be sufficient. Additionally, it is demonstrated that precautions must be taken to precisely define treatment goals when using computerized treatment optimization. Similar phantom tests could be used for a direct dosimetric verification of all steps from inverse treatment planning to IMRT delivery. (note)

The Single Transmembrane Segment of Minimal Sensor DesK Senses Temperature via a Membrane-Thickness Caliper.

Science.gov (United States)

Inda, Maria E; Oliveira, Rafael G; de Mendoza, Diego; Cybulski, Larisa E

2016-11-01

Thermosensors detect temperature changes and trigger cellular responses crucial for survival at different temperatures. The thermosensor DesK is a transmembrane (TM) histidine kinase which detects a decrease in temperature through its TM segments (TMS). Here, we address a key issue: how a physical stimulus such as temperature can be converted into a cellular response. We show that the thickness of Bacillus lipid membranes varies with temperature and that such variations can be detected by DesK with great precision. On the basis of genetic studies and measurements of in vitro activity of a DesK construct with a single TMS (minimal sensor DesK [MS-DesK]), reconstituted in liposomes, we propose an interplay mechanism directed by a conserved dyad, phenylalanine 8-lysine 10. This dyad is critical to anchor the only transmembrane segment of the MS-DesK construct to the extracellular water-lipid interphase and is required for the transmembrane segment of MS-DesK to function as a caliper for precise measurement of membrane thickness. The data suggest that positively charged lysine 10, which is located in the hydrophobic core of the membrane but is close to the water-lipid interface, pulls the transmembrane region toward the water phase to localize its charge at the interface. Nevertheless, the hydrophobic residue phenylalanine 8, located at the N-terminal extreme of the TMS, has a strong tendency to remain in the lipid phase, impairing access of lysine 10 to the water phase. The outcome of this interplay is a fine-tuned sensitivity to membrane thickness that elicits conformational changes that favor different signaling states of the protein. The ability to sense and respond to extracellular signals is essential for cell survival. One example is the cellular response to temperature variation. How do cells "sense" temperature changes? It has been proposed that the bacterial thermosensor DesK acts as a molecular caliper measuring membrane thickness variations that would occur

A hybrid method for airway segmentation and automated measurement of bronchial wall thickness on CT.

Science.gov (United States)

Xu, Ziyue; Bagci, Ulas; Foster, Brent; Mansoor, Awais; Udupa, Jayaram K; Mollura, Daniel J

2015-08-01

Inflammatory and infectious lung diseases commonly involve bronchial airway structures and morphology, and these abnormalities are often analyzed non-invasively through high resolution computed tomography (CT) scans. Assessing airway wall surfaces and the lumen are of great importance for diagnosing pulmonary diseases. However, obtaining high accuracy from a complete 3-D airway tree structure can be quite challenging. The airway tree structure has spiculated shapes with multiple branches and bifurcation points as opposed to solid single organ or tumor segmentation tasks in other applications, hence, it is complex for manual segmentation as compared with other tasks. For computerized methods, a fundamental challenge in airway tree segmentation is the highly variable intensity levels in the lumen area, which often causes a segmentation method to leak into adjacent lung parenchyma through blurred airway walls or soft boundaries. Moreover, outer wall definition can be difficult due to similar intensities of the airway walls and nearby structures such as vessels. In this paper, we propose a computational framework to accurately quantify airways through (i) a novel hybrid approach for precise segmentation of the lumen, and (ii) two novel methods (a spatially constrained Markov random walk method (pseudo 3-D) and a relative fuzzy connectedness method (3-D)) to estimate the airway wall thickness. We evaluate the performance of our proposed methods in comparison with mostly used algorithms using human chest CT images. Our results demonstrate that, on publicly available data sets and using standard evaluation criteria, the proposed airway segmentation method is accurate and efficient as compared with the state-of-the-art methods, and the airway wall estimation algorithms identified the inner and outer airway surfaces more accurately than the most widely applied methods, namely full width at half maximum and phase congruency. Copyright © 2015. Published by Elsevier B.V.

[Pharmacology of local anesthetics and clinical aspects of segmental blocking. II. Spinal anesthesia].

Science.gov (United States)

Kozlov, S P; Svetlov, V A; Luk'ianov, M V

1998-01-01

Clinical picture of development of segmental blocking after subarachnoidal injection of hyperbaric solutions of 0.75% bupivacaine, 5% ultracaine, and isobaric 0.5% bupivacaine is studied. A total of 152 patients operated on the lower part of the body and the lower limbs were examined under conditions of single, prolonged subarachnoidal, and combined spinal epidural anesthesia. Ultracaine and bupivacaine in different concentrations with different barism provided anesthesia equivalent by the efficacy, depth, and dissemination of sensory block. Segmental blocking with 5% ultracaine was characterized by the shortest latent period (3.14 +/- 0.16 min, p anesthesia in comparison with a single injection, and combined spinal epidural anesthesia shortened the latent period of segmental blocking and ensured intraoperative anesthesia and postoperative analgesia at the expense of the epidural component.

Segmentation and Visualisation of Human Brain Structures

Energy Technology Data Exchange (ETDEWEB)

Hult, Roger

2003-10-01

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

Segmentation and Visualisation of Human Brain Structures

International Nuclear Information System (INIS)

Hult, Roger

2003-01-01

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

Segmentation of Nonstationary Time Series with Geometric Clustering

DEFF Research Database (Denmark)

Bocharov, Alexei; Thiesson, Bo

2013-01-01

We introduce a non-parametric method for segmentation in regimeswitching time-series models. The approach is based on spectral clustering of target-regressor tuples and derives a switching regression tree, where regime switches are modeled by oblique splits. Such models can be learned efficiently...... from data, where clustering is used to propose one single split candidate at each split level. We use the class of ART time series models to serve as illustration, but because of the non-parametric nature of our segmentation approach, it readily generalizes to a wide range of time-series models that go...

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

Directory of Open Access Journals (Sweden)

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.

An innovation model of alumni relationship management: Alumni segmentation analysis

Directory of Open Access Journals (Sweden)

Natthawat Rattanamethawong

2018-01-01

Full Text Available The purpose of this study was to cluster alumni into segments to better understand the alumni's characteristics, lifestyles, types of behavior, and interests. A sample of 300 university alumni records was used to obtain their respective attribute values consisting of demographics, preferred communication channels, lifestyle, activities/interests, and expectation from university, needed information, donation willingness, and frequency of contact. The researcher used logistic regression and the k-mean clustering technique to analyze the data from the survey. Five segments could be derived from the analysis. Segment 3, the so-called “Mid Age Religious” contained the highest portion while segment 5, the so-called “Elaborate Cohort” had the least portion. Most of the population under these two segments was female. Differences were identified in age, marital status, education, occupation, position, income, experience, and field of work. The Elaborate Cohort segment represented young females having a bachelor degree, with low experience and low income, working for their first employer, and still enjoying being single. Another segment with similar values of attributes as the Elaborate Cohort was segment 1, the so-called “Activist Mainstreamer” whose field of work was computer technology. The segment called “Senior League” consisted of members older than 41 years like the Mid Age Religious segment, however all members were male. The last segment, the so-called “Passionate Learner” had members aged between 31 and 40 years. In conclusion, the results of this study can assist in formulating strategic marketing by alumni associations to satisfy and engage their alumni. Keywords: cluster, data mining, segmentation analysis, university alumni

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)

Interactive and scale invariant segmentation of the rectum/sigmoid via user-defined templates

Science.gov (United States)

Lüddemann, Tobias; Egger, Jan

2016-03-01

Among all types of cancer, gynecological malignancies belong to the 4th most frequent type of cancer among women. Besides chemotherapy and external beam radiation, brachytherapy is the standard procedure for the treatment of these malignancies. In the progress of treatment planning, localization of the tumor as the target volume and adjacent organs of risks by segmentation is crucial to accomplish an optimal radiation distribution to the tumor while simultaneously preserving healthy tissue. Segmentation is performed manually and represents a time-consuming task in clinical daily routine. This study focuses on the segmentation of the rectum/sigmoid colon as an Organ-At-Risk in gynecological brachytherapy. The proposed segmentation method uses an interactive, graph-based segmentation scheme with a user-defined template. The scheme creates a directed two dimensional graph, followed by the minimal cost closed set computation on the graph, resulting in an outlining of the rectum. The graphs outline is dynamically adapted to the last calculated cut. Evaluation was performed by comparing manual segmentations of the rectum/sigmoid colon to results achieved with the proposed method. The comparison of the algorithmic to manual results yielded to a Dice Similarity Coefficient value of 83.85+/-4.08%, in comparison to 83.97+/-8.08% for the comparison of two manual segmentations of the same physician. Utilizing the proposed methodology resulted in a median time of 128 seconds per dataset, compared to 300 seconds needed for pure manual segmentation.

Preferences towards organic and functional yoghurt in Republic of Srpska

Directory of Open Access Journals (Sweden)

Grubor Aleksandar

2015-01-01

Full Text Available This article presents the results of the research of preferences towards organic and functional yoghurt, conducted in Republic of Srpska, from January to May, 2014 (n=200. Generally, respondents do not consider whether yoghurt being or not being organic or functional as very important. They partially prefer functional yoghurts, but prefer yoghurts made from conventionally produced milk. For both, organic and functional food, consumers were divided into two segments - the first which considered yoghurt being organic (or functional among three the most important attributes of a product and the second segments comprising of all other respondents. Hereby, 8% of respondents belonged to the first segment for organic and 20% for functional yoghurt. Compared to second segments, consumers belonging to the first segment for organic yoghurt statistically significantly differ from others by valuating food importance for health more, while for functional yoghurt by assessing own physical health worse.

Soft segmented inchworm robot with dielectric elastomer muscles

Science.gov (United States)

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

2014-03-01

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

Local Electronic Structure of a Single-Layer Porphyrin-Containing Covalent Organic Framework

KAUST Repository

Chen, Chen; Joshi, Trinity; Li, Huifang; Chavez, Anton D.; Pedramrazi, Zahra; Liu, Pei-Nian; Li, Hong; Dichtel, William R.; Bredas, Jean-Luc; Crommie, Michael F.

2017-01-01

We have characterized the local electronic structure of a porphyrin-containing single-layer covalent organic framework (COF) exhibiting a square lattice. The COF monolayer was obtained by the deposition of 2,5-dimethoxybenzene-1,4-dicarboxaldehyde

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

Single Molecule Spectroelectrochemistry of Interfacial Charge Transfer Dynamics In Hybrid Organic Solar Cell

Energy Technology Data Exchange (ETDEWEB)

Pan, Shanlin [Univ. of Alabama, Tuscaloosa, AL (United States)

2014-11-16

Our research under support of this DOE grant is focused on applied and fundamental aspects of model organic solar cell systems. Major accomplishments are: 1) we developed a spectroelectorchemistry technique of single molecule single nanoparticle method to study charge transfer between conjugated polymers and semiconductor at the single molecule level. The fluorescence of individual fluorescent polymers at semiconductor surfaces was shown to exhibit blinking behavior compared to molecules on glass substrates. Single molecule fluorescence excitation anisotropy measurements showed the conformation of the polymer molecules did not differ appreciably between glass and semiconductor substrates. The similarities in molecular conformation suggest that the observed differences in blinking activity are due to charge transfer between fluorescent polymer and semiconductor, which provides additional pathways between states of high and low fluorescence quantum efficiency. Similar spectroelectrochemistry work has been done for small organic dyes for understand their charge transfer dynamics on various substrates and electrochemical environments; 2) We developed a method of transferring semiconductor nanoparticles (NPs) and graphene oxide (GO) nanosheets into organic solvent for a potential electron acceptor in bulk heterojunction organic solar cells which employed polymer semiconductor as the electron donor. Electron transfer from the polymer semiconductor to semiconductor and GO in solutions and thin films was established through fluorescence spectroscopy and electroluminescence measurements. Solar cells containing these materials were constructed and evaluated using transient absorption spectroscopy and dynamic fluorescence techniques to understand the charge carrier generation and recombination events; 3) We invented a spectroelectorchemistry technique using light scattering and electroluminescence for rapid size determination and studying electrochemistry of single NPs in an

Segment-specific terminal sequences of Bunyamwera bunyavirus regulate genome replication

International Nuclear Information System (INIS)

Barr, John N.; Elliott, Richard M.; Dunn, Ewan F.; Wertz, Gail W.

2003-01-01

Bunyamwera virus (BUNV) is the prototype of both the Orthobunyavirus genus and the Bunyaviridae family of segmented negative sense RNA viruses. The tripartite BUNV genome consists of small (S), medium (M), and large (L) segments that are transcribed to give a single mRNA and replicated to generate an antigenome that is the template for synthesis of further genomic RNA strands. We modified an existing cDNA-derived RNA synthesis system to allow identification of BUNV RNA replication and transcription products by direct metabolic labeling. Direct RNA analysis allowed us to distinguish between template activities that affected either RNA replication or mRNA transcription, an ability that was not possible using previous reporter gene expression assays. We generated genome analogs containing the entire nontranslated terminal sequences of the S, M, and L BUNV segments surrounding a common sequence. Analysis of RNAs synthesized from these templates revealed that the relative abilities of BUNV segments to perform RNA replication was M > L > S. Exchange of segment-specific terminal nucleotides identified a 12-nt region located within both the 3' and 5' termini of the M segment that correlated with its high replication ability

Volumetric multimodality neural network for brain tumor segmentation

Science.gov (United States)

Silvana Castillo, Laura; Alexandra Daza, Laura; Carlos Rivera, Luis; Arbeláez, Pablo

2017-11-01

Brain lesion segmentation is one of the hardest tasks to be solved in computer vision with an emphasis on the medical field. We present a convolutional neural network that produces a semantic segmentation of brain tumors, capable of processing volumetric data along with information from multiple MRI modalities at the same time. This results in the ability to learn from small training datasets and highly imbalanced data. Our method is based on DeepMedic, the state of the art in brain lesion segmentation. We develop a new architecture with more convolutional layers, organized in three parallel pathways with different input resolution, and additional fully connected layers. We tested our method over the 2015 BraTS Challenge dataset, reaching an average dice coefficient of 84%, while the standard DeepMedic implementation reached 74%.

Exploring DeepMedic for the purpose of segmenting white matter hyperintensity lesions

Science.gov (United States)

Lippert, Fiona; Cheng, Bastian; Golsari, Amir; Weiler, Florian; Gregori, Johannes; Thomalla, Götz; Klein, Jan

2018-02-01

DeepMedic, an open source software library based on a multi-channel multi-resolution 3D convolutional neural network, has recently been made publicly available for brain lesion segmentations. It has already been shown that segmentation tasks on MRI data of patients having traumatic brain injuries, brain tumors, and ischemic stroke lesions can be performed very well. In this paper we describe how it can efficiently be used for the purpose of detecting and segmenting white matter hyperintensity lesions. We examined if it can be applied to single-channel routine 2D FLAIR data. For evaluation, we annotated 197 datasets with different numbers and sizes of white matter hyperintensity lesions. Our experiments have shown that substantial results with respect to the segmentation quality can be achieved. Compared to the original parametrization of the DeepMedic neural network, the timings for training can be drastically reduced if adjusting corresponding training parameters, while at the same time the Dice coefficients remain nearly unchanged. This enables for performing a whole training process within a single day utilizing a NVIDIA GeForce GTX 580 graphics board which makes this library also very interesting for research purposes on low-end GPU hardware.

Fabricating an organic complementary inverter by integrating two transistors on a single substrate

International Nuclear Information System (INIS)

Wang Jun; Wei Bin; Zhang Jianhua

2008-01-01

Organic complementary inverters were fabricated by integrating two transistors of different electric type on a single substrate. One is a p-type organic heterojunction transistor with a depletion–accumulation mode that acts as a load element. The other is an n-type transistor with an accumulation mode that acts as a drive element. Typical inverter characteristics with a voltage gain of 12 were obtained. Compared with conventional devices, our organic complementary inverter used only one-step patterning of an organic semiconductor, and simultaneously suppressed the leakage current between supply voltage and ground. Therefore, current studies provide a simpler path to fabrication of organic complementary circuits

Two-Segment Foot Model for the Biomechanical Analysis of Squat

OpenAIRE

Panero, E.; Gastaldi, L.; Rapp, W.

2017-01-01

Squat exercise is acquiring interest in many fields, due to its benefits in improving health and its biomechanical similarities to a wide range of sport motions and the recruitment of many body segments in a single maneuver. Several researches had examined considerable biomechanical aspects of lower limbs during squat, but not without limitations. The main goal of this study focuses on the analysis of the foot contribution during a partial body weight squat, using a two-segment foot model tha...

Corrective action strategy for single-shell tanks containing organic chemicals

International Nuclear Information System (INIS)

Turner, D.A.

1993-08-01

A Waste Tank Organic Safety Program (Program) Plan is to be transmitted to the U.S. Department of Energy, Richland Operations Office (RL) for approval by December 31, 1993. In April 1993 an agreement was reached among cognizant U.S. Department of Energy - Headquarters (HQ), RL and Westinghouse Hanford Company (WHC) staff that the Program Plan would be preceded by a ''Corrective Action Strategy,'' which addressed selected planning elements supporting the Program Plan. The ''Corrective Action Strategy'' would be reviewed and consensus reached regarding the planning elements. A Program Plan reflecting this consensus would then be prepared. A preliminary ''corrective action strategy'' is presented for resolving the organic tanks safety issue based on the work efforts recommended in the ISB (Interim Safety Basis for Hanford Site tank farm facilities). A ''corrective action strategy'' logic was prepared for individual SSTs (single-shell tanks), or a group of SSTs having similar characteristics, as appropriate. Four aspects of the organic tanks safety issue are addressed in the ISB: SSTs with the potential for combustion in the tank's headspace; combustion of a floating organic layer as a pool fire; surface fires in tanks that formerly held floating organic layers; SSTs with the potential for organic-nitrate reactions. A preliminary ''corrective action strategy'' for each aspect of the organic tanks safety issue is presented

Novel active contour model based on multi-variate local Gaussian distribution for local segmentation of MR brain images

Science.gov (United States)

Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong

2017-12-01

Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.

On-chip manipulation of single microparticles, cells, and organisms using surface acoustic waves.

Science.gov (United States)

Ding, Xiaoyun; Lin, Sz-Chin Steven; Kiraly, Brian; Yue, Hongjun; Li, Sixing; Chiang, I-Kao; Shi, Jinjie; Benkovic, Stephen J; Huang, Tony Jun

2012-07-10

Techniques that can dexterously manipulate single particles, cells, and organisms are invaluable for many applications in biology, chemistry, engineering, and physics. Here, we demonstrate standing surface acoustic wave based "acoustic tweezers" that can trap and manipulate single microparticles, cells, and entire organisms (i.e., Caenorhabditis elegans) in a single-layer microfluidic chip. Our acoustic tweezers utilize the wide resonance band of chirped interdigital transducers to achieve real-time control of a standing surface acoustic wave field, which enables flexible manipulation of most known microparticles. The power density required by our acoustic device is significantly lower than its optical counterparts (10,000,000 times less than optical tweezers and 100 times less than optoelectronic tweezers), which renders the technique more biocompatible and amenable to miniaturization. Cell-viability tests were conducted to verify the tweezers' compatibility with biological objects. With its advantages in biocompatibility, miniaturization, and versatility, the acoustic tweezers presented here will become a powerful tool for many disciplines of science and engineering.

Gaussian mixtures on tensor fields for segmentation: applications to medical imaging.

