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Sample records for anatomy segmentation algorithm

  1. Anatomy-aware measurement of segmentation accuracy

    Science.gov (United States)

    Tizhoosh, H. R.; Othman, A. A.

    2016-03-01

    Quantifying the accuracy of segmentation and manual delineation of organs, tissue types and tumors in medical images is a necessary measurement that suffers from multiple problems. One major shortcoming of all accuracy measures is that they neglect the anatomical significance or relevance of different zones within a given segment. Hence, existing accuracy metrics measure the overlap of a given segment with a ground-truth without any anatomical discrimination inside the segment. For instance, if we understand the rectal wall or urethral sphincter as anatomical zones, then current accuracy measures ignore their significance when they are applied to assess the quality of the prostate gland segments. In this paper, we propose an anatomy-aware measurement scheme for segmentation accuracy of medical images. The idea is to create a "master gold" based on a consensus shape containing not just the outline of the segment but also the outlines of the internal zones if existent or relevant. To apply this new approach to accuracy measurement, we introduce the anatomy-aware extensions of both Dice coefficient and Jaccard index and investigate their effect using 500 synthetic prostate ultrasound images with 20 different segments for each image. We show that through anatomy-sensitive calculation of segmentation accuracy, namely by considering relevant anatomical zones, not only the measurement of individual users can change but also the ranking of users' segmentation skills may require reordering.

  2. Fusion of motion segmentation algorithms

    OpenAIRE

    Ellis, Anna-Louise

    2008-01-01

    Many algorithms have been developed to achieve motion segmentation for video surveillance. The algorithms produce varying performances under the infinite amount of changing conditions. It has been recognised that individually these algorithms have useful properties. Fusing the statistical result of these algorithms is investigated, with robust motion segmentation in mind.

  3. Enhanced Segment Compression Steganographic Algorithm

    Directory of Open Access Journals (Sweden)

    STRATULAT, M.

    2013-08-01

    Full Text Available Steganography is the science and art of concealing messages using techniques that allow only the sender and receiver to know of the message?s existence and be able to decipher it. In this article, we would like to present a new steganographic technique for concealing digital images: the Enhanced Segment Compression Steganographic Algorithm (ESCSA. We start by mentioning several desired properties that we have taken into consideration for our algorithm. Next, we define some quality metrics with which we can measure how well / to what extent those properties are achieved. A detailed presentation of the component parts of the algorithm follows, accompanied by quantitative analyses of parameters of interest. Finally, we discuss the strengths and weaknesses of our algorithm. In addition, we make a few suggestions regarding possible further refinements of the ESCSA.

  4. The Watershed Algorithm for Image Segmentation

    Institute of Scientific and Technical Information of China (English)

    OU Yan; LIN Nan

    2007-01-01

    This article introduced the watershed algorithm for the segmentation, illustrated the segmation process by implementing this algorithm. By comparing with another three related algorithm, this article revealed both the advantages and drawbacks of the watershed algorithm.

  5. Novel Facial Features Segmentation Algorithm

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    An efficient algorithm for facial features extractions is proposed. The facial features we segment are the two eyes, nose and mouth. The algorithm is based on an improved Gabor wavelets edge detector, morphological approach to detect the face region and facial features regions, and an improved T-shape face mask to locate the extract location of facial features. The experimental results show that the proposed method is robust against facial expression, illumination, and can be also effective if the person wearing glasses, and so on.

  6. Speech Segmentation Algorithm Based On Fuzzy Memberships

    OpenAIRE

    Luis D. Huerta; Jose Antonio Huesca; Julio C. Contreras

    2010-01-01

    In this work, an automatic speech segmentation algorithm with text independency was implemented. In the algorithm, the use of fuzzy memberships on each characteristic in different speech sub-bands is proposed. Thus, the segmentation is performed a greater detail. Additionally, we tested with various speech signal frequencies and labeling, and we could observe how they affect the performance of the segmentation process in phonemes. The speech segmentation algorithm used is described. During th...

  7. An algorithm for segmenting range imagery

    Energy Technology Data Exchange (ETDEWEB)

    Roberts, R.S.

    1997-03-01

    This report describes the technical accomplishments of the FY96 Cross Cutting and Advanced Technology (CC&AT) project at Los Alamos National Laboratory. The project focused on developing algorithms for segmenting range images. The image segmentation algorithm developed during the project is described here. In addition to segmenting range images, the algorithm can fuse multiple range images thereby providing true 3D scene models. The algorithm has been incorporated into the Rapid World Modelling System at Sandia National Laboratory.

  8. Image Series Segmentation and Improved MC Algorithm

    Institute of Scientific and Technical Information of China (English)

    WAN Wei-bing; SHI Peng-fei

    2008-01-01

    A semiautomatic segmentation method based on active contour is proposed for computed tomog-raphy (CT) image series. First, to get initial contour, one image slice was segmented exactly by C-V method based on Mumford-Shah model. Next, the computer will segment the nearby slice automatically using the snake model one by one. During segmenting of image slices, former slice boundary, as next slice initial con-tour, may cross over next slice real boundary and never return to right position. To avoid contour skipping over, the distance variance between two slices is evaluated by an threshold, which decides whether to initiate again. Moreover, a new improved marching cubes (MC) algorithm based on 2D images series segmentation boundary is given for 3D image reconstruction. Compared with the standard method, the proposed algorithm reduces detecting time and needs less storing memory. The effectiveness and capabilities of the algorithm were illustrated by experimental results.

  9. Interactive segmentation techniques algorithms and performance evaluation

    CERN Document Server

    He, Jia; Kuo, C-C Jay

    2013-01-01

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

  10. Heart region segmentation from low-dose CT scans: an anatomy based approach

    Science.gov (United States)

    Reeves, Anthony P.; Biancardi, Alberto M.; Yankelevitz, David F.; Cham, Matthew D.; Henschke, Claudia I.