Science.gov (United States)

de Luis-García, Rodrigo; Westin, Carl-Fredrik; Alberola-López, Carlos

2011-01-01

In this paper, we introduce a new approach for tensor field segmentation based on the definition of mixtures of Gaussians on tensors as a statistical model. Working over the well-known Geodesic Active Regions segmentation framework, this scheme presents several interesting advantages. First, it yields a more flexible model than the use of a single Gaussian distribution, which enables the method to better adapt to the complexity of the data. Second, it can work directly on tensor-valued images or, through a parallel scheme that processes independently the intensity and the local structure tensor, on scalar textured images. Two different applications have been considered to show the suitability of the proposed method for medical imaging segmentation. First, we address DT-MRI segmentation on a dataset of 32 volumes, showing a successful segmentation of the corpus callosum and favourable comparisons with related approaches in the literature. Second, the segmentation of bones from hand radiographs is studied, and a complete automatic-semiautomatic approach has been developed that makes use of anatomical prior knowledge to produce accurate segmentation results. Copyright © 2010 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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

2018-04-01

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

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.

Market orientation for the hotel segment : the portuguese case

OpenAIRE

Raposo, Mario; Estevão, Cristina; Mainardes, Emerson; Domingues, Maria José

2010-01-01

In view of the importance of the hotel segment for the tourism and for the economy of countries such as Portugal, the objective of this study was to measure the level of orientation for the market of the largest hotel groups of Portugal. This investigation initially emphasized the importance of the marketing for the organizations, mainly the orientation for the market. After a brief explanation on the hotel segment in Portugal, an empirical study was presented, of quantitative, exploratory an...

Development of the WDS Russian-Ukrainian Segment

Directory of Open Access Journals (Sweden)

Marsel Shaimardanov

2013-01-01

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

The validation index: a new metric for validation of segmentation algorithms using two or more expert outlines with application to radiotherapy planning.

Science.gov (United States)

Juneja, Prabhjot; Evans, Philp M; Harris, Emma J

2013-08-01

Validation is required to ensure automated segmentation algorithms are suitable for radiotherapy target definition. In the absence of true segmentation, algorithmic segmentation is validated against expert outlining of the region of interest. Multiple experts are used to overcome inter-expert variability. Several approaches have been studied in the literature, but the most appropriate approach to combine the information from multiple expert outlines, to give a single metric for validation, is unclear. None consider a metric that can be tailored to case-specific requirements in radiotherapy planning. Validation index (VI), a new validation metric which uses experts' level of agreement was developed. A control parameter was introduced for the validation of segmentations required for different radiotherapy scenarios: for targets close to organs-at-risk and for difficult to discern targets, where large variation between experts is expected. VI was evaluated using two simulated idealized cases and data from two clinical studies. VI was compared with the commonly used Dice similarity coefficient (DSCpair - wise) and found to be more sensitive than the DSCpair - wise to the changes in agreement between experts. VI was shown to be adaptable to specific radiotherapy planning scenarios.

Alternate Double Single Track Lines

Energy Technology Data Exchange (ETDEWEB)

Moraga Contreras, P.; Grande Andrade, Z.; Castillo Ron, E.

2016-07-01

The paper discusses the advantages and shortcomings of alternate double single track (ADST) lines with respect to double track lines for high speed lines. ADST lines consists of sequences of double and single track segments optimally selected in order to reduce the construction and maintenance costs of railway lines and to optimize the timetables used to satisfy a given demand. The single tracks are selected to coincide with expensive segments (tunnels and viaducts) and the double tracks are chosen to coincide with flat areas and only where they are necessary. At the same time, departure times are adjusted for trains to cross at the cheap double track segments. This alternative can be used for new lines and also for existing conventional lines where some new tracks are to be constructed to reduce travel time (increase speed). The ADST proposal is illustrated with some examples of both types (new lines and where conventional lines exist), including the Palencia-Santander, the Santiago-Valparaíso-Viña del Mar and the Dublin-Belfast lines, where very important reductions (90 %) are obtained, especially where a railway infrastructure already exist. (Author)

Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics

DEFF Research Database (Denmark)

Maroy, Renaud; Boisgard, Raphaël; Comtat, Claude

2008-01-01

Positron emission tomography (PET) is a useful tool for pharmacokinetics studies in rodents during the preclinical phase of drug and tracer development. However, rodent organs are small as compared to the scanner's intrinsic resolution and are affected by physiological movements. We present a new...... method for the segmentation of rodent whole-body PET images that takes these two difficulties into account by estimating the pharmacokinetics far from organ borders. The segmentation method proved efficient on whole-body numerical rat phantom simulations, including 3-14 organs, together...

SU-C-207B-03: A Geometrical Constrained Chan-Vese Based Tumor Segmentation Scheme for PET

International Nuclear Information System (INIS)

Chen, L; Zhou, Z; Wang, J

2016-01-01

Purpose: Accurate segmentation of tumor in PET is challenging when part of tumor is connected with normal organs/tissues with no difference in intensity. Conventional segmentation methods, such as thresholding or region growing, cannot generate satisfactory results in this case. We proposed a geometrical constrained Chan-Vese based scheme to segment tumor in PET for this special case by considering the similarity between two adjacent slices. Methods: The proposed scheme performs segmentation in a slice-by-slice fashion where an accurate segmentation of one slice is used as the guidance for segmentation of rest slices. For a slice that the tumor is not directly connected to organs/tissues with similar intensity values, a conventional clustering-based segmentation method under user’s guidance is used to obtain an exact tumor contour. This is set as the initial contour and the Chan-Vese algorithm is applied for segmenting the tumor in the next adjacent slice by adding constraints of tumor size, position and shape information. This procedure is repeated until the last slice of PET containing tumor. The proposed geometrical constrained Chan-Vese based algorithm was implemented in Matlab and its performance was tested on several cervical cancer patients where cervix and bladder are connected with similar activity values. The positive predictive values (PPV) are calculated to characterize the segmentation accuracy of the proposed scheme. Results: Tumors were accurately segmented by the proposed method even when they are connected with bladder in the image with no difference in intensity. The average PPVs were 0.9571±0.0355 and 0.9894±0.0271 for 17 slices and 11 slices of PET from two patients, respectively. Conclusion: We have developed a new scheme to segment tumor in PET images for the special case that the tumor is quite similar to or connected to normal organs/tissues in the image. The proposed scheme can provide a reliable way for segmenting tumors.

SU-C-207B-03: A Geometrical Constrained Chan-Vese Based Tumor Segmentation Scheme for PET

Energy Technology Data Exchange (ETDEWEB)

Chen, L; Zhou, Z; Wang, J [UT Southwestern Medical Center, Dallas, TX (United States)

2016-06-15

Purpose: Accurate segmentation of tumor in PET is challenging when part of tumor is connected with normal organs/tissues with no difference in intensity. Conventional segmentation methods, such as thresholding or region growing, cannot generate satisfactory results in this case. We proposed a geometrical constrained Chan-Vese based scheme to segment tumor in PET for this special case by considering the similarity between two adjacent slices. Methods: The proposed scheme performs segmentation in a slice-by-slice fashion where an accurate segmentation of one slice is used as the guidance for segmentation of rest slices. For a slice that the tumor is not directly connected to organs/tissues with similar intensity values, a conventional clustering-based segmentation method under user’s guidance is used to obtain an exact tumor contour. This is set as the initial contour and the Chan-Vese algorithm is applied for segmenting the tumor in the next adjacent slice by adding constraints of tumor size, position and shape information. This procedure is repeated until the last slice of PET containing tumor. The proposed geometrical constrained Chan-Vese based algorithm was implemented in Matlab and its performance was tested on several cervical cancer patients where cervix and bladder are connected with similar activity values. The positive predictive values (PPV) are calculated to characterize the segmentation accuracy of the proposed scheme. Results: Tumors were accurately segmented by the proposed method even when they are connected with bladder in the image with no difference in intensity. The average PPVs were 0.9571±0.0355 and 0.9894±0.0271 for 17 slices and 11 slices of PET from two patients, respectively. Conclusion: We have developed a new scheme to segment tumor in PET images for the special case that the tumor is quite similar to or connected to normal organs/tissues in the image. The proposed scheme can provide a reliable way for segmenting tumors.

Long-term in vivo imaging of multiple organs at the single cell level.

Directory of Open Access Journals (Sweden)

Benny J Chen

Full Text Available Two-photon microscopy has enabled the study of individual cell behavior in live animals. Many organs and tissues cannot be studied, especially longitudinally, because they are located too deep, behind bony structures or too close to the lung and heart. Here we report a novel mouse model that allows long-term single cell imaging of many organs. A wide variety of live tissues were successfully engrafted in the pinna of the mouse ear. Many of these engrafted tissues maintained the normal tissue histology. Using the heart and thymus as models, we further demonstrated that the engrafted tissues functioned as would be expected. Combining two-photon microscopy with fluorescent tracers, we successfully visualized the engrafted tissues at the single cell level in live mice over several months. Four dimensional (three-dimensional (3D plus time information of individual cells was obtained from this imaging. This model makes long-term high resolution 4D imaging of multiple organs possible.

Anisotropic charge transport in large single crystals of π-conjugated organic molecules.

Science.gov (United States)

Hourani, Wael; Rahimi, Khosrow; Botiz, Ioan; Koch, Felix Peter Vinzenz; Reiter, Günter; Lienerth, Peter; Heiser, Thomas; Bubendorff, Jean-Luc; Simon, Laurent

2014-05-07

The electronic properties of organic semiconductors depend strongly on the nature of the molecules, their conjugation and conformation, their mutual distance and the orientation between adjacent molecules. Variations of intramolecular distances and conformation disturb the conjugation and perturb the delocalization of charges. As a result, the mobility considerably decreases compared to that of a covalently well-organized crystal. Here, we present electrical characterization of large single crystals made of the regioregular octamer of 3-hexyl-thiophene (3HT)8 using a conductive-atomic force microscope (C-AFM) in air. We find a large anisotropy in the conduction with charge mobility values depending on the crystallographic orientation of the single crystal. The smaller conduction is in the direction of π-π stacking (along the long axis of the single crystal) with a mobility value in the order of 10(-3) cm(2) V(-1) s(-1), and the larger one is along the molecular axis (in the direction normal to the single crystal surface) with a mobility value in the order of 0.5 cm(2) V(-1) s(-1). The measured current-voltage (I-V) curves showed that along the molecular axis, the current followed an exponential dependence corresponding to an injection mode. In the π-π stacking direction, the current exhibits a space charge limited current (SCLC) behavior, which allows us to estimate the charge carrier mobility.

Influence of nuclei segmentation on breast cancer malignancy classification

Science.gov (United States)

Jelen, Lukasz; Fevens, Thomas; Krzyzak, Adam

2009-02-01

Breast Cancer is one of the most deadly cancers affecting middle-aged women. Accurate diagnosis and prognosis are crucial to reduce the high death rate. Nowadays there are numerous diagnostic tools for breast cancer diagnosis. In this paper we discuss a role of nuclear segmentation from fine needle aspiration biopsy (FNA) slides and its influence on malignancy classification. Classification of malignancy plays a very important role during the diagnosis process of breast cancer. Out of all cancer diagnostic tools, FNA slides provide the most valuable information about the cancer malignancy grade which helps to choose an appropriate treatment. This process involves assessing numerous nuclear features and therefore precise segmentation of nuclei is very important. In this work we compare three powerful segmentation approaches and test their impact on the classification of breast cancer malignancy. The studied approaches involve level set segmentation, fuzzy c-means segmentation and textural segmentation based on co-occurrence matrix. Segmented nuclei were used to extract nuclear features for malignancy classification. For classification purposes four different classifiers were trained and tested with previously extracted features. The compared classifiers are Multilayer Perceptron (MLP), Self-Organizing Maps (SOM), Principal Component-based Neural Network (PCA) and Support Vector Machines (SVM). The presented results show that level set segmentation yields the best results over the three compared approaches and leads to a good feature extraction with a lowest average error rate of 6.51% over four different classifiers. The best performance was recorded for multilayer perceptron with an error rate of 3.07% using fuzzy c-means segmentation.

Consumer knowledge structures with regards to organic foods

DEFF Research Database (Denmark)

Bredahl, Lone; Thøgersen, John; Dean, Moira

2004-01-01

associated with self-relevant consequences do not appear to discriminate clearly among segments, however. Generally, organic origin has significant links to personal values among segments of adventurous, enthusiastic, hedonistic and eco-healthy food consumers while it appears a dysfunctional means......This paper presents results of an empirical study conducted among European consumers to explore consumer knowledge structures with regard to organic foods and to identify the beliefs and the attribute-to-value chains that discriminate best among different consumer segments. Using means-end chain...... theory as the theoretical basis, the objectives of the study were met through carrying out laddering interviews with consumers in Germany, Great Britain, Denmark and Spain, using a Food-Related Lifestyle (FRL) segment-based approach and interviewing both organic and non-organic consumers. Respondents...

ST-segment resolution with bivalirudin versus heparin and routine glycoprotein IIb/IIIa inhibitors started in the ambulance in ST-segment elevation myocardial infarction patients transported for primary percutaneous coronary intervention: The EUROMAX ST-segment resolution substudy.

Science.gov (United States)

Van't Hof, Arnoud; Giannini, Francesco; Ten Berg, Jurrien; Tolsma, Rudolf; Clemmensen, Peter; Bernstein, Debra; Coste, Pierre; Goldstein, Patrick; Zeymer, Uwe; Hamm, Christian; Deliargyris, Efthymios; Steg, Philippe G

2017-08-01

Myocardial reperfusion after primary percutaneous coronary intervention (PCI) can be assessed by the extent of post-procedural ST-segment resolution. The European Ambulance Acute Coronary Syndrome Angiography (EUROMAX) trial compared pre-hospital bivalirudin and pre-hospital heparin or enoxaparin with or without GPIIb/IIIa inhibitors (GPIs) in primary PCI. This nested substudy was performed in centres routinely using pre-hospital GPI in order to compare the impact of randomized treatments on ST-resolution after primary PCI. Residual cumulative ST-segment deviation on the single one hour post-procedure electrocardiogram (ECG) was assessed by an independent core laboratory and was the primary endpoint. It was calculated that 762 evaluable patients were needed to show non-inferiority (85% power, alpha 2.5%) between randomized treatments. A total of 871 participated with electrocardiographic data available in 824 patients (95%). Residual ST-segment deviation one hour after PCI was 3.8±4.9 mm versus 3.9±5.2 mm for bivalirudin and heparin+GPI, respectively ( p=0.0019 for non-inferiority). Overall, there were no differences between randomized treatments in any measures of ST-segment resolution either before or after the index procedure. Pre-hospital treatment with bivalirudin is non-inferior to pre-hospital heparin + GPI with regard to residual ST-segment deviation or ST-segment resolution, reflecting comparable myocardial reperfusion with the two strategies.

Cryo-EM Structure Determination Using Segmented Helical Image Reconstruction.

Science.gov (United States)

Fromm, S A; Sachse, C

2016-01-01

Treating helices as single-particle-like segments followed by helical image reconstruction has become the method of choice for high-resolution structure determination of well-ordered helical viruses as well as flexible filaments. In this review, we will illustrate how the combination of latest hardware developments with optimized image processing routines have led to a series of near-atomic resolution structures of helical assemblies. Originally, the treatment of helices as a sequence of segments followed by Fourier-Bessel reconstruction revealed the potential to determine near-atomic resolution structures from helical specimens. In the meantime, real-space image processing of helices in a stack of single particles was developed and enabled the structure determination of specimens that resisted classical Fourier helical reconstruction and also facilitated high-resolution structure determination. Despite the progress in real-space analysis, the combination of Fourier and real-space processing is still commonly used to better estimate the symmetry parameters as the imposition of the correct helical symmetry is essential for high-resolution structure determination. Recent hardware advancement by the introduction of direct electron detectors has significantly enhanced the image quality and together with improved image processing procedures has made segmented helical reconstruction a very productive cryo-EM structure determination method. © 2016 Elsevier Inc. All rights reserved.

Segmenting a general practitioner market to improve recruitment outcomes.

Science.gov (United States)

Hemphill, Elizabeth; Kulik, Carol T

2011-05-01

Recruitment is an ongoing challenge in the health industry with general practitioner (GP) shortages in many areas beyond rural and Indigenous communities. This paper suggests a marketing solution that identifies different segments of the GP market for recruitment strategy development. In February 2008, 96 GPs in Australia responded to a mail questionnaire (of which 85 questionnaires were useable). A total of 350 GPs were sent the questionnaire. Respondents considered small sets of attributes in the decision to accept a new job at a general practice and selected the most and least important attribute from each set. We identified latent class clusters (cohorts) of GPs from the most-least important data. Three cohorts were found in the GP market, distinguishing practitioners who emphasised job, family or practice attributes in their decision to join a practice. Few significant demographic differences exist between the cohorts. A segmented GP market suggests two alternative recruitment strategies. One option is for general practices to target members of a single cohort (family-, job-, or practice-focussed GPs). The other option is for general practices to diversify their recruitment strategies to target all three cohorts (family-, job- and practice-focussed GPs). A single brand (practice) can have multiple advertising strategies with each strategy involving advertising activities targeting a particular consumer segment.

Lack of protein-tyrosine sulfation disrupts photoreceptor outer segment morphogenesis, retinal function and retinal anatomy.

Science.gov (United States)

Sherry, David M; Murray, Anne R; Kanan, Yogita; Arbogast, Kelsey L; Hamilton, Robert A; Fliesler, Steven J; Burns, Marie E; Moore, Kevin L; Al-Ubaidi, Muayyad R

2010-11-01

To investigate the role(s) of protein-tyrosine sulfation in the retina, we examined retinal function and structure in mice lacking tyrosylprotein sulfotransferases (TPST) 1 and 2. Tpst double knockout (DKO; Tpst1(-/-) /Tpst2 (-/-) ) retinas had drastically reduced electroretinographic responses, although their photoreceptors exhibited normal responses in single cell recordings. These retinas appeared normal histologically; however, the rod photoreceptors had ultrastructurally abnormal outer segments, with membrane evulsions into the extracellular space, irregular disc membrane spacing and expanded intradiscal space. Photoreceptor synaptic terminals were disorganized in Tpst DKO retinas, but established ultrastructurally normal synapses, as did bipolar and amacrine cells; however, the morphology and organization of neuronal processes in the inner retina were abnormal. These results indicate that protein-tyrosine sulfation is essential for proper outer segment morphogenesis and synaptic function, but is not critical for overall retinal structure or synapse formation, and may serve broader functions in neuronal development and maintenance. © 2010 The Authors. European Journal of Neuroscience © 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Single-Organ Gallbladder Vasculitis

Science.gov (United States)

Hernández-Rodríguez, José; Tan, Carmela D.; Rodríguez, E. René; Hoffman, Gary S.

2014-01-01

Abstract Systemic vasculitis (SV) involving abdominal structures usually has a poor prognosis. Gallbladder vasculitis (GV) has been reported as part of SV (GB-SV) and focal single-organ vasculitis (GB-SOV). We analyzed clinical and histologic characteristics of patients with GV to identify features that differentiate GB-SOV from the systemic forms of GV. To identify affected patients with GV we used pathology databases from our institution and an English-language PubMed search. Clinical manifestations, laboratory and histologic features, treatment administered, and outcomes were recorded. Patients were divided in 2 groups, GB-SOV and GB-SV. As in previous studies of single-organ vasculitis, GB-SOV was only considered to be a sustainable diagnosis if disease beyond the gallbladder was not apparent after a follow-up period of at least 6 months. Sixty-one well-characterized patients with GV were included (6 from our institution). There was no significant sex bias (32 female patients, 29 male). Median age was 52 years (range, 18–94 yr). GB-SOV was found in 20 (33%) and GB-SV in 41 (67%) patients. No differences were observed in age, sex frequency, or duration of gallbladder symptoms between groups. Past episodes of recurrent right-upper quadrant or abdominal pain and lithiasic cholecystitis were more frequent in GB-SOV patients, whereas acalculous cholecystitis occurred more often in GB-SV. In GB-SV, gallbladder-related symptoms occurred more often concomitantly with or after the systemic features, but they sometimes appeared before SV was fully developed (13.5%). Constitutional and musculoskeletal symptoms were reported only in GB-SV patients. Compared to GB-SOV, GB-SV patients presented more often with fever (62.5% vs 20%; p = 0.003) and exhibited higher erythrocyte sedimentation rate levels (80 ± 28 vs 37 ± 25 mm/h, respectively; p = 0.006). All GB-SV patients required glucocorticoids and 50% of them also received cytotoxic agents. Mortality in

Classification of semiurban landscapes from very high-resolution satellite images using a regionalized multiscale segmentation approach

Science.gov (United States)

Kavzoglu, Taskin; Erdemir, Merve Yildiz; Tonbul, Hasan

2017-07-01

In object-based image analysis, obtaining representative image objects is an important prerequisite for a successful image classification. The major threat is the issue of scale selection due to the complex spatial structure of landscapes portrayed as an image. This study proposes a two-stage approach to conduct regionalized multiscale segmentation. In the first stage, an initial high-level segmentation is applied through a "broadscale," and a set of image objects characterizing natural borders of the landscape features are extracted. Contiguous objects are then merged to create regions by considering their normalized difference vegetation index resemblance. In the second stage, optimal scale values are estimated for the extracted regions, and multiresolution segmentation is applied with these settings. Two satellite images with different spatial and spectral resolutions were utilized to test the effectiveness of the proposed approach and its transferability to different geographical sites. Results were compared to those of image-based single-scale segmentation and it was found that the proposed approach outperformed the single-scale segmentations. Using the proposed methodology, significant improvement in terms of segmentation quality and classification accuracy (up to 5%) was achieved. In addition, the highest classification accuracies were produced using fine-scale values.

Molecular species identification of Central European ground beetles (Coleoptera: Carabidae using nuclear rDNA expansion segments and DNA barcodes

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Raupach Michael J

2010-09-01

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

Molecular species identification of Central European ground beetles (Coleoptera: Carabidae) using nuclear rDNA expansion segments and DNA barcodes.

Science.gov (United States)

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

2010-09-13

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

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

Multiscale CNNs for Brain Tumor Segmentation and Diagnosis.

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Zhao, Liya; Jia, Kebin

2016-01-01

Early brain tumor detection and diagnosis are critical to clinics. Thus segmentation of focused tumor area needs to be accurate, efficient, and robust. In this paper, we propose an automatic brain tumor segmentation method based on Convolutional Neural Networks (CNNs). Traditional CNNs focus only on local features and ignore global region features, which are both important for pixel classification and recognition. Besides, brain tumor can appear in any place of the brain and be any size and shape in patients. We design a three-stream framework named as multiscale CNNs which could automatically detect the optimum top-three scales of the image sizes and combine information from different scales of the regions around that pixel. Datasets provided by Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized by MICCAI 2013 are utilized for both training and testing. The designed multiscale CNNs framework also combines multimodal features from T1, T1-enhanced, T2, and FLAIR MRI images. By comparison with traditional CNNs and the best two methods in BRATS 2012 and 2013, our framework shows advances in brain tumor segmentation accuracy and robustness.

Analysis of organic carbon and moisture in Hanford single-shell tank waste

Energy Technology Data Exchange (ETDEWEB)

Toth, J.J.; Heasler, P.G.; Lerchen, M.E.; Hill, J.G.; Whitney, P.D.

1995-05-01

This report documents a revised analysis performed by Pacific Northwest Laboratory involving the organic carbon laboratory measurement data for Hanford single-shell tanks (SSTs) obtained from a review of the laboratory analytical data. This activity has as its objective to provide a best-estimate, including confidence levels, of total organic carbon (TOC) and moisture in each of the 149 SSTs at Hanford. The TOC and moisture information presented in this report is useful as part of the criteria to identify SSTs for additional measurements, or monitoring for the Organic Safety Program. In April 1994, an initial study of the organic carbon in Hanford single-shell tanks was completed at PNL. That study reflected the estimates of TOC based on tank characterizations datasets that were available at the time. Also in that study, estimation of dry basis TOC was based on generalized assumptions pertaining to the moisture of the tank wastes. The new information pertaining to tank moisture and TOC data that has become available from the current study influences the best estimates of TOC in each of the SSTs. This investigation of tank TOC and moisture has resulted in improved estimates based on waste phase: saltcake, sludge, or liquid. This report details the assumptions and methodologies used to develop the estimates of TOC and moisture in each of the 149 SSTs at Hanford.

Analysis of organic carbon and moisture in Hanford single-shell tank waste

International Nuclear Information System (INIS)

Toth, J.J.; Heasler, P.G.; Lerchen, M.E.; Hill, J.G.; Whitney, P.D.

1995-05-01

This report documents a revised analysis performed by Pacific Northwest Laboratory involving the organic carbon laboratory measurement data for Hanford single-shell tanks (SSTs) obtained from a review of the laboratory analytical data. This activity has as its objective to provide a best-estimate, including confidence levels, of total organic carbon (TOC) and moisture in each of the 149 SSTs at Hanford. The TOC and moisture information presented in this report is useful as part of the criteria to identify SSTs for additional measurements, or monitoring for the Organic Safety Program. In April 1994, an initial study of the organic carbon in Hanford single-shell tanks was completed at PNL. That study reflected the estimates of TOC based on tank characterizations datasets that were available at the time. Also in that study, estimation of dry basis TOC was based on generalized assumptions pertaining to the moisture of the tank wastes. The new information pertaining to tank moisture and TOC data that has become available from the current study influences the best estimates of TOC in each of the SSTs. This investigation of tank TOC and moisture has resulted in improved estimates based on waste phase: saltcake, sludge, or liquid. This report details the assumptions and methodologies used to develop the estimates of TOC and moisture in each of the 149 SSTs at Hanford

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.

Towards Single-Step Biofabrication of Organs on a Chip via 3D Printing.

Science.gov (United States)

Knowlton, Stephanie; Yenilmez, Bekir; Tasoglu, Savas

2016-09-01

Organ-on-a-chip engineering employs microfabrication of living tissues within microscale fluid channels to create constructs that closely mimic human organs. With the advent of 3D printing, we predict that single-step fabrication of these devices will enable rapid design and cost-effective iterations in the development stage, facilitating rapid innovation in this field. Copyright © 2016 Elsevier Ltd. All rights reserved.

Solution coating of large-area organic semiconductor thin films with aligned single-crystalline domains

KAUST Repository

Diao, Ying

2013-06-02

Solution coating of organic semiconductors offers great potential for achieving low-cost manufacturing of large-area and flexible electronics. However, the rapid coating speed needed for industrial-scale production poses challenges to the control of thin-film morphology. Here, we report an approach - termed fluid-enhanced crystal engineering (FLUENCE) - that allows for a high degree of morphological control of solution-printed thin films. We designed a micropillar-patterned printing blade to induce recirculation in the ink for enhancing crystal growth, and engineered the curvature of the ink meniscus to control crystal nucleation. Using FLUENCE, we demonstrate the fast coating and patterning of millimetre-wide, centimetre-long, highly aligned single-crystalline organic semiconductor thin films. In particular, we fabricated thin films of 6,13-bis(triisopropylsilylethynyl) pentacene having non-equilibrium single-crystalline domains and an unprecedented average and maximum mobilities of 8.1±1.2 cm2 V-1 s -1 and 11 cm2 V-1 s-1. FLUENCE of organic semiconductors with non-equilibrium single-crystalline domains may find use in the fabrication of high-performance, large-area printed electronics. © 2013 Macmillan Publishers Limited. All rights reserved.

Rib fractures and their association With solid organ injury: higher rib fractures have greater significance for solid organ injury screening.

Science.gov (United States)

Rostas, Jack W; Lively, Timothy B; Brevard, Sidney B; Simmons, Jon D; Frotan, Mohammad A; Gonzalez, Richard P

2017-04-01

The purpose of this study was to identify patients with rib injuries who were at risk for solid organ injury. A retrospective chart review was performed of all blunt trauma patients with rib fractures during the period from July 2007 to July 2012. Data were analyzed for association of rib fractures and solid organ injury. In all, 1,103 rib fracture patients were identified; 142 patients had liver injuries with 109 (77%) associated right rib fractures. Right-sided rib fractures with highest sensitivity for liver injury were middle rib segment (5 to 8) and lower segment (9 to 12) with liver injury sensitivities of 68% and 43%, respectively (P rib fractures. Left middle segment rib fractures and lower segment rib fractures had sensitivities of 80% and 63% for splenic injury, respectively (P Rib fractures higher in the thoracic cage have significant association with solid organ injury. Using rib fractures from middle plus lower segments as indication for abdominal screening will significantly improve rib fracture sensitivity for identification of solid organ injury. Copyright © 2016 Elsevier Inc. All rights reserved.

Electrocardiogram ST-Segment Morphology Delineation Method Using Orthogonal Transformations.

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Miha Amon

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

A single model procedure for tank calibration function estimation

International Nuclear Information System (INIS)

York, J.C.; Liebetrau, A.M.

1995-01-01

Reliable tank calibrations are a vital component of any measurement control and accountability program for bulk materials in a nuclear reprocessing facility. Tank volume calibration functions used in nuclear materials safeguards and accountability programs are typically constructed from several segments, each of which is estimated independently. Ideally, the segments correspond to structural features in the tank. In this paper the authors use an extension of the Thomas-Liebetrau model to estimate the entire calibration function in a single step. This procedure automatically takes significant run-to-run differences into account and yields an estimate of the entire calibration function in one operation. As with other procedures, the first step is to define suitable calibration segments. Next, a polynomial of low degree is specified for each segment. In contrast with the conventional practice of constructing a separate model for each segment, this information is used to set up the design matrix for a single model that encompasses all of the calibration data. Estimation of the model parameters is then done using conventional statistical methods. The method described here has several advantages over traditional methods. First, modeled run-to-run differences can be taken into account automatically at the estimation step. Second, no interpolation is required between successive segments. Third, variance estimates are based on all the data, rather than that from a single segment, with the result that discontinuities in confidence intervals at segment boundaries are eliminated. Fourth, the restrictive assumption of the Thomas-Liebetrau method, that the measured volumes be the same for all runs, is not required. Finally, the proposed methods are readily implemented using standard statistical procedures and widely-used software packages

Improving cerebellar segmentation with statistical fusion

Science.gov (United States)

Plassard, Andrew J.; Yang, Zhen; Prince, Jerry L.; Claassen, Daniel O.; Landman, Bennett A.

2016-03-01

The cerebellum is a somatotopically organized central component of the central nervous system well known to be involved with motor coordination and increasingly recognized roles in cognition and planning. Recent work in multiatlas labeling has created methods that offer the potential for fully automated 3-D parcellation of the cerebellar lobules and vermis (which are organizationally equivalent to cortical gray matter areas). This work explores the trade offs of using different statistical fusion techniques and post hoc optimizations in two datasets with distinct imaging protocols. We offer a novel fusion technique by extending the ideas of the Selective and Iterative Method for Performance Level Estimation (SIMPLE) to a patch-based performance model. We demonstrate the effectiveness of our algorithm, Non- Local SIMPLE, for segmentation of a mixed population of healthy subjects and patients with severe cerebellar anatomy. Under the first imaging protocol, we show that Non-Local SIMPLE outperforms previous gold-standard segmentation techniques. In the second imaging protocol, we show that Non-Local SIMPLE outperforms previous gold standard techniques but is outperformed by a non-locally weighted vote with the deeper population of atlases available. This work advances the state of the art in open source cerebellar segmentation algorithms and offers the opportunity for routinely including cerebellar segmentation in magnetic resonance imaging studies that acquire whole brain T1-weighted volumes with approximately 1 mm isotropic resolution.

Power ramp tests of high burnup BWR segment rods

International Nuclear Information System (INIS)

Hayashi, H.; Etoh, Y.; Tsukuda, Y.; Shimada, S.; Sakurai, H.

2002-01-01

Lead use assemblies (LUAs) of high burnup 8x8 fuel design for Japanese BWRs were irradiated up to 5 cycles in Fukushima Daini Nuclear Power Station No. 2 Unit. Segment rods were installed in LUAs and used for power ramp tests in Japanese Material Test Reactor (JMTR). Post irradiation examinations (PIEs) of segment rods were carried out at Nippon Nuclear Fuel Development Co., Ltd. before and after ramp tests. Maximum linear heat rates of LUAs were kept above 300 W/cm in the first cycle, above 250 W/cm in the second and third cycles and decreased to 200 W/cm in the fourth cycle and 80 W/cm in the fifth cycle. The integrity of high burnup 8x8 fuel was confirmed up to the bundle burnup of 48 GWd/t after 5 cycles of irradiation. Systematic and high quality data were collected through detailed PIEs. The main results are as follows. The oxide on the outer surface of cladding tubes was uniform and its thickness was less than 20 micro-meter after 5 cycles of irradiation and was almost independent of burnup. Hydrogen contents in cladding tubes were less than 150 ppm after 5 cycles of irradiation, although hydrogen contents increased during the fourth and fifth irradiation cycles. Mechanical properties of cladding tubes were on the extrapolated line of previous data up to 5 cycles of irradiation. Fission gas release rates were in the low level (mainly less than 6%) up to 5 cycles of irradiation due to the design to decrease pellet temperature. Pellet-cladding bonding layers were observed after the third cycle and almost full bonding was observed after the fifth cycle. Pellet volume increased with burnup in proportion to solid swelling rate up to the forth cycle. After the fifth cycle, slightly higher pellet swelling was confirmed. Power ramp tests were carried out and satisfactory performance of Zr-lined cladding tube was confirmed up to 60 GWd/t (segment average burnup). One segment rod irradiated for 3 cycles failed by a single step ramp test at terminal ramp power of 614 W

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

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Hans Supèr

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

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

Science.gov (United States)

Supèr, Hans; Romeo, August; Keil, Matthias

2010-05-19

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

Robust Object Segmentation Using a Multi-Layer Laser Scanner

Science.gov (United States)

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

2014-01-01

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

GeoSegmenter: A statistically learned Chinese word segmenter for the geoscience domain

Science.gov (United States)

Huang, Lan; Du, Youfu; Chen, Gongyang

2015-03-01

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

Adaptive geodesic transform for segmentation of vertebrae on CT images

Science.gov (United States)

Gaonkar, Bilwaj; Shu, Liao; Hermosillo, Gerardo; Zhan, Yiqiang

2014-03-01

Vertebral segmentation is a critical first step in any quantitative evaluation of vertebral pathology using CT images. This is especially challenging because bone marrow tissue has the same intensity profile as the muscle surrounding the bone. Thus simple methods such as thresholding or adaptive k-means fail to accurately segment vertebrae. While several other algorithms such as level sets may be used for segmentation any algorithm that is clinically deployable has to work in under a few seconds. To address these dual challenges we present here, a new algorithm based on the geodesic distance transform that is capable of segmenting the spinal vertebrae in under one second. To achieve this we extend the theory of the geodesic distance transforms proposed in1 to incorporate high level anatomical knowledge through adaptive weighting of image gradients. Such knowledge may be provided by the user directly or may be automatically generated by another algorithm. We incorporate information 'learnt' using a previously published machine learning algorithm2 to segment the L1 to L5 vertebrae. While we present a particular application here, the adaptive geodesic transform is a generic concept which can be applied to segmentation of other organs as well.

Characterizing and reaching high-risk drinkers using audience segmentation.

Science.gov (United States)

Moss, Howard B; Kirby, Susan D; Donodeo, Fred

2009-08-01

-savvy singles and couples living in fashionable neighborhoods on the urban fringe." Almost 65% of Cyber Millenials households are found in the Pacific and Middle Atlantic regions of the United States. Additional consumer behaviors of the Cyber Millenials and other segments are also described. Audience segmentation can assist in identifying and describing target audience segments, as well as identifying places where segments congregate on- or offline. This information can be helpful for recruiting subjects for alcohol prevention research as well as planning health promotion campaigns. Through commercial data about high-risk drinkers as "consumers," planners can develop interventions that have heightened salience in terms of opportunities, perceptions, and motivations, and have better media channel identification.

Segmental hair mercury evaluation of a single family along the Upper Madeira Basin, Brazilian Amazon

Directory of Open Access Journals (Sweden)

Boischio Ana Amélia Peixoto

2000-01-01

Full Text Available Mercury pollution (MeHg up the aquatic food chains in the Amazonian ecosystems has been a major concern in environmental health. Riverside people (ribeirinhos along the Upper Madeira river are heavy fish eaters. Hair is the best biomarker for MeHg exposure. By assuming a constant hair growth rate, it is possible to evaluate a temporal profile of Hg exposure over the recent defined past. In this paper we present the segmental total hair Hg concentrations from a single family from which some of the 10 persons investigated had high hair Hg concentrations (peak of 339 ppm. We also presented the hair MeHg content from 4 out of the 10 family members investigated. There was a wide variation in total hair Hg concentrations (8 to 339 ppm among these individuals, who were mostly sharing their meals; there was also a wide variation in total Hg concentrations in the same individual over time (136 to 274 ppm. Hg speciation showed a mean and standard deviation in the MeHg content of 62% and 6%, respectively. The wide variation in total hair Hg concentration strongly indicated that it is possible to mitigate critical Hg exposure levels by conducting a fish advisory.

Fetal brain volumetry through MRI volumetric reconstruction and segmentation

Science.gov (United States)

Estroff, Judy A.; Barnewolt, Carol E.; Connolly, Susan A.; Warfield, Simon K.

2013-01-01

Purpose Fetal MRI volumetry is a useful technique but it is limited by a dependency upon motion-free scans, tedious manual segmentation, and spatial inaccuracy due to thick-slice scans. An image processing pipeline that addresses these limitations was developed and tested. Materials and methods The principal sequences acquired in fetal MRI clinical practice are multiple orthogonal single-shot fast spin echo scans. State-of-the-art image processing techniques were used for inter-slice motion correction and super-resolution reconstruction of high-resolution volumetric images from these scans. The reconstructed volume images were processed with intensity non-uniformity correction and the fetal brain extracted by using supervised automated segmentation. Results Reconstruction, segmentation and volumetry of the fetal brains for a cohort of twenty-five clinically acquired fetal MRI scans was done. Performance metrics for volume reconstruction, segmentation and volumetry were determined by comparing to manual tracings in five randomly chosen cases. Finally, analysis of the fetal brain and parenchymal volumes was performed based on the gestational age of the fetuses. Conclusion The image processing pipeline developed in this study enables volume rendering and accurate fetal brain volumetry by addressing the limitations of current volumetry techniques, which include dependency on motion-free scans, manual segmentation, and inaccurate thick-slice interpolation. PMID:20625848

Conflation of Short Identity-by-Descent Segments Bias Their Inferred Length Distribution

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Charleston W. K. Chiang

2016-05-01

Full Text Available Identity-by-descent (IBD is a fundamental concept in genetics with many applications. In a common definition, two haplotypes are said to share an IBD segment if that segment is inherited from a recent shared common ancestor without intervening recombination. Segments several cM long can be efficiently detected by a number of algorithms using high-density SNP array data from a population sample, and there are currently efforts to detect shorter segments from sequencing. Here, we study a problem of identifiability: because existing approaches detect IBD based on contiguous segments of identity-by-state, inferred long segments of IBD may arise from the conflation of smaller, nearby IBD segments. We quantified this effect using coalescent simulations, finding that significant proportions of inferred segments 1–2 cM long are results of conflations of two or more shorter segments, each at least 0.2 cM or longer, under demographic scenarios typical for modern humans for all programs tested. The impact of such conflation is much smaller for longer (> 2 cM segments. This biases the inferred IBD segment length distribution, and so can affect downstream inferences that depend on the assumption that each segment of IBD derives from a single common ancestor. As an example, we present and analyze an estimator of the de novo mutation rate using IBD segments, and demonstrate that unmodeled conflation leads to underestimates of the ages of the common ancestors on these segments, and hence a significant overestimate of the mutation rate. Understanding the conflation effect in detail will make its correction in future methods more tractable.