    2012-02-01

    Cardiovascular disease is a leading cause of death in developed countries. The concurrent detection of heart diseases during low-dose whole-lung CT scans (LDCT), typically performed as part of a screening protocol, hinges on the accurate quantification of coronary calcification. The creation of fully automated methods is ideal as complete manual evaluation is imprecise, operator dependent, time consuming and thus costly. The technical challenges posed by LDCT scans in this context are mainly twofold. First, there is a high level image noise arising from the low radiation dose technique. Additionally, there is a variable amount of cardiac motion blurring due to the lack of electrocardiographic gating and the fact that heart rates differ between human subjects. As a consequence, the reliable segmentation of the heart, the first stage toward the implementation of morphologic heart abnormality detection, is also quite challenging. An automated computer method based on a sequential labeling of major organs and determination of anatomical landmarks has been evaluated on a public database of LDCT images. The novel algorithm builds from a robust segmentation of the bones and airways and embodies a stepwise refinement starting at the top of the lungs where image noise is at its lowest and where the carina provides a good calibration landmark. The segmentation is completed at the inferior wall of the heart where extensive image noise is accommodated. This method is based on the geometry of human anatomy and does not involve training through manual markings. Using visual inspection by an expert reader as a gold standard, the algorithm achieved successful heart and major vessel segmentation in 42 of 45 low-dose CT images. In the 3 remaining cases, the cardiac base was over segmented due to incorrect hemidiaphragm localization.

  11. Uniform wire segmentation algorithm of distributed interconnects

    Institute of Scientific and Technical Information of China (English)

    Yin Guoli; Lin Zhenghui

    2007-01-01

    A uniform wire segmentation algorithm for performance optimization of distributed RLC interconnects was proposed in this paper. The optimal wire length for identical segments and buffer size for buffer insertion are obtained through computation and derivation, based on a 2-pole approximation model of distributed RLC interconnect. For typical inductance value and long wires under 180nm technology, experiments show that the uniform wire segmentation technique proposed in the paper can reduce delay by about 27% ~ 56% , while requires 34%~69% less total buffer usage and thus 29% to 58% less power consumption. It is suitable for long RLC interconnect performance optimization.

  12. AN IMPROVED CLUSTERING ALGORITHM FOR CUSTOMER SEGMENTATION

    Directory of Open Access Journals (Sweden)

    PRABHA DHANDAYUDAM

    2012-02-01

    Full Text Available Customer Segmentation is the process of grouping the customers based on their purchase habit. Data mining is useful in finding knowledge from huge amounts of data. The clustering techniques in data mining can be used for the customer segmentation process so that it clusters the customers in such a way that the customers in one group behave similar when compared to the customers in the other group based on their transaction details. The Recency (R, Frequency (F and Monetary (M are the important attributes that determine the purchase behavior of the customer. In this, we have provided an improved clustering algorithm for segmenting customers using RFM values and compared the performance against the traditional techniques like K-means, single link and complete link.

  13. Linac design algorithm with symmetric segments

    International Nuclear Information System (INIS)

    The cell lengths in linacs of traditional design are typically graded as a function of particle velocity. By making groups of cells and individual cells symmetric in both the CCDTL AND CCL, the cavity design as well as mechanical design and fabrication is simplified without compromising the performance. We have implemented a design algorithm in the PARMILA code in which cells and multi-cavity segments are made symmetric, significantly reducing the number of unique components. Using the symmetric algorithm, a sample linac design was generated and its performance compared with a similar one of conventional design

  14. Fusion of Image Segmentation Algorithms using Consensus Clustering

    OpenAIRE

    Ozay, Mete; Vural, Fatos T. Yarman; Kulkarni, Sanjeev R.; Poor, H. Vincent

    2015-01-01

    A new segmentation fusion method is proposed that ensembles the output of several segmentation algorithms applied on a remotely sensed image. The candidate segmentation sets are processed to achieve a consensus segmentation using a stochastic optimization algorithm based on the Filtered Stochastic BOEM (Best One Element Move) method. For this purpose, Filtered Stochastic BOEM is reformulated as a segmentation fusion problem by designing a new distance learning approach. The proposed algorithm...

  15. A Review of Retinal Vessel Segmentation Techniques and Algorithms

    OpenAIRE

    Mohd Imran Khan; Heena Shaikh; Anwar Mohd. Mansuri

    2011-01-01

    Retinal vessel segmentation algorithms are the critical components of circulatory blood vessel Analysis systems. We present a survey of vessel segmentation techniques and algorithms. We put the various vessel segmentation approaches and techniques in perspective by means of a classification of the existing research. While we have mainly targeted the segmentation of blood vessels, neurovascular structure in particular. We have divided vessel segmentation algorithms and techniques into six main...

  16. Segmentation of Medical Image using Clustering and Watershed Algorithms

    OpenAIRE

    M. C.J. Christ; R. M. S. Parvathi

    2011-01-01

    Problem statement: Segmentation plays an important role in medical imaging. Segmentation of an image is the division or separation of the image into dissimilar regions of similar attribute. In this study we proposed a methodology that integrates clustering algorithm and marker controlled watershed segmentation algorithm for medical image segmentation. The use of the conservative watershed algorithm for medical image analysis is pervasive because of its advantages, such as always being able to...

  17. A Framework for Evaluating Video Object Segmentation Algorithms

    OpenAIRE

    Drelie Gelasca, E.; Karaman, M.; Ebrahimi, T.; Sikora, T.

    2006-01-01

    Segmentation of moving objects in image sequences plays an important role in video processing and analysis. Evaluating the quality of segmentation results is necessary to allow the appropriate selection of segmentation algorithms and to tune their parameters for optimal performance. Many segmentation algorithms have been proposed along with a number of evaluation criteria. Nevertheless, no psychophysical experiments evaluating the quality of different video object segmentation results have be...