Single Versus Multiple Solid Organ Injuries Following Blunt Abdominal Trauma.

Science.gov (United States)

El-Menyar, Ayman; Abdelrahman, Husham; Al-Hassani, Ammar; Peralta, Ruben; AbdelAziz, Hiba; Latifi, Rifat; Al-Thani, Hassan

2017-11-01

We aimed to describe the pattern of solid organ injuries (SOIs) and analyze the characteristics, management and outcomes based on the multiplicity of SOIs. A retrospective study in a Level 1 trauma center was conducted and included patients admitted with blunt abdominal trauma between 2011 and 2014. Data were analyzed and compared for patients with single versus multiple SOIs. A total of 504 patients with SOIs were identified with a mean age of 28 ± 13 years. The most frequently injured organ was liver (45%) followed by spleen (30%) and kidney (18%). One-fifth of patients had multiple SOIs, of that 87% had two injured organs. Patients with multiple SOIs had higher frequency of head injury and injury severity scores (p hepatic injuries (13%) than the other SOIs. SOIs represent one-tenth of trauma admissions in Qatar. Although liver was the most frequently injured organ, the rate of mortality was higher in pancreatic injury. Patients with multiple SOIs had higher morbidity which required frequent operative management. Further prospective studies are needed to develop management algorithm based on the multiplicity of SOIs.

On grouping individual wire segments into equivalent wires or chains, and introduction of multiple domain basis functions

CSIR Research Space (South Africa)

Lysko, AA

2009-06-01

Full Text Available The paper introduces a method to cover several wire segments with a single basis function, describes related practical algorithms, and gives some results. The process involves three steps: identifying chains of wire segments, splitting the chains...

Double segmental tibial fractures - an unusual fracture pattern

Directory of Open Access Journals (Sweden)

Bali Kamal

2012-02-01

Full Text Available 【Abstract】A case of a 50-year-old pedestrian who was hit by a bike and suffered fractures of both bones of his right leg was presented. Complete clinical and radiographic assessment showed double segmental fractures of the tibia and multisegmental fractures of the fibula. Review of the literature revealed that this fracture pattern was unique and only a single case was reported so far. Moreover, we discussed the possible mechanisms which can lead to such an injury. We also discussed the management of segmental tibial fracture and the difficulties encountered with them. This case was managed by modern osteosynthesis tech- nique with a pleasing outcome. Key words: Fracture, bone; Tibia; Fibula; Nails

Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks.

Science.gov (United States)

Men, Kuo; Dai, Jianrong; Li, Yexiong

2017-12-01

Delineation of the clinical target volume (CTV) and organs at risk (OARs) is very important for radiotherapy but is time-consuming and prone to inter-observer variation. Here, we proposed a novel deep dilated convolutional neural network (DDCNN)-based method for fast and consistent auto-segmentation of these structures. Our DDCNN method was an end-to-end architecture enabling fast training and testing. Specifically, it employed a novel multiple-scale convolutional architecture to extract multiple-scale context features in the early layers, which contain the original information on fine texture and boundaries and which are very useful for accurate auto-segmentation. In addition, it enlarged the receptive fields of dilated convolutions at the end of networks to capture complementary context features. Then, it replaced the fully connected layers with fully convolutional layers to achieve pixel-wise segmentation. We used data from 278 patients with rectal cancer for evaluation. The CTV and OARs were delineated and validated by senior radiation oncologists in the planning computed tomography (CT) images. A total of 218 patients chosen randomly were used for training, and the remaining 60 for validation. The Dice similarity coefficient (DSC) was used to measure segmentation accuracy. Performance was evaluated on segmentation of the CTV and OARs. In addition, the performance of DDCNN was compared with that of U-Net. The proposed DDCNN method outperformed the U-Net for all segmentations, and the average DSC value of DDCNN was 3.8% higher than that of U-Net. Mean DSC values of DDCNN were 87.7% for the CTV, 93.4% for the bladder, 92.1% for the left femoral head, 92.3% for the right femoral head, 65.3% for the intestine, and 61.8% for the colon. The test time was 45 s per patient for segmentation of all the CTV, bladder, left and right femoral heads, colon, and intestine. We also assessed our approaches and results with those in the literature: our system showed superior

Exploiting Interslice Correlation for MRI Prostate Image Segmentation, from Recursive Neural Networks Aspect

Directory of Open Access Journals (Sweden)

Qikui Zhu

2018-01-01

Full Text Available Segmentation of the prostate from Magnetic Resonance Imaging (MRI plays an important role in prostate cancer diagnosis. However, the lack of clear boundary and significant variation of prostate shapes and appearances make the automatic segmentation very challenging. In the past several years, approaches based on deep learning technology have made significant progress on prostate segmentation. However, those approaches mainly paid attention to features and contexts within each single slice of a 3D volume. As a result, this kind of approaches faces many difficulties when segmenting the base and apex of the prostate due to the limited slice boundary information. To tackle this problem, in this paper, we propose a deep neural network with bidirectional convolutional recurrent layers for MRI prostate image segmentation. In addition to utilizing the intraslice contexts and features, the proposed model also treats prostate slices as a data sequence and utilizes the interslice contexts to assist segmentation. The experimental results show that the proposed approach achieved significant segmentation improvement compared to other reported methods.

A method of segment weight optimization for intensity modulated radiation therapy

International Nuclear Information System (INIS)

Pei Xi; Cao Ruifen; Jing Jia; Cheng Mengyun; Zheng Huaqing; Li Jia; Huang Shanqing; Li Gui; Song Gang; Wang Weihua; Wu Yican; FDS Team

2011-01-01

The error caused by leaf sequencing often leads to planning of Intensity-Modulated Radiation Therapy (IMRT) arrange system couldn't meet clinical demand. The optimization approach in this paper can reduce this error and improve efficiency of plan-making effectively. Conjugate Gradient algorithm was used to optimize segment weight and readjust segment shape, which could minimize the error anterior-posterior leaf sequencing eventually. Frequent clinical cases were tasted by precise radiotherapy system, and then compared Dose-Volume histogram between target area and organ at risk as well as isodose line in computed tomography (CT) film, we found that the effect was improved significantly after optimizing segment weight. Segment weight optimizing approach based on Conjugate Gradient method can make treatment planning meet clinical request more efficiently, so that has extensive application perspective. (authors)

Fully automatic algorithm for segmenting full human diaphragm in non-contrast CT Images

Science.gov (United States)

Karami, Elham; Gaede, Stewart; Lee, Ting-Yim; Samani, Abbas

2015-03-01

The diaphragm is a sheet of muscle which separates the thorax from the abdomen and it acts as the most important muscle of the respiratory system. As such, an accurate segmentation of the diaphragm, not only provides key information for functional analysis of the respiratory system, but also can be used for locating other abdominal organs such as the liver. However, diaphragm segmentation is extremely challenging in non-contrast CT images due to the diaphragm's similar appearance to other abdominal organs. In this paper, we present a fully automatic algorithm for diaphragm segmentation in non-contrast CT images. The method is mainly based on a priori knowledge about the human diaphragm anatomy. The diaphragm domes are in contact with the lungs and the heart while its circumference runs along the lumbar vertebrae of the spine as well as the inferior border of the ribs and sternum. As such, the diaphragm can be delineated by segmentation of these organs followed by connecting relevant parts of their outline properly. More specifically, the bottom surface of the lungs and heart, the spine borders and the ribs are delineated, leading to a set of scattered points which represent the diaphragm's geometry. Next, a B-spline filter is used to find the smoothest surface which pass through these points. This algorithm was tested on a noncontrast CT image of a lung cancer patient. The results indicate that there is an average Hausdorff distance of 2.96 mm between the automatic and manually segmented diaphragms which implies a favourable accuracy.

Statistical region based active contour using a fractional entropy descriptor: Application to nuclei cell segmentation in confocal \\ud microscopy images

OpenAIRE

Histace, A; Meziou, B J; Matuszewski, Bogdan; Precioso, F; Murphy, M F; Carreiras, F

2013-01-01

We propose an unsupervised statistical region based active contour approach integrating an original fractional entropy measure for image segmentation with a particular application to single channel actin tagged fluorescence confocal microscopy image segmentation. Following description of statistical based active contour segmentation and the mathematical definition of the proposed fractional entropy descriptor, we demonstrate comparative segmentation results between the proposed approach and s...

Atlas-based liver segmentation and hepatic fat-fraction assessment for clinical trials.

Science.gov (United States)

Yan, Zhennan; Zhang, Shaoting; Tan, Chaowei; Qin, Hongxing; Belaroussi, Boubakeur; Yu, Hui Jing; Miller, Colin; Metaxas, Dimitris N

2015-04-01

Automated assessment of hepatic fat-fraction is clinically important. A robust and precise segmentation would enable accurate, objective and consistent measurement of hepatic fat-fraction for disease quantification, therapy monitoring and drug development. However, segmenting the liver in clinical trials is a challenging task due to the variability of liver anatomy as well as the diverse sources the images were acquired from. In this paper, we propose an automated and robust framework for liver segmentation and assessment. It uses single statistical atlas registration to initialize a robust deformable model to obtain fine segmentation. Fat-fraction map is computed by using chemical shift based method in the delineated region of liver. This proposed method is validated on 14 abdominal magnetic resonance (MR) volumetric scans. The qualitative and quantitative comparisons show that our proposed method can achieve better segmentation accuracy with less variance comparing with two other atlas-based methods. Experimental results demonstrate the promises of our assessment framework. Copyright © 2014 Elsevier Ltd. All rights reserved.

Real-Time Visualization of Active Species in a Single-Site Metal–Organic Framework Photocatalyst

Energy Technology Data Exchange (ETDEWEB)

Yang, Sizhuo [Department of Chemistry, Marquette University, Milwaukee, Wisconsin 53201, United States; Pattengale, Brian [Department of Chemistry, Marquette University, Milwaukee, Wisconsin 53201, United States; Lee, Sungsik [X-ray Science Division, Argonne National Laboratory, Argonne, Illinois 60349, United States; Huang, Jier [Department of Chemistry, Marquette University, Milwaukee, Wisconsin 53201, United States

2018-02-06

In this work, we report a new single-site photocatalyst (Co-Ru-UIO- 67(bpy)) based on a metal-organic framework platform with incorporated molecular photosensitizer and catalyst. We show that this catalyst not only demonstrates exceptional activity for light-driven H2 production but also can be recycled without loss of activity. Using the combination of optical transient absorption spectroscopy and in situ X-ray absorption spectroscopy, we not only captured the key CoI intermediate species formed after ultrafast charge transfer from the incorporated photosensitizer but also identified the rate-limiting step in the catalytic cycle, providing insight into the catalysis mechanism of these single-site metal-organic framework photocatalysts.

[Definition of nodal volumes in breast cancer treatment and segmentation guidelines].

Science.gov (United States)

Kirova, Y M; Castro Pena, P; Dendale, R; Campana, F; Bollet, M A; Fournier-Bidoz, N; Fourquet, A

2009-06-01

To assist in the determination of breast and nodal volumes in the setting of radiotherapy for breast cancer and establish segmentation guidelines. Materials and methods. Contrast metarial enhanced CT examinations were obtained in the treatment position in 25 patients to clearly define the target volumes. The clinical target volume (CTV) including the breast, internal mammary nodes, supraclavicular and subclavicular regions and axxilary region were segmented along with the brachial plexus and interpectoral nodes. The following critical organs were also segmented: heart, lungs, contralateral breast, thyroid, esophagus and humeral head. A correlation between clinical and imaging findings and meeting between radiation oncologists and breast specialists resulted in a better definition of irradiation volumes for breast and nodes with establishement of segmentation guidelines and creation of an anatomical atlas. A practical approach, based on anatomical criteria, is proposed to assist in the segmentation of breast and node volumes in the setting of breast cancer treatment along with a definition of irradiation volumes.

Feasibility of automated 3-dimensional magnetic resonance imaging pancreas segmentation

Directory of Open Access Journals (Sweden)

Shuiping Gou, PhD

2016-07-01

Conclusions: Our study demonstrated potential feasibility of automated segmentation of the pancreas on MRI scans with minimal human supervision at the beginning of imaging acquisition. The achieved accuracy is promising for organ localization.

Real-time observation of conformational switching in single conjugated polymer chains.

Science.gov (United States)

Tenopala-Carmona, Francisco; Fronk, Stephanie; Bazan, Guillermo C; Samuel, Ifor D W; Penedo, J Carlos

2018-02-01

Conjugated polymers (CPs) are an important class of organic semiconductors that combine novel optoelectronic properties with simple processing from organic solvents. It is important to study CP conformation in solution to understand the physics of these materials and because it affects the properties of solution-processed films. Single-molecule techniques are unique in their ability to extract information on a chain-to-chain basis; however, in the context of CPs, technical challenges have limited their general application to host matrices or semiliquid environments that constrain the conformational dynamics of the polymer. We introduce a conceptually different methodology that enables measurements in organic solvents using the single-end anchoring of polymer chains to avoid diffusion while preserving polymer flexibility. We explore the effect of organic solvents and show that, in addition to chain-to-chain conformational heterogeneity, collapsed and extended polymer segments can coexist within the same chain. The technique enables real-time solvent-exchange measurements, which show that anchored CP chains respond to sudden changes in solvent conditions on a subsecond time scale. Our results give an unprecedented glimpse into the mechanism of solvent-induced reorganization of CPs and can be expected to lead to a new range of techniques to investigate and conformationally manipulate CPs.

Large-area aligned growth of single-crystalline organic nanowire arrays for high-performance photodetectors

International Nuclear Information System (INIS)

Wu Yiming; Zhang Xiujuan; Pan Huanhuan; Zhang Xiwei; Zhang Yuping; Zhang Xiaozhen; Jie Jiansheng

2013-01-01

Due to their extraordinary properties, single-crystalline organic nanowires (NWs) are important building blocks for future low-cost and efficient nano-optoelectronic devices. However, it remains a critical challenge to assemble organic NWs rationally in an orientation-, dimensionality- and location-controlled manner. Herein, we demonstrate a feasible method for aligned growth of single-crystalline copper phthalocyanine (CuPc) NW arrays with high density, large-area uniformity and perfect crossed alignment by using Au film as a template. The growth process was investigated in detail. The Au film was found to have a critical function in the aligned growth of NWs, but may only serve as the active site for NW nucleation because of the large surface energy, as well as direct the subsequent aligned growth. The as-prepared NWs were then transferred to construct single NW-based photoconductive devices, which demonstrated excellent photoresponse properties with robust stability and reproducibility; the device showed a high switching ratio of ∼180, a fast response speed of ∼100 ms and could stand continuous operation up to 2 h. Importantly, this strategy can be extended to other organic molecules for their synthesis of NW arrays, revealing great potential for use in the construction of large-scale high-performance functional nano-optoelectronic devices. (paper)

Bladder segmentation in MR images with watershed segmentation and graph cut algorithm

Science.gov (United States)

Blaffert, Thomas; Renisch, Steffen; Schadewaldt, Nicole; Schulz, Heinrich; Wiemker, Rafael

2014-03-01

Prostate and cervix cancer diagnosis and treatment planning that is based on MR images benefit from superior soft tissue contrast compared to CT images. For these images an automatic delineation of the prostate or cervix and the organs at risk such as the bladder is highly desirable. This paper describes a method for bladder segmentation that is based on a watershed transform on high image gradient values and gray value valleys together with the classification of watershed regions into bladder contents and tissue by a graph cut algorithm. The obtained results are superior if compared to a simple region-after-region classification.

Functionalised metal-organic frameworks : A novel approach to stabilising single metal atoms

NARCIS (Netherlands)

Szilagyi, P.A.; Rogers, D. M.; Zaiser, I.; Callini, E; Turner, Stuart; Borgschulte, A; Züttel, A.; Geerlings, J.J.C.; Hirscher, M; Dam, B.

2017-01-01

We have investigated the potential of metal-organic frameworks for immobilising single atoms of transition metals using a model system of Pd supported on NH₂-MIL-101(Cr). Our transmission electron microscopy and in situ Raman spectroscopy results give evidence for the first time that

Investigations on the quality of manual image segmentation in 3D radiotherapy planning

International Nuclear Information System (INIS)

Perelmouter, J.; Tuebingen Univ.; Bohsung, J.; Nuesslin, F.; Becker, G.; Kortmann, R.D.; Bamberg, M.

1998-01-01

In 3D radiotherapy planning image segmentation plays an important role in the definition process of target volume and organs at risk. Here, we present a method to quantify the technical precision of the manual image segmentation process. To validate our method we developed a virtual phantom consisting of several geometrical objects of changing form and contrast, which should be contoured by volunteers using the TOMAS tool for manual segmentation of the Heidelberg VOXELPLAN system. The results of this examination are presented. (orig.) [de

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

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

Multiscale CNNs for Brain Tumor Segmentation and Diagnosis

Directory of Open Access Journals (Sweden)

Liya Zhao

2016-01-01

Full Text Available Early brain tumor detection and diagnosis are critical to clinics. Thus segmentation of focused tumor area needs to be accurate, efficient, and robust. In this paper, we propose an automatic brain tumor segmentation method based on Convolutional Neural Networks (CNNs. Traditional CNNs focus only on local features and ignore global region features, which are both important for pixel classification and recognition. Besides, brain tumor can appear in any place of the brain and be any size and shape in patients. We design a three-stream framework named as multiscale CNNs which could automatically detect the optimum top-three scales of the image sizes and combine information from different scales of the regions around that pixel. Datasets provided by Multimodal Brain Tumor Image Segmentation Benchmark (BRATS organized by MICCAI 2013 are utilized for both training and testing. The designed multiscale CNNs framework also combines multimodal features from T1, T1-enhanced, T2, and FLAIR MRI images. By comparison with traditional CNNs and the best two methods in BRATS 2012 and 2013, our framework shows advances in brain tumor segmentation accuracy and robustness.

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

International Nuclear Information System (INIS)

Li, L; Tan, S; Lu, W

2016-01-01

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

Treatment of ankylosed maxillary central incisors by segmental osteotomy with autogenous bone graft.

Science.gov (United States)

You, Kug-Ho; Min, Yon-Sook; Baik, Hyoung-Seon

2012-04-01

This case report describes the treatment of a 16-year-old girl with ankylosed maxillary central incisors that were noticeably infraoccluded and labially displaced. We performed a segmental osteotomy with an autogenous bone graft in a single-stage surgery to align and level the ankylosed teeth. The dento-osseous segment was successfully repositioned with satisfactory periodontal results. Copyright © 2012 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Discourse segmentation and the management of multiple tasks in single episodes of air traffic controller-pilot spoken radio communication

Directory of Open Access Journals (Sweden)

Paul A. Falzon

2009-06-01

Full Text Available Episodes of VHF radio-mediated pilot-controller spoken communication in which multiple tasks are conducted are engendered in and through the skilful deployment and combination, by the parties to the talk, of multiple orders of discourse segmentation. These orders of segmentation are manifest at the levels of transmission design and sequential organisation. Both of these features are analysed from a Conversation Analytic standpoint in order to track their segment by segment genesis, development and completion. From the analysis it emerges that in addition to the serial type of sequential organisations described by Schegloff (1986, there exists an alternative form of organisation that enables tasks to be managed in a quasi-parallel manner, and which affords controllers and pilots a number of practical advantages in the conduct of their radio-mediated service encounters.Cet article présente des extraits d’échanges oraux entre pilots et contrôleurs du ciel via la radio VHF. On peut y voir comment le déploiement et la combinaison habile de plusieurs ordres de segmentation discursive, engageant les deux coénonciateurs de la conversation, leur permet d’accomplir des tâches multiples. Ces ordres de segmentation se manifestent aux niveaux du plan de la transmission et de l’organisation séquentielle. Ces deux niveaux sont envisagées du point de vue de l’analyse conversationnelle dans le but d’examiner, segment après segment, comment ils se mettent en place, se développent puis prennent fin. Notre étude montre que, outre le type sériel d’organisations séquentielles décrit par Schegloff (1986, il existe une forme alternative d’organisation qui permet de gérer les tâches de manière quasi parallèle, et qui fournit aux contrôleurs aériens ainsi qu’aux pilotes de nombreux avantages pratiques dans la conduite de leurs radio.

Characterizing and Reaching High-Risk Drinkers Using Audience Segmentation

Science.gov (United States)

Moss, Howard B.; Kirby, Susan D.; Donodeo, Fred

2010-01-01

Background Market or audience segmentation is widely used in social marketing efforts to help planners identify segments of a population to target for tailored program interventions. Market-based segments are typically defined by behaviors, attitudes, knowledge, opinions, or lifestyles. They are more helpful to health communication and marketing planning than epidemiologically-defined groups because market-based segments are similar in respect to how they behave or might react to marketing and communication efforts. However, market segmentation has rarely been used in alcohol research. As an illustration of its utility, we employed commercial data that describes the sociodemographic characteristics of high-risk drinkers as an audience segment; where they tend to live, lifestyles, interests, consumer behaviors, alcohol consumption behaviors, other health-related behaviors, and cultural values. Such information can be extremely valuable in targeting and planning public health campaigns, targeted mailings, prevention interventions and research efforts. Methods We describe the results of a segmentation analysis of those individuals who self-report consuming five or more drinks per drinking episode at least twice in the last 30-days. The study used the proprietary PRIZM™ audience segmentation database merged with Center for Disease Control and Prevention's (CDC) Behavioral Risk Factor Surveillance System (BRFSS) database. The top ten of the 66 PRIZM™ audience segments for this risky drinking pattern are described. For five of these segments we provide additional in-depth details about consumer behavior and the estimates of the market areas where these risky drinkers reside. Results The top ten audience segments (PRIZM clusters) most likely to engage in high-risk drinking are described. The cluster with the highest concentration of binge drinking behavior is referred to as the “Cyber Millenials.” This cluster is characterized as “the nation's tech-savvy singles

Organic carbon in Hanford single-shell tank waste

International Nuclear Information System (INIS)

Toth, J.J.; Willingham, C.E.; Heasler, P.G.; Whitney, P.D.

1994-07-01

This report documents an analysis performed by Pacific Northwest Laboratory (PNL) involving the organic carbon laboratory measurement data for Hanford single-shell tanks (SSTS) obtained from a review of the laboratory analytical data. This activity was undertaken at the request of Westinghouse Hanford Company (WHC). The objective of this study is to provide a best estimate, including confidence levels, of total organic carbon (TOC) in each of the 149 SSTs at Hanford. The TOC analyte information presented in this report is useful as part of the criteria to identify SSTs for additional measurements or monitoring for the organic safety program. This report is a precursor to an investigation of TOC and moisture in Hanford SSTS, in order to provide best estimates for each together in one report. Measured laboratory data were obtained for 75 of the 149 SSTS. The data represent a thorough investigation of data from 224 tank characterization datasets, including core-sampling and process laboratory data. Liquid and solid phase TOC values were investigated by examining selected tanks with both reported TOC values in solid and liquid phases. Some relationships were noted, but there was no clustering of data or significance between the solid and liquid phases. A methodology was developed for estimating the distribution and levels of TOC in SSTs using a logarithmic scale and an analysis of variance (ANOVA) technique. The methodology grouped tanks according to waste type using the Sort On Radioactive Waste Type (SORWT) grouping method. The SORWT model categorizes Hanford SSTs into groups of tanks expected to exhibit similar characteristics based on major waste types and processing histories. The methodology makes use of laboratory data for the particular tank and information about the SORWT group of which the tank is a member. Recommendations for a simpler tank grouping strategy based on organic transfer records were made

Charged-particle spectroscopy in organic semiconducting single crystals

Energy Technology Data Exchange (ETDEWEB)

Ciavatti, A.; Basiricò, L.; Fraboni, B. [Department of Physics and Astronomy, University of Bologna, Viale Berti Pichat 6/2, 40127 Bologna (Italy); Sellin, P. J. [Department of Physics, University of Surrey, Guildford, Surrey GU2 7XH (United Kingdom); Fraleoni-Morgera, A. [ELETTRA-Sincrotrone Trieste, Strada Statale 14, Km 163.5, Basovizza, Trieste (Italy); Department of Engineering and Architecture, University of Trieste, V. Valerio 10, 34100 Trieste (Italy); CNR-Nano S3 Institute, Via Campi 213/A, 41125 Modena (Italy)

2016-04-11

The use of organic materials as radiation detectors has grown, due to the easy processability in liquid phase at room temperature and the possibility to cover large areas by means of low cost deposition techniques. Direct charged-particle detectors based on solution-grown Organic Semiconducting Single Crystals (OSSCs) are shown to be capable to detect charged particles in pulse mode, with very good peak discrimination. The direct charged-particle detection in OSSCs has been assessed both in the planar and in the vertical axes, and a digital pulse processing algorithm has been used to perform pulse height spectroscopy and to study the charge collection efficiency as a function of the applied bias voltage. Taking advantage of the charge spectroscopy and the good peak discrimination of pulse height spectra, an Hecht-like behavior of OSSCs radiation detectors is demonstrated. It has been possible to estimate the mobility-lifetime value in organic materials, a fundamental parameter for the characterization of radiation detectors, whose results are equal to μτ{sub coplanar} = (5 .5 ± 0.6 ) × 10{sup −6} cm{sup 2}/V and μτ{sub sandwich} = (1 .9 ± 0.2 ) × 10{sup −6} cm{sup 2}/V, values comparable to those of polycrystalline inorganic detectors. Moreover, alpha particles Time-of-Flight experiments have been carried out to estimate the drift mobility value. The results reported here indicate how charged-particle detectors based on OSSCs possess a great potential as low-cost, large area, solid-state direct detectors operating at room temperature. More interestingly, the good detection efficiency and peak discrimination observed for charged-particle detection in organic materials (hydrogen-rich molecules) are encouraging for their further exploitation in the detection of thermal and high-energy neutrons.

Single-walled carbon nanotubes nanocomposite microacoustic organic vapor sensors

Energy Technology Data Exchange (ETDEWEB)

Penza, M. [ENEA, Materials and New Technologies Unit, SS. 7, Appia, km 714, 72100 Brindisi (Italy)]. E-mail: michele.penza@brindisi.enea.it; Tagliente, M.A. [ENEA, Materials and New Technologies Unit, SS. 7, Appia, km 714, 72100 Brindisi (Italy); Aversa, P. [ENEA, Materials and New Technologies Unit, SS. 7, Appia, km 714, 72100 Brindisi (Italy); Cassano, G. [ENEA, Materials and New Technologies Unit, SS. 7, Appia, km 714, 72100 Brindisi (Italy); Capodieci, L. [ENEA, Materials and New Technologies Unit, SS. 7, Appia, km 714, 72100 Brindisi (Italy)

2006-07-15

We have developed highly sensitive microacoustic vapor sensors based on surface acoustic waves (SAWs) configured as oscillators using a two-port resonator 315, 433 and 915 MHz device. A nanocomposite film of single-walled carbon nanotubes (SWCNTs) embedded in a cadmium arachidate (CdA) amphiphilic organic matrix was prepared by Langmuir-Blodgett technique with a different SWCNTs weight filler content onto SAW transducers as nanosensing interface for vapor detection, at room temperature. The structural properties and surface morphology of the nanocomposite have been examined by X-ray diffraction, transmission and scanning electron microscopy, respectively. The sensing properties of SWCNTs nanocomposite LB films consisting of tangled nanotubules have been also investigated by using Quartz Crystal Microbalance 10 MHz AT-cut quartz resonators. The measured acoustic sensing characteristics indicate that the room-temperature SAW sensitivity to polar and nonpolar tested organic molecules (ethanol, ethylacetate, toluene) of the SWCNTs-in-CdA nanocomposite increases with the filler content of SWCNTs incorporated in the nanocomposite; also the SWCNTs-in-CdA nanocomposite vapor sensitivity results significantly enhanced with respect to traditional organic molecular cavities materials with a linearity in the frequency change response for a given nanocomposite weight composition and a very low sub-ppm limit of detection.

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.

Single Pt Atoms Confined into a Metal-Organic Framework for Efficient Photocatalysis.

Science.gov (United States)

Fang, Xinzuo; Shang, Qichao; Wang, Yu; Jiao, Long; Yao, Tao; Li, Yafei; Zhang, Qun; Luo, Yi; Jiang, Hai-Long

2018-02-01

It is highly desirable yet remains challenging to improve the dispersion and usage of noble metal cocatalysts, beneficial to charge transfer in photocatalysis. Herein, for the first time, single Pt atoms are successfully confined into a metal-organic framework (MOF), in which electrons transfer from the MOF photosensitizer to the Pt acceptor for hydrogen production by water splitting under visible-light irradiation. Remarkably, the single Pt atoms exhibit a superb activity, giving a turnover frequency of 35 h -1 , ≈30 times that of Pt nanoparticles stabilized by the same MOF. Ultrafast transient absorption spectroscopy further unveils that the single Pt atoms confined into the MOF provide highly efficient electron transfer channels and density functional theory calculations indicate that the introduction of single Pt atoms into the MOF improves the hydrogen binding energy, thus greatly boosting the photocatalytic H 2 production activity. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Bend-resistant large mode area fiber with novel segmented cladding

Science.gov (United States)

Ma, Shaoshuo; Ning, Tigang; Pei, Li; Li, Jing; Zheng, Jingjing

2018-01-01

A novel structure of segment cladding fiber (SCF) with characteristics of bend-resistance and large-mode-area (LMA) is proposed. In this new structure, the high refractive index (RI) core is periodically surrounded by high RI fan-segmented claddings. Numerical investigations show that effective single-mode operation of the proposed fiber with mode field area of 700 μm2 can be achieved when the bending radius is 15 cm. Besides, this fiber is insensitive to the bending orientation at the ranging of [-180°, 180°]. The proposed design shows great potential in high power fiber lasers and amplifiers with compact structure.

Self-Aligned Growth of Organic Semiconductor Single Crystals by Electric Field.

Science.gov (United States)

Kotsuki, Kenji; Obata, Seiji; Saiki, Koichiro

2016-01-19

We proposed a novel but facile method for growing organic semiconductor single-crystals via solvent vapor annealing (SVA) under electric field. In the conventional SVA growth process, nuclei of crystals appeared anywhere on the substrate and their crystallographic axes were randomly distributed. We applied electric field during the SVA growth of 2,7-dioctyl[1]benzothieno[3,2-b][1]benzothiophene (C8-BTBT) on the SiO2/Si substrate on which a pair of electrodes had been deposited beforehand. Real-time observation of the SVA process revealed that rodlike single crystals grew with their long axes parallel to the electric field and bridged the prepatterned electrodes. As a result, C8-BTBT crystals automatically formed a field effect transistor (FET) structure and the mobility reached 1.9 cm(2)/(V s). Electric-field-assisted SVA proved a promising method for constructing high-mobility single-crystal FETs at the desired position by a low-cost solution process.

Automated coronal hole identification via multi-thermal intensity segmentation

Science.gov (United States)

Garton, Tadhg M.; Gallagher, Peter T.; Murray, Sophie A.

2018-01-01

Coronal holes (CH) are regions of open magnetic fields that appear as dark areas in the solar corona due to their low density and temperature compared to the surrounding quiet corona. To date, accurate identification and segmentation of CHs has been a difficult task due to their comparable intensity to local quiet Sun regions. Current segmentation methods typically rely on the use of single Extreme Ultra-Violet passband and magnetogram images to extract CH information. Here, the coronal hole identification via multi-thermal emission recognition algorithm (CHIMERA) is described, which analyses multi-thermal images from the atmospheric image assembly (AIA) onboard the solar dynamics observatory (SDO) to segment coronal hole boundaries by their intensity ratio across three passbands (171 Å, 193 Å, and 211 Å). The algorithm allows accurate extraction of CH boundaries and many of their properties, such as area, position, latitudinal and longitudinal width, and magnetic polarity of segmented CHs. From these properties, a clear linear relationship was identified between the duration of geomagnetic storms and coronal hole areas. CHIMERA can therefore form the basis of more accurate forecasting of the start and duration of geomagnetic storms.

Focal Segmental Glomerulosclerosis: A Single Center Experience

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Yavuz Ayar

2016-09-01

Full Text Available Aim: Focal segmental glomerulosclerosis (FSGS is one of the most common glomerulonephritis (GNP worldwide. Despite treatment, it may progress to end-stage renal disease. In the present study, we compared clinical and histopathological data on FSGS with primary and secondary GNP retrospectively. Methods: We retrospectively analyzed data on clinical and laboratory findings, treatment response, and risk factors associated with mortality in patients, who had been diagnosed with FSGS and other GNP via renal biopsy between January 2009 and December 2014. The average follow-up time was 22 (8-76 months. Results: FSGS and primary GNP were more frequently seen in males than in females (55.9% vs. 65.3%, p=0.033. Nephrotic syndrome was more common in patients with FSGS (41.2% and primary GNP (57.7%, while chronic renal disease was more frequent in patients with secondary GNP (35%. In FSGS, the complete remission rate was 54.4%. 63.2% of patients had continued to receive treatment. According to the biopsy findings, interstitial inflammation and fibrosis were observed in 100% and 98.5% of patients with FSGS, respectively (p=0.010 and p<0.001, respectively. Serum albumin level was found to be increased and proteinuria, total cholesterol, triglyceride, and LDL levels to be decreased after treatment (p<0.001. Serum creatinine levels and type of GNP (secondary GNP were detected to be 1.48 and 8.14 fold increased in mortality analysis, respectively. Conclusion: Renal biopsy is the gold standard for the diagnosis of glomerular diseases. Renal function at the time of diagnosis, follow-up and appropriate immunosuppressive therapy have effects on mortality and clinical progress in FSGS as is the case in all GNPs.

Sideband cooling and coherent dynamics in a microchip multi-segmented ion trap

Energy Technology Data Exchange (ETDEWEB)

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

2008-04-15

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

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

Science.gov (United States)

Anderson, Jeffrey R; Barrett, Steven F

2010-01-01

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

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)

Multi-region unstructured volume segmentation using tetrahedron filling

Energy Technology Data Exchange (ETDEWEB)

Willliams, Sean Jamerson [Los Alamos National Laboratory; Dillard, Scott E [Los Alamos National Laboratory; Thoma, Dan J [MDI, INSTITUTES; Hlawitschka, Mario [UC DAVIS; Hamann, Bernd [UC DAVIS

2010-01-01

Segmentation is one of the most common operations in image processing, and while there are several solutions already present in the literature, they each have their own benefits and drawbacks that make them well-suited for some types of data and not for others. We focus on the problem of breaking an image into multiple regions in a single segmentation pass, while supporting both voxel and scattered point data. To solve this problem, we begin with a set of potential boundary points and use a Delaunay triangulation to complete the boundaries. We use heuristic- and interaction-driven Voronoi clustering to find reasonable groupings of tetrahedra. Apart from the computation of the Delaunay triangulation, our algorithm has linear time complexity with respect to the number of tetrahedra.

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

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.

Effective Segmentation of University Alumni: Mining Contribution Data with Finite-Mixture Models

Science.gov (United States)

Durango-Cohen, Elizabeth J.; Balasubramanian, Siva K.

2015-01-01

Having an effective segmentation strategy is key to the viability of any organization. This is particularly true for colleges, universities, and other nonprofit organizations--who have seen sharp declines in private contributions, endowment income, and government grants in the past few years, and face fierce competition for donor dollars…

An Accurate liver segmentation method using parallel computing algorithm

International Nuclear Information System (INIS)

Elbasher, Eiman Mohammed Khalied

2014-12-01

Computed Tomography (CT or CAT scan) is a noninvasive diagnostic imaging procedure that uses a combination of X-rays and computer technology to produce horizontal, or axial, images (often called slices) of the body. A CT scan shows detailed images of any part of the body, including the bones muscles, fat and organs CT scans are more detailed than standard x-rays. CT scans may be done with or without "contrast Contrast refers to a substance taken by mouth and/ or injected into an intravenous (IV) line that causes the particular organ or tissue under study to be seen more clearly. CT scan of the liver and biliary tract are used in the diagnosis of many diseases in the abdomen structures, particularly when another type of examination, such as X-rays, physical examination, and ultra sound is not conclusive. Unfortunately, the presence of noise and artifact in the edges and fine details in the CT images limit the contrast resolution and make diagnostic procedure more difficult. This experimental study was conducted at the College of Medical Radiological Science, Sudan University of Science and Technology and Fidel Specialist Hospital. The sample of study was included 50 patients. The main objective of this research was to study an accurate liver segmentation method using a parallel computing algorithm, and to segment liver and adjacent organs using image processing technique. The main technique of segmentation used in this study was watershed transform. The scope of image processing and analysis applied to medical application is to improve the quality of the acquired image and extract quantitative information from medical image data in an efficient and accurate way. The results of this technique agreed wit the results of Jarritt et al, (2010), Kratchwil et al, (2010), Jover et al, (2011), Yomamoto et al, (1996), Cai et al (1999), Saudha and Jayashree (2010) who used different segmentation filtering based on the methods of enhancing the computed tomography images. Anther

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

Contract mechanisms for coordinating pricing strategies in a supply chain with two consumer segments

NARCIS (Netherlands)

Nalla, V.R.; Venugopal, V.; Veen, van der J.A.A.

2009-01-01

This paper addresses pricing strategies in a serial supply chain (SC) consisting of a single Buyer, a single Supplier and where the end-consumers are comprised of two segments, each with a different willingness-to-pay. Under the assumption that the final demand and the segments’ willingness-to-pay

Evaluation of segmentation algorithms for optical coherence tomography images of ovarian tissue

Science.gov (United States)

Sawyer, Travis W.; Rice, Photini F. S.; Sawyer, David M.; Koevary, Jennifer W.; Barton, Jennifer K.