  18. Segmentation precision of abdominal anatomy for MRI-based radiotherapy

    International Nuclear Information System (INIS)

    The limited soft tissue visualization provided by computed tomography, the standard imaging modality for radiotherapy treatment planning and daily localization, has motivated studies on the use of magnetic resonance imaging (MRI) for better characterization of treatment sites, such as the prostate and head and neck. However, no studies have been conducted on MRI-based segmentation for the abdomen, a site that could greatly benefit from enhanced soft tissue targeting. We investigated the interobserver and intraobserver precision in segmentation of abdominal organs on MR images for treatment planning and localization. Manual segmentation of 8 abdominal organs was performed by 3 independent observers on MR images acquired from 14 healthy subjects. Observers repeated segmentation 4 separate times for each image set. Interobserver and intraobserver contouring precision was assessed by computing 3-dimensional overlap (Dice coefficient [DC]) and distance to agreement (Hausdorff distance [HD]) of segmented organs. The mean and standard deviation of intraobserver and interobserver DC and HD values were DCintraobserver = 0.89 ± 0.12, HDintraobserver = 3.6 mm ± 1.5, DCinterobserver = 0.89 ± 0.15, and HDinterobserver = 3.2 mm ± 1.4. Overall, metrics indicated good interobserver/intraobserver precision (mean DC > 0.7, mean HD < 4 mm). Results suggest that MRI offers good segmentation precision for abdominal sites. These findings support the utility of MRI for abdominal planning and localization, as emerging MRI technologies, techniques, and onboard imaging devices are beginning to enable MRI-based radiotherapy

  19. A new algorithm of brain volume contours segmentation

    Institute of Scientific and Technical Information of China (English)

    吴建明; 施鹏飞

    2003-01-01

    This paper explores brain CT slices segmentation technique and some related problems, including contours segmentation algorithms, edge detector, algorithm evaluation and experimental results. This article describes a method for contour-based segmentation of anatomical structures in 3D medical data sets. With this method, the user manually traces one or more 2D contours of an anatomical structure of interest on parallel planes arbitrarily cutting the data set. The experimental results showes the segmentation based on 3D brain volume and 2D CT slices. The main creative contributions in this paper are: (1) contours segmentation algorithm; (2) edge detector; (3) algorithm evaluation.

  20. A New Image Segmentation Algorithm and It’s Application in lettuce object segmentation

    Directory of Open Access Journals (Sweden)

    Xiaodong Zhang

    2012-07-01

    Full Text Available Lettuce image segmentation which based on computer image processing is the premise of non-destructive testing of lettuce quality. The traditional 2-D maximum entropy algorithm has some faults, such as low accuracy of segmentation, slow speed, and poor anti-noise ability. As a result, it leads to the problems of poor image segmentation and low efficiency. An improved 2-D maximum entropy algorithm is presented in this paper. It redistricts segmented regions and furtherly classifies the segmented image pixels with the method of the minimum fuzzy entropy, and reduces the impact of noise points, as a result the image segmentation accuracy is improved. The improved algorithm is used to lettuce object segmentation, and the experimental results show that the improved segmentation algorithm has many advantages compared with the traditional 2-D maximum entropy algorithm, such as less false interference, strong anti-noise ability, good robustness and validity.  

  1. Leaf sequencing algorithms for segmented multileaf collimation

    Energy Technology Data Exchange (ETDEWEB)

    Kamath, Srijit [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States); Sahni, Sartaj [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States); Li, Jonathan [Department of Radiation Oncology, University of Florida, Gainesville, FL (United States); Palta, Jatinder [Department of Radiation Oncology, University of Florida, Gainesville, FL (United States); Ranka, Sanjay [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States)

    2003-02-07

    The delivery of intensity-modulated radiation therapy (IMRT) with a multileaf collimator (MLC) requires the conversion of a radiation fluence map into a leaf sequence file that controls the movement of the MLC during radiation delivery. It is imperative that the fluence map delivered using the leaf sequence file is as close as possible to the fluence map generated by the dose optimization algorithm, while satisfying hardware constraints of the delivery system. Optimization of the leaf sequencing algorithm has been the subject of several recent investigations. In this work, we present a systematic study of the optimization of leaf sequencing algorithms for segmental multileaf collimator beam delivery and provide rigorous mathematical proofs of optimized leaf sequence settings in terms of monitor unit (MU) efficiency under most common leaf movement constraints that include minimum leaf separation constraint and leaf interdigitation constraint. Our analytical analysis shows that leaf sequencing based on unidirectional movement of the MLC leaves is as MU efficient as bidirectional movement of the MLC leaves.

  2. A Survey of Image Segmentation Algorithms Based On Fuzzy Clustering

    OpenAIRE

    R. Ravindraiah; K. Tejaswini

    2013-01-01

    Medical image segmentation plays a vital role in one of the most challenging fields ofengineering. Imaging modality provides detailed information about anatomy. It is also helpful in the findingof the disease and its progressive treatment. More research and work on it has enhanced more effectivenessas far as the subject is concerned. Different methods are used for medical image segmentation such asClustering methods, Thresholding method, Classifier, Region Growing, Deformable Model, Markov Ra...

  3. Video segmentation using multiple features based on EM algorithm

    Institute of Scientific and Technical Information of China (English)

    张风超; 杨杰; 刘尔琦

    2004-01-01

    Object-based video segmentation is an important issue for many multimedia applications. A video segmentation method based on EM algorithm is proposed. We consider video segmentation as an unsupervised classification problem and apply EM algorithm to obtain the maximum-likelihood estimation of the Gaussian model parameters for model-based segmentation. We simultaneously combine multiple features (motion, color) within a maximum likelihood framework to obtain accurate segment results. We also use the temporal consistency among video frames to improve the speed of EM algorithm. Experimental results on typical MPEG-4 sequences and real scene sequences show that our method has an attractive accuracy and robustness.

  4. Illumination Compensation Algorithm for Unevenly Lighted Document Segmentation

    Directory of Open Access Journals (Sweden)

    Ju Zhiyong

    2013-07-01

    Full Text Available For the problem of segmenting the unevenly lighted document image, this paper proposes an illumination compensation segmentation algorithm which can effectively segment the unevenly lighted document. The illumination compensation method is proposed to equivalently convert unevenly lighted document image to evenly lighted document image, then segment the evenly lighted document directly. Experimental results show that the proposed method can get the accurate evenly lighted document images so that we can segment the document accurately and it is more efficient to process unevenly lighted document  images than traditional binarization methods. The algorithm effectively overcomes the difficulty in handling uneven lighting and enhances segmentation quality considerably.