2018-02-01

Ovarian cancer has the lowest survival rate among all gynecologic cancers due to predominantly late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Optical coherence tomography (OCT) is an emerging technique that provides depthresolved, high-resolution images of biological tissue in real time and demonstrates great potential for imaging of ovarian tissue. Mouse models are crucial to quantitatively assess the diagnostic potential of OCT for ovarian cancer imaging; however, due to small organ size, the ovaries must rst be separated from the image background using the process of segmentation. Manual segmentation is time-intensive, as OCT yields three-dimensional data. Furthermore, speckle noise complicates OCT images, frustrating many processing techniques. While much work has investigated noise-reduction and automated segmentation for retinal OCT imaging, little has considered the application to the ovaries, which exhibit higher variance and inhomogeneity than the retina. To address these challenges, we evaluated a set of algorithms to segment OCT images of mouse ovaries. We examined ve preprocessing techniques and six segmentation algorithms. While all pre-processing methods improve segmentation, Gaussian filtering is most effective, showing an improvement of 32% +/- 1.2%. Of the segmentation algorithms, active contours performs best, segmenting with an accuracy of 0.948 +/- 0.012 compared with manual segmentation (1.0 being identical). Nonetheless, further optimization could lead to maximizing the performance for segmenting OCT images of the ovaries.

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.

Generation of organized germ layers from a single mouse embryonic stem cell.

Science.gov (United States)

Poh, Yeh-Chuin; Chen, Junwei; Hong, Ying; Yi, Haiying; Zhang, Shuang; Chen, Junjian; Wu, Douglas C; Wang, Lili; Jia, Qiong; Singh, Rishi; Yao, Wenting; Tan, Youhua; Tajik, Arash; Tanaka, Tetsuya S; Wang, Ning

2014-05-30

Mammalian inner cell mass cells undergo lineage-specific differentiation into germ layers of endoderm, mesoderm and ectoderm during gastrulation. It has been a long-standing challenge in developmental biology to replicate these organized germ layer patterns in culture. Here we present a method of generating organized germ layers from a single mouse embryonic stem cell cultured in a soft fibrin matrix. Spatial organization of germ layers is regulated by cortical tension of the colony, matrix dimensionality and softness, and cell-cell adhesion. Remarkably, anchorage of the embryoid colony from the 3D matrix to collagen-1-coated 2D substrates of ~1 kPa results in self-organization of all three germ layers: ectoderm on the outside layer, mesoderm in the middle and endoderm at the centre of the colony, reminiscent of generalized gastrulating chordate embryos. These results suggest that mechanical forces via cell-matrix and cell-cell interactions are crucial in spatial organization of germ layers during mammalian gastrulation. This new in vitro method could be used to gain insights on the mechanisms responsible for the regulation of germ layer formation.

Automatic segmentation of cerebral MR images using artificial neural networks

International Nuclear Information System (INIS)

Alirezaie, J.; Jernigan, M.E.; Nahmias, C.

1996-01-01

In this paper we present an unsupervised clustering technique for multispectral segmentation of magnetic resonance (MR) images of the human brain. Our scheme utilizes the Self Organizing Feature Map (SOFM) artificial neural network for feature mapping and generates a set of codebook vectors. By extending the network with an additional layer the map will be classified and each tissue class will be labelled. An algorithm has been developed for extracting the cerebrum from the head scan prior to the segmentation. Extracting the cerebrum is performed by stripping away the skull pixels from the T2 image. Three tissue types of the brain: white matter, gray matter and cerebral spinal fluid (CSF) are segmented accurately. To compare the results with other conventional approaches we applied the c-means algorithm to the problem

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.

Chemoselective single-site Earth-abundant metal catalysts at metal–organic framework nodes

Energy Technology Data Exchange (ETDEWEB)

Manna, Kuntal; Ji, Pengfei; Lin, Zekai; Greene, Francis X.; Urban, Ania; Thacker, Nathan C.; Lin, Wenbin (UC)

2016-08-30

Earth-abundant metal catalysts are critically needed for sustainable chemical synthesis. Here we report a simple, cheap and effective strategy of producing novel earth-abundant metal catalysts at metal–organic framework (MOF) nodes for broad-scope organic transformations. The straightforward metalation of MOF secondary building units (SBUs) with cobalt and iron salts affords highly active and reusable single-site solid catalysts for a range of organic reactions, including chemoselective borylation, silylation and amination of benzylic C–H bonds, as well as hydrogenation and hydroboration of alkenes and ketones. Our structural, spectroscopic and kinetic studies suggest that chemoselective organic transformations occur on site-isolated, electron-deficient and coordinatively unsaturated metal centres at the SBUs via σ-bond metathesis pathways and as a result of the steric environment around the catalytic site. MOFs thus provide a novel platform for the development of highly active and affordable base metal catalysts for the sustainable synthesis of fine chemicals.

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

Directory of Open Access Journals (Sweden)

Praveen Agarwal

2017-06-01

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

A segmentation approach for a delineation of terrestrial ecoregions

Science.gov (United States)

Nowosad, J.; Stepinski, T.

2017-12-01

Terrestrial ecoregions are the result of regionalization of land into homogeneous units of similar ecological and physiographic features. Terrestrial Ecoregions of the World (TEW) is a commonly used global ecoregionalization based on expert knowledge and in situ observations. Ecological Land Units (ELUs) is a global classification of 250 meters-sized cells into 4000 types on the basis of the categorical values of four environmental variables. ELUs are automatically calculated and reproducible but they are not a regionalization which makes them impractical for GIS-based spatial analysis and for comparison with TEW. We have regionalized terrestrial ecosystems on the basis of patterns of the same variables (land cover, soils, landform, and bioclimate) previously used in ELUs. Considering patterns of categorical variables makes segmentation and thus regionalization possible. Original raster datasets of the four variables are first transformed into regular grids of square-sized blocks of their cells called eco-sites. Eco-sites are elementary land units containing local patterns of physiographic characteristics and thus assumed to contain a single ecosystem. Next, eco-sites are locally aggregated using a procedure analogous to image segmentation. The procedure optimizes pattern homogeneity of all four environmental variables within each segment. The result is a regionalization of the landmass into land units characterized by uniform pattern of land cover, soils, landforms, climate, and, by inference, by uniform ecosystem. Because several disjoined segments may have very similar characteristics, we cluster the segments to obtain a smaller set of segment types which we identify with ecoregions. Our approach is automatic, reproducible, updatable, and customizable. It yields the first automatic delineation of ecoregions on the global scale. In the resulting vector database each ecoregion/segment is described by numerous attributes which make it a valuable GIS resource for

Medical Image Segmentation for Mobile Electronic Patient Charts Using Numerical Modeling of IoT

Directory of Open Access Journals (Sweden)

Seung-Hoon Chae

2014-01-01

Full Text Available Internet of Things (IoT brings telemedicine a new chance. This enables the specialist to consult the patient’s condition despite the fact that they are in different places. Medical image segmentation is needed for analysis, storage, and protection of medical image in telemedicine. Therefore, a variety of methods have been researched for fast and accurate medical image segmentation. Performing segmentation in various organs, the accurate judgment of the region is needed in medical image. However, the removal of region occurs by the lack of information to determine the region in a small region. In this paper, we researched how to reconstruct segmentation region in a small region in order to improve the segmentation results. We generated predicted segmentation of slices using volume data with linear equation and proposed improvement method for small regions using the predicted segmentation. In order to verify the performance of the proposed method, lung region by chest CT images was segmented. As a result of experiments, volume data segmentation accuracy rose from 0.978 to 0.981 and from 0.281 to 0.187 with a standard deviation improvement confirmed.

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.

Challenges for single molecule electronic devices with nanographene and organic molecules. Do single molecules offer potential as elements of electronic devices in the next generation?

Science.gov (United States)

Enoki, Toshiaki; Kiguchi, Manabu

2018-03-01

Interest in utilizing organic molecules to fabricate electronic materials has existed ever since organic (molecular) semiconductors were first discovered in the 1950s. Since then, scientists have devoted serious effort to the creation of various molecule-based electronic systems, such as molecular metals and molecular superconductors. Single-molecule electronics and the associated basic science have emerged over the past two decades and provided hope for the development of highly integrated molecule-based electronic devices in the future (after the Si-based technology era has ended). Here, nanographenes (nano-sized graphene) with atomically precise structures are among the most promising molecules that can be utilized for electronic/spintronic devices. To manipulate single small molecules for an electronic device, a single molecular junction has been developed. It is a powerful tool that allows even small molecules to be utilized. External electric, magnetic, chemical, and mechanical perturbations can change the physical and chemical properties of molecules in a way that is different from bulk materials. Therefore, the various functionalities of molecules, along with changes induced by external perturbations, allows us to create electronic devices that we cannot create using current top-down Si-based technology. Future challenges that involve the incorporation of condensed matter physics, quantum chemistry calculations, organic synthetic chemistry, and electronic device engineering are expected to open a new era in single-molecule device electronic technology.

Readout-Segmented Echo-Planar Imaging in Diffusion-Weighted MR Imaging in Breast Cancer: Comparison with Single-Shot Echo-Planar Imaging in Image Quality

International Nuclear Information System (INIS)

Kim, Yun Ju; Kim, Sung Hun; Kang, Bong Joo; Park, Chang Suk; Kim, Hyeon Sook; Son, Yo Han; Porter, David Andrew; Song, Byung Joo

2014-01-01

The purpose of this study was to compare the image quality of standard single-shot echo-planar imaging (ss-EPI) and that of readout-segmented EPI (rs-EPI) in patients with breast cancer. Seventy-one patients with 74 breast cancers underwent both ss-EPI and rs-EPI. For qualitative comparison of image quality, three readers independently assessed the two sets of diffusion-weighted (DW) images. To evaluate geometric distortion, a comparison was made between lesion lengths derived from contrast enhanced MR (CE-MR) images and those obtained from the corresponding DW images. For assessment of image parameters, signal-to-noise ratio (SNR), lesion contrast, and contrast-to-noise ratio (CNR) were calculated. The rs-EPI was superior to ss-EPI in most criteria regarding the qualitative image quality. Anatomical structure distinction, delineation of the lesion, ghosting artifact, and overall image quality were significantly better in rs-EPI. Regarding the geometric distortion, lesion length on ss-EPI was significantly different from that of CE-MR, whereas there were no significant differences between CE-MR and rs-EPI. The rs-EPI was superior to ss-EPI in SNR and CNR. Readout-segmented EPI is superior to ss-EPI in the aspect of image quality in DW MR imaging of the breast

Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration

Science.gov (United States)

Sun, Kaioqiong; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Torigian, Drew A.

2014-03-01

This paper proposes a thoracic anatomy segmentation method based on hierarchical recognition and delineation guided by a built fuzzy model. Labeled binary samples for each organ are registered and aligned into a 3D fuzzy set representing the fuzzy shape model for the organ. The gray intensity distributions of the corresponding regions of the organ in the original image are recorded in the model. The hierarchical relation and mean location relation between different organs are also captured in the model. Following the hierarchical structure and location relation, the fuzzy shape model of different organs is registered to the given target image to achieve object recognition. A fuzzy connected delineation method is then used to obtain the final segmentation result of organs with seed points provided by recognition. The hierarchical structure and location relation integrated in the model provide the initial parameters for registration and make the recognition efficient and robust. The 3D fuzzy model combined with hierarchical affine registration ensures that accurate recognition can be obtained for both non-sparse and sparse organs. The results on real images are presented and shown to be better than a recently reported fuzzy model-based anatomy recognition strategy.

Segmental Vitiligo.

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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.

In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation

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Chunlei Xia

2015-08-01

Full Text Available In this paper, we present a challenging task of 3D segmentation of individual plant leaves from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to improve the robustness of plant leaf segmentation. The low cost RGB-D camera is utilized to capture depth and color image in fields. Mean shift clustering is applied to segment plant leaves in depth image. Plant leaves are extracted from the natural background by examining vegetation of the candidate segments produced by mean shift. Subsequently, individual leaves are segmented from occlusions by active contour models. Automatic initialization of the active contour models is implemented by calculating the center of divergence from the gradient vector field of depth image. The proposed segmentation scheme is tested through experiments under greenhouse conditions. The overall segmentation rate is 87.97% while segmentation rates for single and occluded leaves are 92.10% and 86.67%, respectively. Approximately half of the experimental results show segmentation rates of individual leaves higher than 90%. Nevertheless, the proposed method is able to segment individual leaves from heavy occlusions.

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. 

SEGMENTATION IN TOURISTIC SECTOR: LGBT TOURISTS OF SAO PAULO

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Maurício Sanitá Azevedo

2012-05-01

Full Text Available The objective of this article is to present the tourism segment LGBT (Lesbian, Gays, Bisexual and Transgender of Sao Paulo city and gather information about his profile as important support for the tourism sector in defining their marketing strategies. It was carried out an exploratory and statistical data from government and representatives of this public for a description and analysis of data on the composition and profile of this segment, as well as the strategies being used by companies to captivate it and loyalty it. It also composes a Descriptive Study carried out by the Tourism Observatory of São Paulo next to the participants of the Sao Paulo Gay Parade in 2011. As results, it appears that LGBT public presents behavioral particularities as buyers of tourist products, providing during their stay, higher investments than others tourism segments, because it comes as a tourist for a longer period of stay in Sao Paulo, thus leaving more financial resources in the city. It also presents as results, examples of effective use of differentiation strategies by organizations, attraction, service and loyalty in this segment.

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.

Auto-segmentation of low-risk clinical target volume for head and neck radiation therapy.

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Yang, Jinzhong; Beadle, Beth M; Garden, Adam S; Gunn, Brandon; Rosenthal, David; Ang, Kian; Frank, Steven; Williamson, Ryan; Balter, Peter; Court, Laurence; Dong, Lei

2014-01-01

To investigate atlas-based auto-segmentation methods to improve the quality of the delineation of low-risk clinical target volumes (CTVs) of unilateral tonsil cancers. Sixteen patients received intensity modulated radiation therapy for left tonsil tumors. These patients were treated by a total of 8 oncologists, who delineated all contours manually on the planning CT image. We chose 6 of the patients as atlas cases and used atlas-based auto-segmentation to map each the atlas CTV to the other 10 patients (test patients). For each test patient, the final contour was produced by combining the 6 individual segmentations from the atlases using the simultaneous truth and performance level estimation algorithm. In addition, for each test patient, we identified a single atlas that produced deformed contours best matching the physician's manual contours. The auto-segmented contours were compared with the physician's manual contours using the slice-wise Hausdorff distance (HD), the slice-wise Dice similarity coefficient (DSC), and a total volume overlap index. No single atlas consistently produced good results for all 10 test cases. The multiatlas segmentation achieved a good agreement between auto-segmented contours and manual contours, with a median slice-wise HD of 7.4 ± 1.0 mm, median slice-wise DSC of 80.2% ± 5.9%, and total volume overlap of 77.8% ± 3.3% over the 10 test cases. For radiation oncologists who contoured both the test case and one of the atlas cases, the best atlas for a test case had almost always been contoured by the oncologist who had contoured that test case, indicating that individual physician's practice dominated in target delineation and was an important factor in optimal atlas selection. Multiatlas segmentation may improve the quality of CTV delineation in clinical practice for unilateral tonsil cancers. We also showed that individual physician's practice was an important factor in selecting the optimal atlas for atlas-based auto-segmentation

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).

Application of neural network in market segmentation: A review on recent trends

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Manojit Chattopadhyay

2012-04-01

Full Text Available Despite the significance of Artificial Neural Network (ANN algorithm to market segmentation, there is a need of a comprehensive literature review and a classification system for it towards identification of future trend of market segmentation research. The present work is the first identifiable academic literature review of the application of neural network based techniques to segmentation. Our study has provided an academic database of literature between the periods of 2000–2010 and proposed a classification scheme for the articles. One thousands (1000 articles have been identified, and around 100 relevant selected articles have been subsequently reviewed and classified based on the major focus of each paper. Findings of this study indicated that the research area of ANN based applications are receiving most research attention and self organizing map based applications are second in position to be used in segmentation. The commonly used models for market segmentation are data mining, intelligent system etc. Our analysis furnishes a roadmap to guide future research and aid knowledge accretion and establishment pertaining to the application of ANN based techniques in market segmentation. Thus the present work will significantly contribute to both the industry and academic research in business and marketing as a sustainable valuable knowledge source of market segmentation with the future trend of ANN application in segmentation.

Identifying uniformly mutated segments within repeats.

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Sahinalp, S Cenk; Eichler, Evan; Goldberg, Paul; Berenbrink, Petra; Friedetzky, Tom; Ergun, Funda

2004-12-01

Given a long string of characters from a constant size alphabet we present an algorithm to determine whether its characters have been generated by a single i.i.d. random source. More specifically, consider all possible n-coin models for generating a binary string S, where each bit of S is generated via an independent toss of one of the n coins in the model. The choice of which coin to toss is decided by a random walk on the set of coins where the probability of a coin change is much lower than the probability of using the same coin repeatedly. We present a procedure to evaluate the likelihood of a n-coin model for given S, subject a uniform prior distribution over the parameters of the model (that represent mutation rates and probabilities of copying events). In the absence of detailed prior knowledge of these parameters, the algorithm can be used to determine whether the a posteriori probability for n=1 is higher than for any other n>1. Our algorithm runs in time O(l4logl), where l is the length of S, through a dynamic programming approach which exploits the assumed convexity of the a posteriori probability for n. Our test can be used in the analysis of long alignments between pairs of genomic sequences in a number of ways. For example, functional regions in genome sequences exhibit much lower mutation rates than non-functional regions. Because our test provides means for determining variations in the mutation rate, it may be used to distinguish functional regions from non-functional ones. Another application is in determining whether two highly similar, thus evolutionarily related, genome segments are the result of a single copy event or of a complex series of copy events. This is particularly an issue in evolutionary studies of genome regions rich with repeat segments (especially tandemly repeated segments).

A martian case study of segmenting images automatically for granulometry and sedimentology, Part 2: Assessment

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Karunatillake, Suniti; McLennan, Scott M.; Herkenhoff, Kenneth E.; Husch, Jonathan M.; Hardgrove, Craig; Skok, J. R.

2014-02-01

In a companion work, we bridge the gap between mature segmentation software used in terrestrial sedimentology and emergent planetary segmentation with an original algorithm optimized to segment whole images from the Microscopic Imager (MI) of the Mars Exploration Rovers (MER). In this work, we compare its semi-automated outcome with manual photoanalyses using unconsolidated sediment at Gusev and Meridiani Planum sites for geologic context. On average, our code and manual segmentation converge to within ∼10% in the number and total area of identified grains in a pseudo-random, single blind comparison of 50 samples. Unlike manual segmentation, it also locates finer grains in an image with internal consistency, enabling robust comparisons across geologic contexts. When implemented in Mathematica-8, the algorithm segments an entire MI image within minutes, surpassing the extent and speed possible with manual segmentation by about a factor of ten. These results indicate that our algorithm enables not only new sedimentological insight from the MER MI data, but also detailed sedimentology with the Mars Science Laboratory’s Mars Hand Lens Instrument.

Segmentation and object-oriented classification of wetlands in a karst Florida landscape using multi-season Landsat-7 ETM+ Imagery

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Segmentation and object-oriented processing of single-season and multi-season Landsat-7 ETM+ data was utilized for the classification of wetlands in a 1560 km2 study area of north central Florida. This segmentation and object-oriented classification outperformed the traditional ...

Unsupervised motion-based object segmentation refined by color

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

2003-06-01

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

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-06-15

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

Allocating time to future tasks: the effect of task segmentation on planning fallacy bias.

Science.gov (United States)

Forsyth, Darryl K; Burt, Christopher D B

2008-06-01

The scheduling component of the time management process was used as a "paradigm" to investigate the allocation of time to future tasks. In three experiments, we compared task time allocation for a single task with the summed time allocations given for each subtask that made up the single task. In all three, we found that allocated time for a single task was significantly smaller than the summed time allocated to the individual subtasks. We refer to this as the segmentation effect. In Experiment 3, we asked participants to give estimates by placing a mark on a time line, and found that giving time allocations in the form of rounded close approximations probably does not account for the segmentation effect. We discuss the results in relation to the basic processes used to allocate time to future tasks and the means by which planning fallacy bias might be reduced.

Image-guided regularization level set evolution for MR image segmentation and bias field correction.

Science.gov (United States)

Wang, Lingfeng; Pan, Chunhong

2014-01-01

Magnetic resonance (MR) image segmentation is a crucial step in surgical and treatment planning. In this paper, we propose a level-set-based segmentation method for MR images with intensity inhomogeneous problem. To tackle the initialization sensitivity problem, we propose a new image-guided regularization to restrict the level set function. The maximum a posteriori inference is adopted to unify segmentation and bias field correction within a single framework. Under this framework, both the contour prior and the bias field prior are fully used. As a result, the image intensity inhomogeneity can be well solved. Extensive experiments are provided to evaluate the proposed method, showing significant improvements in both segmentation and bias field correction accuracies as compared with other state-of-the-art approaches. Copyright © 2014 Elsevier Inc. All rights reserved.

Dynamic segment shared protection for multicast traffic in meshed wavelength-division-multiplexing optical networks

Science.gov (United States)

Liao, Luhua; Li, Lemin; Wang, Sheng

2006-12-01

We investigate the protection approach for dynamic multicast traffic under shared risk link group (SRLG) constraints in meshed wavelength-division-multiplexing optical networks. We present a shared protection algorithm called dynamic segment shared protection for multicast traffic (DSSPM), which can dynamically adjust the link cost according to the current network state and can establish a primary light-tree as well as corresponding SRLG-disjoint backup segments for a dependable multicast connection. A backup segment can efficiently share the wavelength capacity of its working tree and the common resources of other backup segments based on SRLG-disjoint constraints. The simulation results show that DSSPM not only can protect the multicast sessions against a single-SRLG breakdown, but can make better use of the wavelength resources and also lower the network blocking probability.

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.

Bilevel Optimization for Scene Segmentation of LiDAR Point Cloud

Directory of Open Access Journals (Sweden)

LI Minglei

2018-02-01

Full Text Available The segmentation of point clouds obtained by light detection and ranging (LiDAR systems is a critical step for many tasks,such as data organization,reconstruction and information extraction.In this paper,we propose a bilevel progressive optimization algorithm based on the local differentiability.First,we define the topological relation and distance metric of points in the framework of Riemannian geometry,and in the point-based level using k-means method generates over-segmentation results,e.g.super voxels.Then these voxels are formulated as nodes which consist a minimal spanning tree.High level features are extracted from voxel structures,and a graph-based optimization method is designed to yield the final adaptive segmentation results.The implementation experiments on real data demonstrate that our method is efficient and superior to state-of-the-art methods.

Segmentation of head magnetic resonance image using self-mapping characteristic

International Nuclear Information System (INIS)

Madokoro, Hirokazu; Sato, Kazuhito; Ishii, Masaki; Kadowaki, Sakura

2004-01-01

In this paper, we proposed a segmentation method, for head magnetic resonance (MR) images. Our method used self mapping characteristic of a self-organization map (SOM), and it does not need the setting of the representative point by the operator. We considered the continuity and boundary in the brain tissues by the definition of the local block. In the evaluation experiment, we obtained the segmentation result of matching anatomical structure information. In addition, our method applied the clinical MR images, it was possible to obtain the effective and objective result for supporting the diagnosis of the brain atrophy by the doctor. (author)

Induction of prophage lambda by chlorinated organics: Detection of some single-species/single-site carcinogens

Energy Technology Data Exchange (ETDEWEB)

DeMarini, D.M.; Brooks, H.G. (Environmental Protection Agency, Research Triangle Park, NC (United States))

1992-01-01

Twenty-eight chlorinated organic compounds were evaluated for their ability to induce DNA damage using the Microscreen prophage-induction assay in Escherichia coli. Comparison of the performance characteristics of the prophage-induction and Salmonella assays to rodent carcinogenicity assays showed that the prophage-induction assay had a somewhat higher specificity than did the Salmonella assay (70% vs. 50%); sensitivity, concordance, and positive and negative predictivity were similar for the two microbial assays. The Microscreen prophage-induction assay failed to detect eight carcinogens, perhaps due to toxicity or other unknown factors; five of these eight carcinogens were detected by the Salmonella assay. However, the prophage-induction assay did detect six carcinogens that were not detected by the Salmonella assay, and five of these were single-species, single-site carcinogens, mostly mouse liver carcinogens. Some of these carcinogens, such as the chloroethanes, produce free radicals, which may be the basis for their carcinogenicity and ability to induce prophage. The prophage-induction (or other SOS) assay may be useful in identifying some genotoxic chlorinated carcinogens that induce DNA damage that do not revert the standard Salmonella tester strains.

Task-based evaluation of segmentation algorithms for diffusion-weighted MRI without using a gold standard

International Nuclear Information System (INIS)

Jha, Abhinav K; Kupinski, Matthew A; Rodríguez, Jeffrey J; Stephen, Renu M; Stopeck, Alison T

2012-01-01

In many studies, the estimation of the apparent diffusion coefficient (ADC) of lesions in visceral organs in diffusion-weighted (DW) magnetic resonance images requires an accurate lesion-segmentation algorithm. To evaluate these lesion-segmentation algorithms, region-overlap measures are used currently. However, the end task from the DW images is accurate ADC estimation, and the region-overlap measures do not evaluate the segmentation algorithms on this task. Moreover, these measures rely on the existence of gold-standard segmentation of the lesion, which is typically unavailable. In this paper, we study the problem of task-based evaluation of segmentation algorithms in DW imaging in the absence of a gold standard. We first show that using manual segmentations instead of gold-standard segmentations for this task-based evaluation is unreliable. We then propose a method to compare the segmentation algorithms that does not require gold-standard or manual segmentation results. The no-gold-standard method estimates the bias and the variance of the error between the true ADC values and the ADC values estimated using the automated segmentation algorithm. The method can be used to rank the segmentation algorithms on the basis of both the ensemble mean square error and precision. We also propose consistency checks for this evaluation technique. (paper)

Unusual fatal multiple-organ dysfunction and pancreatitis induced by a single wasp sting

Directory of Open Access Journals (Sweden)

C Azad

2011-01-01

Full Text Available Acute onset of multiple organ dysfunction syndrome (MODS is a well-known complication following multiple wasp stings. However, MODS after a single wasp sting has been rarely reported in children and acute pancreatitis have probably never been observed before. Herein we describe the case of a 12-year-old boy who had urticaria and abdominal pain after a single wasp sting. The child gradually developed MODS while his abdominal complaints were worsening. Despite aggressive supportive management, the child did not survive. Afterward, the cause of the acute abdomen was finally diagnosed as acute pancreatitis. Both MODS and pancreatitis following a single wasp sting are very unusual. Thus, although pancreatitis is rarely manifested, it should be suspected after a wasp sting if there are predominant abdominal symptoms.

Segmentation-driven compound document coding based on H.264/AVC-INTRA.

Science.gov (United States)

Zaghetto, Alexandre; de Queiroz, Ricardo L

2007-07-01

In this paper, we explore H.264/AVC operating in intraframe mode to compress a mixed image, i.e., composed of text, graphics, and pictures. Even though mixed contents (compound) documents usually require the use of multiple compressors, we apply a single compressor for both text and pictures. For that, distortion is taken into account differently between text and picture regions. Our approach is to use a segmentation-driven adaptation strategy to change the H.264/AVC quantization parameter on a macroblock by macroblock basis, i.e., we deviate bits from pictorial regions to text in order to keep text edges sharp. We show results of a segmentation driven quantizer adaptation method applied to compress documents. Our reconstructed images have better text sharpness compared to straight unadapted coding, at negligible visual losses on pictorial regions. Our results also highlight the fact that H.264/AVC-INTRA outperforms coders such as JPEG-2000 as a single coder for compound images.

Information or prices, which is most powerful in increasing consumer demand for organic vegetables?

DEFF Research Database (Denmark)

Smed, Sinne; Andersen, Laura Mørch

2012-01-01

of consuming conventional vegetables on demand for organic foods for six different segments of Danish households. Three of these segments are positive towards organics whereas the remaining three segments are negative or indifferent. Using the double hurdle model we estimate partial effects of both directly...... and indirectly obtained information as well as prices. The results show, that there are larger effects of information for households where the information is in accordance with initial knowledge and attitudes, hence the positive segments react more to information whereas the negative segments react more......Based on a unique and very detailed panel dataset covering consumption of organically and conventionally produced vegetables in the years 2005 - 2007, we examine the effects of information about positive health effects of consuming organic vegetables and information about negative health effects...

Short segment myelitis as a first manifestation of neuromyelitis optica spectrum disorders.

Science.gov (United States)

Huh, So-Young; Kim, Su-Hyun; Hyun, Jae-Won; Jeong, In Hye; Park, Min Su; Lee, Sang-Hyun; Kim, Ho Jin

2017-03-01

Some patients with neuromyelitis optica spectrum disorders (NMOSD) present with spinal cord lesions extending fewer than three vertebral segments (short transverse myelitis, STM), hindering an early diagnosis. We investigated the frequency and imaging characteristics of STM lesions in patients presenting with myelitis as an initial manifestation of NMOSD. Patients seen at three referral hospitals in Korea between June 2005 and March 2015 who met the following inclusion criteria were recruited for review: seropositivity for aquaporin-4 antibody, initial presentation with myelitis and spinal cord magnetic resonance imaging (MRI) performed within 1 month of initial myelitis onset. Of the 76 enrolled patients, 65 (85.5%) collectively had 69 longitudinally extensive transverse myelitis lesions, while the remaining 11 (14.5%) had a total of 15 STM lesions. Of the 15 STM lesions, 5 spanned 2.5 vertebral segments, 6 were continuous over two segments, 3 showed a length of 1.5 segments and 1 was confined to a single segment. On axial imaging, all of the STM lesions involved the central grey matter. These MRI findings suggested that STM does not preclude the possibility of an NMOSD diagnosis.

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.

Single-cell MALDI-MS as an analytical tool for studying intrapopulation metabolic heterogeneity of unicellular organisms.

Science.gov (United States)

Amantonico, Andrea; Urban, Pawel L; Fagerer, Stephan R; Balabin, Roman M; Zenobi, Renato

2010-09-01

Heterogeneity is a characteristic feature of all populations of living organisms. Here we make an attempt to validate a single-cell mass spectrometric method for detection of changes in metabolite levels occurring in populations of unicellular organisms. Selected metabolites involved in central metabolism (ADP, ATP, GTP, and UDP-Glucose) could readily be detected in single cells of Closterium acerosum by means of negative-mode matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS). The analytical capabilities of this approach were characterized using standard compounds. The method was then used to study populations of individual cells with different levels of the chosen metabolites. With principal component analysis and support vector machine algorithms, it was possible to achieve a clear separation of individual C. acerosum cells in different metabolic states. This study demonstrates the suitability of mass spectrometric analysis of metabolites in single cells to measure cell-population heterogeneity.

Segmentation of multiple sclerosis lesions in MR images: a review

International Nuclear Information System (INIS)

Mortazavi, Daryoush; Kouzani, Abbas Z.; Soltanian-Zadeh, Hamid

2012-01-01

Multiple sclerosis (MS) is an inflammatory demyelinating disease that the parts of the nervous system through the lesions generated in the white matter of the brain. It brings about disabilities in different organs of the body such as eyes and muscles. Early detection of MS and estimation of its progression are critical for optimal treatment of the disease. For diagnosis and treatment evaluation of MS lesions, they may be detected and segmented in Magnetic Resonance Imaging (MRI) scans of the brain. However, due to the large amount of MRI data to be analyzed, manual segmentation of the lesions by clinical experts translates into a very cumbersome and time consuming task. In addition, manual segmentation is subjective and prone to human errors. Several groups have developed computerized methods to detect and segment MS lesions. These methods are not categorized and compared in the past. This paper reviews and compares various MS lesion segmentation methods proposed in recent years. It covers conventional methods like multilevel thresholding and region growing, as well as more recent Bayesian methods that require parameter estimation algorithms. It also covers parameter estimation methods like expectation maximization and adaptive mixture model which are among unsupervised techniques as well as kNN and Parzen window methods that are among supervised techniques. Integration of knowledge-based methods such as atlas-based approaches with Bayesian methods increases segmentation accuracy. In addition, employing intelligent classifiers like Fuzzy C-Means, Fuzzy Inference Systems, and Artificial Neural Networks reduces misclassified voxels. (orig.)

Segmentation of multiple sclerosis lesions in MR images: a review

Energy Technology Data Exchange (ETDEWEB)

Mortazavi, Daryoush; Kouzani, Abbas Z. [Deakin University, School of Engineering, Geelong, Victoria (Australia); Soltanian-Zadeh, Hamid [Henry Ford Health System, Image Analysis Laboratory, Radiology Department, Detroit, MI (United States); University of Tehran, Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, Tehran (Iran, Islamic Republic of); School of Cognitive Sciences, Institute for Studies in Theoretical Physics and Mathematics (IPM), Tehran (Iran, Islamic Republic of)

2012-04-15

Multiple sclerosis (MS) is an inflammatory demyelinating disease that the parts of the nervous system through the lesions generated in the white matter of the brain. It brings about disabilities in different organs of the body such as eyes and muscles. Early detection of MS and estimation of its progression are critical for optimal treatment of the disease. For diagnosis and treatment evaluation of MS lesions, they may be detected and segmented in Magnetic Resonance Imaging (MRI) scans of the brain. However, due to the large amount of MRI data to be analyzed, manual segmentation of the lesions by clinical experts translates into a very cumbersome and time consuming task. In addition, manual segmentation is subjective and prone to human errors. Several groups have developed computerized methods to detect and segment MS lesions. These methods are not categorized and compared in the past. This paper reviews and compares various MS lesion segmentation methods proposed in recent years. It covers conventional methods like multilevel thresholding and region growing, as well as more recent Bayesian methods that require parameter estimation algorithms. It also covers parameter estimation methods like expectation maximization and adaptive mixture model which are among unsupervised techniques as well as kNN and Parzen window methods that are among supervised techniques. Integration of knowledge-based methods such as atlas-based approaches with Bayesian methods increases segmentation accuracy. In addition, employing intelligent classifiers like Fuzzy C-Means, Fuzzy Inference Systems, and Artificial Neural Networks reduces misclassified voxels. (orig.)

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

Efficient white organic light emission by single emitting layer

Energy Technology Data Exchange (ETDEWEB)

Ko, Young Wook; Chung, Choong-Heui; Lee, Jin Ho; Kim, Yong-Hae; Sohn, Choong-Yong; Kim, Bong-Chul; Hwang, Chi-Sun; Song, Yoon-Ho; Lim, Jongtae; Ahn, Young-Joo; Kang, Gi-Wook; Lee, Namheon; Lee, Changhee

2003-02-24

Stable organic white light-emitting diodes are successfully fabricated by a single organic white emitting layer, which is Bis (2-methyl-8-quinolinato) (triphenylsiloxy) aluminum (III) (SAlq) doped red fluorescent dye of 4-(dicyanomethylene)-2-tert-butyl-6(1,1,7,7-tetramethyljulolidyl-9-enyl)- 4H-pyran (DCJTB). The incomplete energy transfer from blue-emitting SAlq to red-emitting DCJTB enables to obtain a stable white balanced light-emission by the DCJTB doping concentration of 0.5%. A device with the structure of ITO/TPD (50 nm)/SAlq:DCJTB (30 nm, 0.5%)/Alq{sub 3} (20 nm)/LiF (0.5 nm)/Al (110 nm) shows maximum luminance of 20 400 cd/m{sup 2} at 810 mA/cm{sup 2}, external quantum efficiency of 2% at 200 cd/m{sup 2} ({approx}3 mA/cm{sup 2}), power efficiency of 2.3 lm/W at 67 cd/m{sup 2} ({approx}1 mA/cm{sup 2}), and a Commission Internationale de l'Eclairage chromaticity coordinates of (0.34, 0.39) at 1.8 mA/cm{sup 2} to (0.31, 0.38) at 36 mA/cm{sup 2}.

Near-diffraction-limited segmented broad area diode laser based on off-axis spectral beam combining

DEFF Research Database (Denmark)

Jensen, O.B.; Thestrup Nielsen, Birgitte; Andersen, Peter E.

2006-01-01

-feedback scheme we are able to improve the beam quality of the laser by a factor of 23 from M-2 = 55 for the free-running diode laser to M-2 = 2.4 for the laser with feedback at a drive current of 2.2 A. The improved M-2 value is a factor of 3.4 below M-2 = 8.2 for a single free-running segment. This is the first......The beam quality of a 500-mu m-wide broad area diode laser with five active segments has been improved beyond the beam quality of the individual segments. The principle of this new laser system is based on off-axis feedback in combination with spectral beam combining. By using a double...... time that the beam quality of a segmented broad area diode laser has been improved beyond the beam quality of the individual segments....

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

Cross-Border Mergers and Market Segmentation (Replaces TILEC DP 2010-035)

NARCIS (Netherlands)

Ray Chaudhuri, A.

2011-01-01

This paper shows that cross-border mergers are more likely to occur in industries which serve multiple segmented markets rather than a single integrated market, given that cost functions are strictly convex. The product price rises in the market where an acquisition is made but falls in the other,

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...

Segment-Specific Adhesion as a Driver of Convergent Extension

Science.gov (United States)

Vroomans, Renske M. A.; Hogeweg, Paulien; ten Tusscher, Kirsten H. W. J.

2015-01-01

Convergent extension, the simultaneous extension and narrowing of tissues, is a crucial event in the formation of the main body axis during embryonic development. It involves processes on multiple scales: the sub-cellular, cellular and tissue level, which interact via explicit or intrinsic feedback mechanisms. Computational modelling studies play an important role in unravelling the multiscale feedbacks underlying convergent extension. Convergent extension usually operates in tissue which has been patterned or is currently being patterned into distinct domains of gene expression. How such tissue patterns are maintained during the large scale tissue movements of convergent extension has thus far not been investigated. Intriguingly, experimental data indicate that in certain cases these tissue patterns may drive convergent extension rather than requiring safeguarding against convergent extension. Here we use a 2D Cellular Potts Model (CPM) of a tissue prepatterned into segments, to show that convergent extension tends to disrupt this pre-existing segmental pattern. However, when cells preferentially adhere to cells of the same segment type, segment integrity is maintained without any reduction in tissue extension. Strikingly, we demonstrate that this segment-specific adhesion is by itself sufficient to drive convergent extension. Convergent extension is enhanced when we endow our in silico cells with persistence of motion, which in vivo would naturally follow from cytoskeletal dynamics. Finally, we extend our model to confirm the generality of our results. We demonstrate a similar effect of differential adhesion on convergent extension in tissues that can only extend in a single direction (as often occurs due to the inertia of the head region of the embryo), and in tissues prepatterned into a sequence of domains resulting in two opposing adhesive gradients, rather than alternating segments. PMID:25706823

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

Science.gov (United States)

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

2017-01-01

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

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...

Software test plan/description/report (STP/STD/STR) for the enhanced logistics intratheater support tool (ELIST) global data segment. Version 8.1.0.0, Database Instance Segment Version 8.1.0.0, ...[elided] and Reference Data Segment Version 8.1.0.0 for Solaris 7; TOPICAL

International Nuclear Information System (INIS)

Dritz, K.; Absil-Mills, M.; Jacobs, K.