  5. 3D automatic anatomy segmentation based on iterative graph-cut-ASM

    International Nuclear Information System (INIS)

    Purpose: This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images. Methods: The AAS system, the authors are developing consists of two main parts: object recognition and object delineation. As for recognition, a hierarchical 3D scale-based multiobject method is used for the multiobject recognition task, which incorporates intensity weighted ball-scale (b-scale) information into the active shape model (ASM). For object delineation, an iterative graph-cut-ASM (IGCASM) algorithm is proposed, which effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability of the GC method. The presented IGCASM algorithm is a 3D generalization of the 2D GC-ASM method that they proposed previously in Chen et al.[Proc. SPIE, 7259, 72590C1-72590C-8 (2009)]. The proposed methods are tested on two datasets comprised of images obtained from 20 patients (10 male and 10 female) of clinical abdominal CT scans, and 11 foot magnetic resonance imaging (MRI) scans. The test is for four organs (liver, left and right kidneys, and spleen) segmentation, five foot bones (calcaneus, tibia, cuboid, talus, and navicular). The recognition and delineation accuracies were evaluated separately. The recognition accuracy was evaluated in terms of translation, rotation, and scale (size) error. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF, FPVF). The efficiency of the delineation method was also evaluated on an Intel Pentium IV PC with a 3.4 GHZ CPU machine. Results: The recognition accuracies in terms of translation, rotation, and scale error over all organs are about 8 mm, 10 deg. and 0.03, and over all foot bones are about 3.5709 mm, 0.35 deg. and 0.025, respectively. The accuracy of delineation over all organs for all subjects as expressed in TPVF and FPVF is 93.01% and 0.22%, and

  6. 3D automatic anatomy segmentation based on iterative graph-cut-ASM

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Xinjian; Bagci, Ulas [Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Building 10 Room 1C515, Bethesda, Maryland 20892-1182 and Life Sciences Research Center, School of Life Sciences and Technology, Xidian University, Xi' an 710071 (China); Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Building 10 Room 1C515, Bethesda, Maryland 20892-1182 (United States)

    2011-08-15

    Purpose: This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images. Methods: The AAS system, the authors are developing consists of two main parts: object recognition and object delineation. As for recognition, a hierarchical 3D scale-based multiobject method is used for the multiobject recognition task, which incorporates intensity weighted ball-scale (b-scale) information into the active shape model (ASM). For object delineation, an iterative graph-cut-ASM (IGCASM) algorithm is proposed, which effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability of the GC method. The presented IGCASM algorithm is a 3D generalization of the 2D GC-ASM method that they proposed previously in Chen et al.[Proc. SPIE, 7259, 72590C1-72590C-8 (2009)]. The proposed methods are tested on two datasets comprised of images obtained from 20 patients (10 male and 10 female) of clinical abdominal CT scans, and 11 foot magnetic resonance imaging (MRI) scans. The test is for four organs (liver, left and right kidneys, and spleen) segmentation, five foot bones (calcaneus, tibia, cuboid, talus, and navicular). The recognition and delineation accuracies were evaluated separately. The recognition accuracy was evaluated in terms of translation, rotation, and scale (size) error. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF, FPVF). The efficiency of the delineation method was also evaluated on an Intel Pentium IV PC with a 3.4 GHZ CPU machine. Results: The recognition accuracies in terms of translation, rotation, and scale error over all organs are about 8 mm, 10 deg. and 0.03, and over all foot bones are about 3.5709 mm, 0.35 deg. and 0.025, respectively. The accuracy of delineation over all organs for all subjects as expressed in TPVF and FPVF is 93.01% and 0.22%, and

  7. A Hierarchical Algorithm for Multiphase Texture Image Segmentation

    OpenAIRE

    Yalin Zheng; Ke Chen

    2012-01-01

    Image segmentation is a fundamental task for many computer vision and image processing applications. There exist many useful and reliable models for two-phase segmentation. However, the multiphase segmentation is a more challenging problem than two phase segmentation, mainly due to strong dependence on initialization of solutions. In this paper we propose a reliable hierarchical algorithm for multiphase texture image segmentation by making full use of two-phase texture models in a fuzzy membe...

  8. CT segmentation of dental shapes by anatomy-driven reformation imaging and B-spline modelling.

    Science.gov (United States)

    Barone, S; Paoli, A; Razionale, A V

    2016-06-01

    Dedicated imaging methods are among the most important tools of modern computer-aided medical applications. In the last few years, cone beam computed tomography (CBCT) has gained popularity in digital dentistry for 3D imaging of jawbones and teeth. However, the anatomy of a maxillofacial region complicates the assessment of tooth geometry and anatomical location when using standard orthogonal views of the CT data set. In particular, a tooth is defined by a sub-region, which cannot be easily separated from surrounding tissues by only considering pixel grey-intensity values. For this reason, an image enhancement is usually necessary in order to properly segment tooth geometries. In this paper, an anatomy-driven methodology to reconstruct individual 3D tooth anatomies by processing CBCT data is presented. The main concept is to generate a small set of multi-planar reformation images along significant views for each target tooth, driven by the individual anatomical geometry of a specific patient. The reformation images greatly enhance the clearness of the target tooth contours. A set of meaningful 2D tooth contours is extracted and used to automatically model the overall 3D tooth shape through a B-spline representation. The effectiveness of the methodology has been verified by comparing some anatomy-driven reconstructions of anterior and premolar teeth with those obtained by using standard tooth segmentation tools. Copyright © 2015 John Wiley & Sons, Ltd.

  9. Analysis of image thresholding segmentation algorithms based on swarm intelligence

    Science.gov (United States)

    Zhang, Yi; Lu, Kai; Gao, Yinghui; Yang, Bo

    2013-03-01

    Swarm intelligence-based image thresholding segmentation algorithms are playing an important role in the research field of image segmentation. In this paper, we briefly introduce the theories of four existing image segmentation algorithms based on swarm intelligence including fish swarm algorithm, artificial bee colony, bacteria foraging algorithm and particle swarm optimization. Then some image benchmarks are tested in order to show the differences of the segmentation accuracy, time consumption, convergence and robustness for Salt & Pepper noise and Gaussian noise of these four algorithms. Through these comparisons, this paper gives qualitative analyses for the performance variance of the four algorithms. The conclusions in this paper would give a significant guide for the actual image segmentation.