2002-01-01

This document is the Software Test Plan/Description/Report (STP/STD/STR) for the DII COE Enhanced Logistics Intratheater Support Tool (ELIST) mission application. It combines in one document the information normally presented separately in a Software Test Plan, a Software Test Description, and a Software Test Report; it also presents this information in one place for all the segments of the ELIST mission application. The primary purpose of this document is to show that ELIST has been tested by the developer and found, by that testing, to install, deinstall, and work properly. The information presented here is detailed enough to allow the reader to repeat the testing independently. The remainder of this document is organized as follows. Section 1.1 identifies the ELIST mission application. Section 2 is the list of all documents referenced in this document. Section 3, the Software Test Plan, outlines the testing methodology and scope-the latter by way of a concise summary of the tests performed. Section 4 presents detailed descriptions of the tests, along with the expected and observed results; that section therefore combines the information normally found in a Software Test Description and a Software Test Report. The remaining small sections present supplementary information. Throughout this document, the phrase ELIST IP refers to the Installation Procedures (IP) for the Enhanced Logistics Intratheater Support Tool (ELIST) Global Data Segment, Database Instance Segment, Database Fill Segment, Database Segment, Database Utility Segment, Software Segment, and Reference Data Segment

Three-dimensional lung tumor segmentation from x-ray computed tomography using sparse field active models.

Science.gov (United States)

Awad, Joseph; Owrangi, Amir; Villemaire, Lauren; O'Riordan, Elaine; Parraga, Grace; Fenster, Aaron

2012-02-01

Manual segmentation of lung tumors is observer dependent and time-consuming but an important component of radiology and radiation oncology workflow. The objective of this study was to generate an automated lung tumor measurement tool for segmentation of pulmonary metastatic tumors from x-ray computed tomography (CT) images to improve reproducibility and decrease the time required to segment tumor boundaries. The authors developed an automated lung tumor segmentation algorithm for volumetric image analysis of chest CT images using shape constrained Otsu multithresholding (SCOMT) and sparse field active surface (SFAS) algorithms. The observer was required to select the tumor center and the SCOMT algorithm subsequently created an initial surface that was deformed using level set SFAS to minimize the total energy consisting of mean separation, edge, partial volume, rolling, distribution, background, shape, volume, smoothness, and curvature energies. The proposed segmentation algorithm was compared to manual segmentation whereby 21 tumors were evaluated using one-dimensional (1D) response evaluation criteria in solid tumors (RECIST), two-dimensional (2D) World Health Organization (WHO), and 3D volume measurements. Linear regression goodness-of-fit measures (r(2) = 0.63, p < 0.0001; r(2) = 0.87, p < 0.0001; and r(2) = 0.96, p < 0.0001), and Pearson correlation coefficients (r = 0.79, p < 0.0001; r = 0.93, p < 0.0001; and r = 0.98, p < 0.0001) for 1D, 2D, and 3D measurements, respectively, showed significant correlations between manual and algorithm results. Intra-observer intraclass correlation coefficients (ICC) demonstrated high reproducibility for algorithm (0.989-0.995, 0.996-0.997, and 0.999-0.999) and manual measurements (0.975-0.993, 0.985-0.993, and 0.980-0.992) for 1D, 2D, and 3D measurements, respectively. The intra-observer coefficient of variation (CV%) was low for algorithm (3.09%-4.67%, 4.85%-5.84%, and 5

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

Directory of Open Access Journals (Sweden)

Javier Ortega-Hernández

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

Hand-Assisted Laparoscopic (HAL) Multiple Segmental Colorectal Resections: Are They Feasible and Safe?

Science.gov (United States)

Taggarshe, Deepa; Attuwaybi, Bashir O; Matier, Brian; Visco, Jeffrey J; Butler, Bryan N

2015-04-01

The objective of this study was to evaluate the short-term outcomes of synchronous hand-assisted laparoscopic (HAL) segmental colorectal resections. The surgical options for synchronous colonic pathology include extensive colonic resection with single anastomosis, multiple synchronous segmental resections with multiple anastomoses, or staged resections. Traditionally, multiple open, synchronous, segmental resections have been performed. There is a lack of data on HAL multiple segmental colorectal resections. A retrospective chart review was compiled on all patients who underwent HAL synchronous segmental colorectal resections by all the colorectal surgeons from our Group during the period of 1999 to 2014. Demographics, operative details, and short-term outcomes are reported. During the period, 9 patients underwent HAL synchronous multiple segmental colorectal resections. There were 5 women and 4 men, with median age of 54 (24-83) years and median BMI of 24 (19.8-38.7) kg/m(2). Two patients were on long-term corticosteroid therapy. The median operative time was 210 (120-330) minutes and median operative blood loss was 200 (75-300) mLs. The median duration for return of bowel function was 2 days and the median length of stay was 3.5 days. We had 2 minor wound infections. There were no deaths. Synchronous segmental colorectal resections with anastomoses using the hand-assisted laparoscopic technique are safe. Early conversion to open and use of stomas are advisable in challenging cases.

Effect of a novel motion correction algorithm (SSF) on the image quality of coronary CTA with intermediate heart rates: Segment-based and vessel-based analyses

Energy Technology Data Exchange (ETDEWEB)

Li, Qianwen, E-mail: qianwen18@126.com; Li, Pengyu, E-mail: lipyu818@gmail.com; Su, Zhuangzhi, E-mail: suzhuangzhi@xwh.ccmu.edu.cn; Yao, Xinyu, E-mail: 314985151@qq.com; Wang, Yan, E-mail: wy19851121@126.com; Wang, Chen, E-mail: fskwangchen@gmail.com; Du, Xiangying, E-mail: duxying_xw@163.com; Li, Kuncheng, E-mail: kuncheng.li@gmail.com

2014-11-15

Highlights: • SSF provided better image quality than single-sector and bi-sector reconstruction among the intermediate heart rates (65–75 bpm). • Evidence for the application of prospective ECG-triggered coronary CTA with SSF onto an expanded heart rate range. • Information about the inconsistent effectiveness of SSF among the segments of coronary artery. - Abstract: Purpose: To evaluate the effect of SnapShot Freeze (SSF) reconstruction at an intermediate heart-rate (HR) range (65–75 bpm) and compare this method with single-sector reconstruction and bi-sector reconstruction on segmental and vessel bases in retrospective coronary computed tomography angiography (CCTA). Materials and methods: Retrospective electrocardiogram-gated CCTA was performed on 37 consecutive patients with HR between 65 and 75 bpm using a 64-row CT scanner. Retrospective single-sector reconstruction, bi-sector reconstruction, and SSF were performed for each patient. Multi-phase single-sector reconstruction was performed to select the optimal phase. SSF and bi-sector images were also reconstructed at the optimal phase. The images were interpreted in an intent-to-diagnose fashion by two experienced readers using a 5-point scale, with 3 points as diagnostically acceptable. Image quality among the three reconstruction groups were compared on per-patient, per-vessel, and per-segment bases. Results: The average HR of the enrolled patients was 69.4 ± 2.7 bpm. A total of 111 vessels and 481 coronary segments were assessed. SSF provided significantly higher interpretability of the coronary segments than bi-sector reconstructions. The qualified and excellent rates of SSF (97.9% and 82.3%) were significantly higher than those of single-sector (92.9% and 66.3%) and bi-sector (90.9% and 64.7%) reconstructions. The image quality score (IQS) using SSF was also significantly higher than those of single-sector and bi-sector reconstructions both on per-patient and per-vessel bases. On per-segment

Sympatho-vagal balance, as quantified by ANSindex, predicts post spinal hypotension and vasopressor requirement in parturients undergoing lower segmental cesarean section: a single blinded prospective observational study.

Science.gov (United States)

Prashanth, Anitha; Chakravarthy, Murali; George, Antony; Mayur, Rohini; Hosur, Rajathadri; Pargaonkar, Sumant

2017-08-01

Hypotension subsequent to spinal anesthesia occurs in a significant number of parturients undergoing lower segment caesarian section. Currently available methods to predict the incidence of hypotension, its severity and the outcome are sub-optimal. Many workers have used basal heart rate as one of the predictors. But using this method it is not possible to objectively analyze and predict the extent and severity of hypotension. We used an equipment measuring the level of sympatho-vagal balance, ANSiscope™, which derives these values from computed value of RR interval variability. We made a single measure of the value which was blinded to the patient and the anesthesiologist. We studied one hundred eight patients who underwent lower segment caesarian section under spinal anesthesia and found the variability of preoperative ANSindex (% activity displayed by the equipment) from 9 to 65 %. Higher ANSindex value was significantly associated with post spinal hypotension (p 0.017). A value of 24 % indicated the critical level above which hypotension appeared commonly. The ANSindex value might help anesthesiologist to anticipate and prepare for hypotension that is likely to ensue.

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.

High-Resolution Gamma-Ray Imaging Measurements Using Externally Segmented Germanium Detectors

Science.gov (United States)

Callas, J.; Mahoney, W.; Skelton, R.; Varnell, L.; Wheaton, W.

1994-01-01

Fully two-dimensional gamma-ray imaging with simultaneous high-resolution spectroscopy has been demonstrated using an externally segmented germanium sensor. The system employs a single high-purity coaxial detector with its outer electrode segmented into 5 distinct charge collection regions and a lead coded aperture with a uniformly redundant array (URA) pattern. A series of one-dimensional responses was collected around 511 keV while the system was rotated in steps through 180 degrees. A non-negative, linear least-squares algorithm was then employed to reconstruct a 2-dimensional image. Corrections for multiple scattering in the detector, and the finite distance of source and detector are made in the reconstruction process.

Capturing Three-Dimensional Genome Organization in Individual Cells by Single-Cell Hi-C.

Science.gov (United States)

Nagano, Takashi; Wingett, Steven W; Fraser, Peter

2017-01-01

Hi-C is a powerful method to investigate genome-wide, higher-order chromatin and chromosome conformations averaged from a population of cells. To expand the potential of Hi-C for single-cell analysis, we developed single-cell Hi-C. Similar to the existing "ensemble" Hi-C method, single-cell Hi-C detects proximity-dependent ligation events between cross-linked and restriction-digested chromatin fragments in cells. A major difference between the single-cell Hi-C and ensemble Hi-C protocol is that the proximity-dependent ligation is carried out in the nucleus. This allows the isolation of individual cells in which nearly the entire Hi-C procedure has been carried out, enabling the production of a Hi-C library and data from individual cells. With this new method, we studied genome conformations and found evidence for conserved topological domain organization from cell to cell, but highly variable interdomain contacts and chromosome folding genome wide. In addition, we found that the single-cell Hi-C protocol provided cleaner results with less technical noise suggesting it could be used to improve the ensemble Hi-C technique.

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

Science.gov (United States)

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

2015-01-01

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

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

OpenAIRE

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

2018-01-01

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

A Parallel Distributed-Memory Particle Method Enables Acquisition-Rate Segmentation of Large Fluorescence Microscopy Images.

Science.gov (United States)

Afshar, Yaser; Sbalzarini, Ivo F

2016-01-01

Modern fluorescence microscopy modalities, such as light-sheet microscopy, are capable of acquiring large three-dimensional images at high data rate. This creates a bottleneck in computational processing and analysis of the acquired images, as the rate of acquisition outpaces the speed of processing. Moreover, images can be so large that they do not fit the main memory of a single computer. We address both issues by developing a distributed parallel algorithm for segmentation of large fluorescence microscopy images. The method is based on the versatile Discrete Region Competition algorithm, which has previously proven useful in microscopy image segmentation. The present distributed implementation decomposes the input image into smaller sub-images that are distributed across multiple computers. Using network communication, the computers orchestrate the collectively solving of the global segmentation problem. This not only enables segmentation of large images (we test images of up to 10(10) pixels), but also accelerates segmentation to match the time scale of image acquisition. Such acquisition-rate image segmentation is a prerequisite for the smart microscopes of the future and enables online data compression and interactive experiments.

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%.

Preliminary study of single contrast enhanced dual energy heart imaging using dual-source CT

International Nuclear Information System (INIS)

Peng Jin; Zhang Longjiang; Zhou Changsheng; Lu Guangming; Ma Yan; Gu Haifeng

2009-01-01

Objective: To evaluate the feasibility and preliminary applications of single contrast enhanced dual energy heart imaging using dual-source CT (DSCT). Methods: Thirty patients underwent dual energy heart imaging with DSCT, of which 6 cases underwent SPECT or DSA within one week. Two experienced radiologists assessed image quality of coronary arteries and iodine map of myocardium. and correlated the coronary artery stenosis with the perfusion distribution of iodine map. Results: l00% (300/300) segments reached diagnostic standards. The mean score of image for all patients was 4.68±0.57. Mural coronary artery was present in 10 segments in S cases, atherosclerotic plaques in 32 segments in 12 cases, of which 20 segments having ≥50% stenosis, 12 segments ≤50% stenosis; dual energy CT coronary angiography was consistent with the DSA in 3 patients. 37 segmental perfusion abnormalities on iodine map were found in 15 cases, including 28 coronary blood supply segment narrow segment and 9 no coronary stenosis (including three negative segments in SPECD. Conclusion: Single contrast enhanced dual energy heart imaging can provide good coronary artery and myocardium perfusion images in the patients with appropriate heart rate, which has a potential to be used in the clinic and further studies are needed. (authors)

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.

Inferring segmented dense motion layers using 5D tensor voting.

Science.gov (United States)

Min, Changki; Medioni, Gérard

2008-09-01

We present a novel local spatiotemporal approach to produce motion segmentation and dense temporal trajectories from an image sequence. A common representation of image sequences is a 3D spatiotemporal volume, (x,y,t), and its corresponding mathematical formalism is the fiber bundle. However, directly enforcing the spatiotemporal smoothness constraint is difficult in the fiber bundle representation. Thus, we convert the representation into a new 5D space (x,y,t,vx,vy) with an additional velocity domain, where each moving object produces a separate 3D smooth layer. The smoothness constraint is now enforced by extracting 3D layers using the tensor voting framework in a single step that solves both correspondence and segmentation simultaneously. Motion segmentation is achieved by identifying those layers, and the dense temporal trajectories are obtained by converting the layers back into the fiber bundle representation. We proceed to address three applications (tracking, mosaic, and 3D reconstruction) that are hard to solve from the video stream directly because of the segmentation and dense matching steps, but become straightforward with our framework. The approach does not make restrictive assumptions about the observed scene or camera motion and is therefore generally applicable. We present results on a number of data sets.

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...

Marker-controlled watershed for lymphoma segmentation in sequential CT images

International Nuclear Information System (INIS)

Yan Jiayong; Zhao Binsheng; Wang, Liang; Zelenetz, Andrew; Schwartz, Lawrence H.

2006-01-01

Segmentation of lymphoma containing lymph nodes is a difficult task because of multiple variables associated with the tumor's location, intensity distribution, and contrast to its surrounding tissues. In this paper, we present a reliable and practical marker-controlled watershed algorithm for semi-automated segmentation of lymphoma in sequential CT images. Robust determination of internal and external markers is the key to successful use of the marker-controlled watershed transform in the segmentation of lymphoma and is the focus of this work. The external marker in our algorithm is the circle enclosing the lymphoma in a single slice. The internal marker, however, is determined automatically by combining techniques including Canny edge detection, thresholding, morphological operation, and distance map estimation. To obtain tumor volume, the segmented lymphoma in the current slice needs to be propagated to the adjacent slice to help determine the external and internal markers for delineation of the lymphoma in that slice. The algorithm was applied to 29 lymphomas (size range, 9-53 mm in diameter; mean, 23 mm) in nine patients. A blinded radiologist manually delineated all lymphomas on all slices. The manual result served as the ''gold standard'' for comparison. Several quantitative methods were applied to objectively evaluate the performance of the segmentation algorithm. The algorithm received a mean overlap, overestimation, and underestimation ratios of 83.2%, 13.5%, and 5.5%, respectively. The mean average boundary distance and Hausdorff boundary distance were 0.7 and 3.7 mm. Preliminary results have shown the potential of this computer algorithm to allow reliable segmentation and quantification of lymphomas on sequential CT images

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

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.

A multi-atlas based method for automated anatomical rat brain MRI segmentation and extraction of PET activity.

Science.gov (United States)

Lancelot, Sophie; Roche, Roxane; Slimen, Afifa; Bouillot, Caroline; Levigoureux, Elise; Langlois, Jean-Baptiste; Zimmer, Luc; Costes, Nicolas

2014-01-01

Preclinical in vivo imaging requires precise and reproducible delineation of brain structures. Manual segmentation is time consuming and operator dependent. Automated segmentation as usually performed via single atlas registration fails to account for anatomo-physiological variability. We present, evaluate, and make available a multi-atlas approach for automatically segmenting rat brain MRI and extracting PET activies. High-resolution 7T 2DT2 MR images of 12 Sprague-Dawley rat brains were manually segmented into 27-VOI label volumes using detailed protocols. Automated methods were developed with 7/12 atlas datasets, i.e. the MRIs and their associated label volumes. MRIs were registered to a common space, where an MRI template and a maximum probability atlas were created. Three automated methods were tested: 1/registering individual MRIs to the template, and using a single atlas (SA), 2/using the maximum probability atlas (MP), and 3/registering the MRIs from the multi-atlas dataset to an individual MRI, propagating the label volumes and fusing them in individual MRI space (propagation & fusion, PF). Evaluation was performed on the five remaining rats which additionally underwent [18F]FDG PET. Automated and manual segmentations were compared for morphometric performance (assessed by comparing volume bias and Dice overlap index) and functional performance (evaluated by comparing extracted PET measures). Only the SA method showed volume bias. Dice indices were significantly different between methods (PF>MP>SA). PET regional measures were more accurate with multi-atlas methods than with SA method. Multi-atlas methods outperform SA for automated anatomical brain segmentation and PET measure's extraction. They perform comparably to manual segmentation for FDG-PET quantification. Multi-atlas methods are suitable for rapid reproducible VOI analyses.

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

The Segmentation of Point Clouds with K-Means and ANN (artifical Neural Network)

Science.gov (United States)

Kuçak, R. A.; Özdemir, E.; Erol, S.

2017-05-01

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

THE SEGMENTATION OF POINT CLOUDS WITH K-MEANS AND ANN (ARTIFICAL NEURAL NETWORK

Directory of Open Access Journals (Sweden)

R. A. Kuçak

2017-05-01

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

Buildings and Terrain of Urban Area Point Cloud Segmentation based on PCL

International Nuclear Information System (INIS)

Liu, Ying; Zhong, Ruofei

2014-01-01

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

Determining the number of clusters for nuclei segmentation in breast cancer image

Science.gov (United States)

Fatichah, Chastine; Navastara, Dini Adni; Suciati, Nanik; Nuraini, Lubna

2017-02-01

Clustering is commonly technique for image segmentation, however determining an appropriate number of clusters is still challenging. Due to nuclei variation of size and shape in breast cancer image, an automatic determining number of clusters for segmenting the nuclei breast cancer is proposed. The phase of nuclei segmentation in breast cancer image are nuclei detection, touched nuclei detection, and touched nuclei separation. We use the Gram-Schmidt for nuclei cell detection, the geometry feature for touched nuclei detection, and combining of watershed and spatial k-Means clustering for separating the touched nuclei in breast cancer image. The spatial k-Means clustering is employed for separating the touched nuclei, however automatically determine the number of clusters is difficult due to the variation of size and shape of single cell breast cancer. To overcome this problem, first we apply watershed algorithm to separate the touched nuclei and then we calculate the distance among centroids in order to solve the over-segmentation. We merge two centroids that have the distance below threshold. And the new of number centroid as input to segment the nuclei cell using spatial k- Means algorithm. Experiment show that, the proposed scheme can improve the accuracy of nuclei cell counting.