  10. 3D automatic anatomy segmentation based on iterative graph-cut-ASM

    OpenAIRE

    Chen, Xinjian; Bagci, Ulas

    2011-01-01

    Purpose: This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images.Methods: The AAS system, the authors are developing consists of two main parts: object recognition and object delineation. As for recognition, a hierarchical 3D scale-based multiobject method is used for the multiobject recognition task, which incorporates intensity weighted ball-scale (b-scale) information into the...

  11. Gaussian Kernel Based Fuzzy C-Means Clustering Algorithm for Image Segmentation

    Directory of Open Access Journals (Sweden)

    Rehna Kalam

    2016-04-01

    Full Text Available Image processing is an important research area in c omputer vision. clustering is an unsupervised study. clustering can also be used for image segmen tation. there exist so many methods for image segmentation. image segmentation plays an importan t role in image analysis.it is one of the first and the most important tasks in image analysis and computer vision. this proposed system presents a variation of fuzzy c-means algorithm tha t provides image clustering. the kernel fuzzy c-means clustering algorithm (kfcm is derived from the fuzzy c-means clustering algorithm(fcm.the kfcm algorithm that provides ima ge clustering and improves accuracy significantly compared with classical fuzzy c-means algorithm. the new algorithm is called gaussian kernel based fuzzy c-means clustering algo rithm (gkfcmthe major characteristic of gkfcm is the use of a fuzzy clustering approach ,ai ming to guarantee noise insensitiveness and image detail preservation.. the objective of the wo rk is to cluster the low intensity in homogeneity area from the noisy images, using the clustering me thod, segmenting that portion separately using content level set approach. the purpose of designin g this system is to produce better segmentation results for images corrupted by noise, so that it c an be useful in various fields like medical image analysis, such as tumor detection, study of anatomi cal structure, and treatment planning.

  12. IMPROVED RANDOMIZED ALGORITHM FOR THE EQUIVALENT 2-CATALOG SEGMENTATION PROBLEM

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    An improved randomized algorithm of the equivalent 2-catalog segmentation problem is presented. The result obtained in this paper makes some progress to answer the open problem by analyze this algorithm with performance guarantee. A 0.6378-approximation for the equivalent 2-catalog segmentation problem is obtained.

  13. Fuzzy Clustering Algorithms for Effective Medical Image Segmentation

    OpenAIRE

    Deepali Aneja; Tarun Kumar Rawat

    2013-01-01

    Medical image segmentation demands a segmentation algorithm which works against noise. The most popular algorithm used in image segmentation is Fuzzy C-Means clustering. It uses only intensity values for clustering which makes it highly sensitive to noise. The comparison of the three fundamental image segmentation methods based on fuzzy logic namely Fuzzy C-Means (FCM), Intuitionistic Fuzzy C-Means (IFCM), and Type-II Fuzzy C-Means (T2FCM) is presented in this paper. These algorithms are exe...

  14. TCP smart framing: a segmentation algorithm to reduce TCP latency

    OpenAIRE

    Mellia, Marco; Meo, Michela; Casetti, Claudio Ettore

    2005-01-01

    TCP Smart Framing, or TCP-SF for short, enables the Fast Retransmit/Recovery algorithms even when the congestion window is small. Without modifying the TCP congestion control based on the additive-increase/multiplicative-decrease paradigm, TCP-SF adopts a novel segmentation algorithm: while Classic TCP always tries to send full-sized segments, a TCP-SF source adopts a more flexible segmentation algorithm to try and always have a number of in-flight segments larger than 3 so as to enable Fast ...

  15. Research of the multimodal brain-tumor segmentation algorithm

    Science.gov (United States)

    Lu, Yisu; Chen, Wufan

    2015-12-01

    It is well-known that the number of clusters is one of the most important parameters for automatic segmentation. However, it is difficult to define owing to the high diversity in appearance of tumor tissue among different patients and the ambiguous boundaries of lesions. In this study, a nonparametric mixture of Dirichlet process (MDP) model is applied to segment the tumor images, and the MDP segmentation can be performed without the initialization of the number of clusters. A new nonparametric segmentation algorithm combined with anisotropic diffusion and a Markov random field (MRF) smooth constraint is proposed in this study. Besides the segmentation of single modal brain tumor images, we developed the algorithm to segment multimodal brain tumor images by the magnetic resonance (MR) multimodal features and obtain the active tumor and edema in the same time. The proposed algorithm is evaluated and compared with other approaches. The accuracy and computation time of our algorithm demonstrates very impressive performance.

  16. COMPARISON OF DIFFERENT SEGMENTATION ALGORITHMS FOR DERMOSCOPIC IMAGES

    Directory of Open Access Journals (Sweden)

    A.A. Haseena Thasneem

    2015-05-01

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

  17. Optimized Audio Classification and Segmentation Algorithm by Using Ensemble Methods

    OpenAIRE

    Saadia Zahid; Fawad Hussain; Muhammad Rashid; Muhammad Haroon Yousaf; Hafiz Adnan Habib

    2015-01-01

    Audio segmentation is a basis for multimedia content analysis which is the most important and widely used application nowadays. An optimized audio classification and segmentation algorithm is presented in this paper that segments a superimposed audio stream on the basis of its content into four main audio types: pure-speech, music, environment sound, and silence. An algorithm is proposed that preserves important audio content and reduces the misclassification rate without using large amount o...

  18. An Improved FCM Medical Image Segmentation Algorithm Based on MMTD

    Directory of Open Access Journals (Sweden)

    Ningning Zhou

    2014-01-01

    Full Text Available Image segmentation plays an important role in medical image processing. Fuzzy c-means (FCM is one of the popular clustering algorithms for medical image segmentation. But FCM is highly vulnerable to noise due to not considering the spatial information in image segmentation. This paper introduces medium mathematics system which is employed to process fuzzy information for image segmentation. It establishes the medium similarity measure based on the measure of medium truth degree (MMTD and uses the correlation of the pixel and its neighbors to define the medium membership function. An improved FCM medical image segmentation algorithm based on MMTD which takes some spatial features into account is proposed in this paper. The experimental results show that the proposed algorithm is more antinoise than the standard FCM, with more certainty and less fuzziness. This will lead to its practicable and effective applications in medical image segmentation.

  19. A Review of Retinal Vessel Segmentation Techniques and Algorithms

    Directory of Open Access Journals (Sweden)

    Mohd. Imran Khan

    2011-09-01

    Full Text Available Retinal vessel segmentation algorithms are the critical components of circulatory blood vessel Analysis systems. We present a survey of vessel segmentation techniques and algorithms. We put the various vessel segmentation approaches and techniques in perspective by means of a classification of the existing research. While we have mainly targeted the segmentation of blood vessels, neurovascular structure in particular. We have divided vessel segmentation algorithms and techniques into six main categories: (1 Parallel Multiscale Feature Extraction and Region Growing, (2 a hybrid filtering, (3 Ridge-Based Vessel Segmentation, (4 artificial intelligencebased approaches, (5 neural network-based approaches, and (6 miscellaneous tube-like object detection approaches. Some of these categories are further divided into subcategories.

  20. Track segment association algorithm based on statistical binary thresholds

    Directory of Open Access Journals (Sweden)

    Qi Lin

    2015-05-01

    Full Text Available The classical Track Segment Association (TSA algorithm suffers from low accuracy and is impractical to use in concentrated targets, branching, and cross-tracking environment. Thus, a new statistical binary track segment association algorithm is proposed. The new algorithm is more appropriate as it increases the sample size for the χ2 distribution threshold detection. Simulation results show that in air cross tracking and for ballistic targets, the global correct association rate and the average correct association rate of the proposed algorithm are remarkably improved, which proves the good performance of the proposed algorithm.

  1. Pixel Intensity Clustering Algorithm for Multilevel Image Segmentation

    Directory of Open Access Journals (Sweden)

    Oludayo O. Olugbara

    2015-01-01

    Full Text Available Image segmentation is an important problem that has received significant attention in the literature. Over the last few decades, a lot of algorithms were developed to solve image segmentation problem; prominent amongst these are the thresholding algorithms. However, the computational time complexity of thresholding exponentially increases with increasing number of desired thresholds. A wealth of alternative algorithms, notably those based on particle swarm optimization and evolutionary metaheuristics, were proposed to tackle the intrinsic challenges of thresholding. In codicil, clustering based algorithms were developed as multidimensional extensions of thresholding. While these algorithms have demonstrated successful results for fewer thresholds, their computational costs for a large number of thresholds are still a limiting factor. We propose a new clustering algorithm based on linear partitioning of the pixel intensity set and between-cluster variance criterion function for multilevel image segmentation. The results of testing the proposed algorithm on real images from Berkeley Segmentation Dataset and Benchmark show that the algorithm is comparable with state-of-the-art multilevel segmentation algorithms and consistently produces high quality results. The attractive properties of the algorithm are its simplicity, generalization to a large number of clusters, and computational cost effectiveness.

  2. Automated lung segmentation algorithm for CAD system of thoracic CT

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Objective: To design and test the accuracy and efficiency of our lung segmentation algorithm on thoracic CT image in computer-aided diagnostic (CAD) system, especially on the segmentation between left and right lungs. Methods: We put forward the base frame of our lung segmentation firstly. Then, using optimal thresholding and mathematical morphologic methods, we acquired the rough image of lung segmentation. Finally, we presented a fast self-fit segmentation refinement algorithm, adapting to the unsuccessful left-right lung segmentation of thredsholding. Then our algorithm was used to CT scan images of 30 patients and the results were compared with those made by experts. Results: Experiments on clinical 2-D pulmonary images showed the results of our algorithm were very close to the expert's manual outlines, and it was very effective for the separation of left and right lungs with a successful segmentation ratio 94.8%. Conclusion: It is a practicable fast lung segmentation algorithm for CAD system on thoracic CT image.

  3. An Improved Image Segmentation Based on Mean Shift Algorithm

    Institute of Scientific and Technical Information of China (English)

    CHENHanfeng; QIFeihu

    2003-01-01

    Gray image segmentation is to segment an image into some homogeneous regions and only one gray level is defined for each region as the result. These grayl evels are called major gray levels. Mean shift algorithm(MSA) has shown its efficiency in image segmentation. An improved gray image segmentation method based on MSAis proposed in this paper since usual image segmentation methods based on MSA often fail in segmenting imageswith weak edges. Corrupted block and its J-value are defined firstly in the proposed method. Then, J-matrix gotten from corrupted blocks are proposed to measure whether weak edges appear in the image. According to the J-matrix, major gray levels gotten with usual segmen-tation methods based on MSA are augmented and corre-sponding allocation windows are modified to detect weak edges. Experimental results demonstrate the effectiveness of the proposed method in gray image segmentation.

  4. Image segmentation by using the localized subspace iteration algorithm

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    An image segmentation algorithm called"segmentation based on the localized subspace iterations"(SLSI)is proposed in this paper.The basic idea is to combine the strategies in Ncut algorithm by Shi and Malik in 2000 and the LSI by E,Li and Lu in 2007.The LSI is applied to solve an eigenvalue problem associated with the affinity matrix of an image,which makes the overall algorithm linearly scaled.The choices of the partition number,the supports and weight functions in SLSI are discussed.Numerical experiments for real images show the applicability of the algorithm.

  5. Joint graph cut and relative fuzzy connectedness image segmentation algorithm

    OpenAIRE

    Ciesielski, Krzysztof Chris; Miranda, P.A.V.; A. X. Falcão; Udupa, Jayaram K.

    2013-01-01

    We introduce an image segmentation algorithm, called GCsummax, which combines, in novel manner, the strengths of two popular algorithms: Relative Fuzzy Connectedness (RFC) and (standard) Graph Cut (GC). We show, both theoretically and experimentally, that GCsummax preserves robustness of RFC with respect to the seed choice (thus, avoiding “shrinking problem” of GC), while keeping GC’s stronger control over the problem of “leaking though poorly defined boundary segments.” The analysis of GCsum...

  6. Segmentation algorithm for non-stationary compound Poisson processes

    OpenAIRE

    Bence Toth; Fabrizio Lillo; J Doyne Farmer

    2010-01-01

    We introduce an algorithm for the segmentation of a class of regime switching processes. The segmentation algorithm is a non parametric statistical method able to identify the regimes (patches) of the time series. The process is composed of consecutive patches of variable length, each patch being described by a stationary compound Poisson process, i.e. a Poisson process where each count is associated to a fluctuating signal. The parameters of the process are different in each patch and theref...

  7. A CT Image Segmentation Algorithm Based on Level Set Method

    Institute of Scientific and Technical Information of China (English)

    QU Jing-yi; SHI Hao-shan

    2006-01-01

    Level Set methods are robust and efficient numerical tools for resolving curve evolution in image segmentation. This paper proposes a new image segmentation algorithm based on Mumford-Shah module. The method is used to CT images and the experiment results demonstrate its efficiency and veracity.

  8. Color Image Segmentation via Improved K-Means Algorithm

    Directory of Open Access Journals (Sweden)

    Ajay Kumar

    2016-03-01

    Full Text Available Data clustering techniques are often used to segment the real world images. Unsupervised image segmentation algorithms that are based on the clustering suffer from random initialization. There is a need for efficient and effective image segmentation algorithm, which can be used in the computer vision, object recognition, image recognition, or compression. To address these problems, the authors present a density-based initialization scheme to segment the color images. In the kernel density based clustering technique, the data sample is mapped to a high-dimensional space for the effective data classification. The Gaussian kernel is used for the density estimation and for the mapping of sample image into a high- dimensional color space. The proposed initialization scheme for the k-means clustering algorithm can homogenously segment an image into the regions of interest with the capability of avoiding the dead centre and the trapped centre by local minima phenomena. The performance of the experimental result indicates that the proposed approach is more effective, compared to the other existing clustering-based image segmentation algorithms. In the proposed approach, the Berkeley image database has been used for the comparison analysis with the recent clustering-based image segmentation algorithms like k-means++, k-medoids and k-mode.

  9. Optimized Audio Classification and Segmentation Algorithm by Using Ensemble Methods

    Directory of Open Access Journals (Sweden)

    Saadia Zahid

    2015-01-01

    Full Text Available Audio segmentation is a basis for multimedia content analysis which is the most important and widely used application nowadays. An optimized audio classification and segmentation algorithm is presented in this paper that segments a superimposed audio stream on the basis of its content into four main audio types: pure-speech, music, environment sound, and silence. An algorithm is proposed that preserves important audio content and reduces the misclassification rate without using large amount of training data, which handles noise and is suitable for use for real-time applications. Noise in an audio stream is segmented out as environment sound. A hybrid classification approach is used, bagged support vector machines (SVMs with artificial neural networks (ANNs. Audio stream is classified, firstly, into speech and nonspeech segment by using bagged support vector machines; nonspeech segment is further classified into music and environment sound by using artificial neural networks and lastly, speech segment is classified into silence and pure-speech segments on the basis of rule-based classifier. Minimum data is used for training classifier; ensemble methods are used for minimizing misclassification rate and approximately 98% accurate segments are obtained. A fast and efficient algorithm is designed that can be used with real-time multimedia applications.

  10. CT examination of segmental liver transplants from living donors. Anatomy and pathological findings

    International Nuclear Information System (INIS)

    A lack of suitable pediatric donors and significantly better results than conventional transplantation have contributed to the steady increase in the number of segmental liver transplants from living donors throughout the world. This article describes the diagnostic impact of axial CT scans following transplantation in a retrospective evaluation of 18 CT examinations of 10 children with an average age of two years. Both spiral and conventional CT scans permit precise visualization of the postoperative anatomy of the upper abdomen that is more distinct than the images provided by ultrasonic scans. Thus, CT scans better facilitate detection of pathological findings. In 60% of the patients (67% of the examinations), the CT scan permitted a definite diagnosis; in the remaining cases, no morphological correlate to the clinical and laboratory findings was detected. In addition to traditional ultrasonic scanning, computed tomography represents a further noninvasive imaging technique for postoperative diagnostics following segmental liver transplants from living donors. (orig.)

  11. Segmentation algorithm for non-stationary compound Poisson processes

    CERN Document Server

    Toth, Bence; Farmer, J Doyne

    2010-01-01

    We introduce an algorithm for the segmentation of a class of regime switching processes. The segmentation algorithm is a non parametric statistical method able to identify the regimes (patches) of the time series. The process is composed of consecutive patches of variable length, each patch being described by a stationary compound Poisson process, i.e. a Poisson process where each count is associated to a fluctuating signal. The parameters of the process are different in each patch and therefore the time series is non stationary. Our method is a generalization of the algorithm introduced by Bernaola-Galvan, et al., Phys. Rev. Lett., 87, 168105 (2001). We show that the new algorithm outperforms the original one for regime switching compound Poisson processes. As an application we use the algorithm to segment the time series of the inventory of market members of the London Stock Exchange and we observe that our method finds almost three times more patches than the original one.

  12. A Multi-Stage Algorithm for Enhanced XRay Image Segmentation

    Directory of Open Access Journals (Sweden)

    ADITYA A. TIRODKAR

    2011-09-01

    Full Text Available With the ever increasing usage of empirical data collected from X-Ray and other Digital Imaging techniques, it has become imperative that this data be subjected to computer algorithms for speedy and more accurate diagnosis. Segmentation is one of the key techniques that are employed during the pre-processing stages of these algorithms for separating those details from the images that are required for analysis. There are currently a number of widespread techniques for segmentation, in use. Our proposed algorithm is a quick and morequalitatively efficient technique for segmentation that is optimized for X-Ray images. It applies Otsu’s algorithm to provide thresholding values that can be used for contrasting and binarizing the images. Also, an edge detection technique has been applied to better evince observations, allowing more fruitful extraction of information and the algorithm has itself been tested on a set of 40 images.

  13. Multi-agent Remote Sensing Image Segmentation Algorithm

    Directory of Open Access Journals (Sweden)

    Jing Chen

    2014-05-01

    Full Text Available Due to fractal network evolution algorithm (FNEA in the treatment of the high spatial resolution remote sensing image (HSRI using a parallel global control strategies which limited when the objects in each cycle by traversal of and not good use the continuity of homogenous area on the space and lead to problems such as bad image segmentation, therefore puts forward the remote sensing image segmentation algorithm based on multi-agent. The algorithm in the merger guidelines, combining the image spectral and shape information, and by using region merging process of multi-agent parallel control integral, its global merger control strategy can ensure algorithm has the advantages of parallel computing and fully considering the regional homogeneity, and continuity. Finally simulation experiment was performed with FNEA algorithms, experimental results show that the proposed algorithm is better than FNEA algorithm in dividing the overall effect, has a good stability

  14. An enhanced fast scanning algorithm for image segmentation

    Science.gov (United States)

    Ismael, Ahmed Naser; Yusof, Yuhanis binti

    2015-12-01

    Segmentation is an essential and important process that separates an image into regions that have similar characteristics or features. This will transform the image for a better image analysis and evaluation. An important benefit of segmentation is the identification of region of interest in a particular image. Various algorithms have been proposed for image segmentation and this includes the Fast Scanning algorithm which has been employed on food, sport and medical images. It scans all pixels in the image and cluster each pixel according to the upper and left neighbor pixels. The clustering process in Fast Scanning algorithm is performed by merging pixels with similar neighbor based on an identified threshold. Such an approach will lead to a weak reliability and shape matching of the produced segments. This paper proposes an adaptive threshold function to be used in the clustering process of the Fast Scanning algorithm. This function used the gray'value in the image's pixels and variance Also, the level of the image that is more the threshold are converted into intensity values between 0 and 1, and other values are converted into intensity values zero. The proposed enhanced Fast Scanning algorithm is realized on images of the public and private transportation in Iraq. Evaluation is later made by comparing the produced images of proposed algorithm and the standard Fast Scanning algorithm. The results showed that proposed algorithm is faster in terms the time from standard fast scanning.

  15. Autonomous Image Segmentation using Density-Adaptive Dendritic Cell Algorithm

    Directory of Open Access Journals (Sweden)

    Vishwambhar Pathak

    2013-08-01

    Full Text Available Contemporary image processing based applications like medical diagnosis automation and analysis of satellite imagery include autonomous image segmentation as inevitable facility. The research done shows the efficiency of an adaptive evolutionary algorithm based on immune system dynamics for the task of autonomous image segmentation. The recognition dynamics of immune-kernels modeled with infinite Gaussian mixture models exhibit the capability to automatically determine appropriate number of segments in presence of noise. In addition, the model using representative density-kernel-parameters processes the information with much reduced space requirements. Experiments conducted with synthetic images as well as real images recorded assured convergence and optimal autonomous model estimation. The segmentation results tested in terms of PBM-index values have been found comparable to those of the Fuzzy C-Means (FCM for the same number of segments as generated by our algorithm.

  16. A Novel Plant Root Foraging Algorithm for Image Segmentation Problems

    Directory of Open Access Journals (Sweden)

    Lianbo Ma

    2014-01-01

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

  17. MEDICAL IMAGE SEGMENTATION BASED ON A MODIFIED LEVEL SET ALGORITHM

    Institute of Scientific and Technical Information of China (English)

    Yang Yong; Lin Pan; Zheng Chongxun; Gu Jianwen

    2005-01-01

    Objective To present a novel modified level set algorithm for medical image segmentation. Methods The algorithm is developed by substituting the speed function of level set algorithm with the region and gradient information of the image instead of the conventional gradient information. This new algorithm has been tested by a series of different modality medical images. Results We present various examples and also evaluate and compare the performance of our method with the classical level set method on weak boundaries and noisy images. Conclusion Experimental results show the proposed algorithm is effective and robust.

  18. Segmenting trajectories: A framework and algorithms using spatiotemporal criteria

    Directory of Open Access Journals (Sweden)

    Maike Buchin

    2011-12-01

    Full Text Available In this paper we address the problem of segmenting a trajectory based on spatiotemporal criteria. We require that each segment is homogeneous in the sense that a set of spatiotemporal criteria are fulfilled. We define different such criteria, including location, heading, speed, velocity, curvature, sinuosity, curviness, and shape. We present an algorithmic framework that allows us to segment any trajectory into a minimum number of segments under any of these criteria, or any combination of these criteria. In this framework, a segmentation can generally be computed in O(n log n time, where n is the number of edges of the trajectory to be segmented. We also discuss the robustness of our approach.

  19. AN IMPROVED FUZZY CLUSTERING ALGORITHM FOR MICROARRAY IMAGE SPOTS SEGMENTATION

    Directory of Open Access Journals (Sweden)

    V.G. Biju

    2015-11-01

    Full Text Available An automatic cDNA microarray image processing using an improved fuzzy clustering algorithm is presented in this paper. The spot segmentation algorithm proposed uses the gridding technique developed by the authors earlier, for finding the co-ordinates of each spot in an image. Automatic cropping of spots from microarray image is done using these co-ordinates. The present paper proposes an improved fuzzy clustering algorithm Possibility fuzzy local information c means (PFLICM to segment the spot foreground (FG from background (BG. The PFLICM improves fuzzy local information c means (FLICM algorithm by incorporating typicality of a pixel along with gray level information and local spatial information. The performance of the algorithm is validated using a set of simulated cDNA microarray images added with different levels of AWGN noise. The strength of the algorithm is tested by computing the parameters such as the Segmentation matching factor (SMF, Probability of error (pe, Discrepancy distance (D and Normal mean square error (NMSE. SMF value obtained for PFLICM algorithm shows an improvement of 0.9 % and 0.7 % for high noise and low noise microarray images respectively compared to FLICM algorithm. The PFLICM algorithm is also applied on real microarray images and gene expression values are computed.

  20. Comparison of algorithms for ultrasound image segmentation without ground truth

    Science.gov (United States)

    Sikka, Karan; Deserno, Thomas M.

    2010-02-01

    Image segmentation is a pre-requisite to medical image analysis. A variety of segmentation algorithms have been proposed, and most are evaluated on a small dataset or based on classification of a single feature. The lack of a gold standard (ground truth) further adds to the discrepancy in these comparisons. This work proposes a new methodology for comparing image segmentation algorithms without ground truth by building a matrix called region-correlation matrix. Subsequently, suitable distance measures are proposed for quantitative assessment of similarity. The first measure takes into account the degree of region overlap or identical match. The second considers the degree of splitting or misclassification by using an appropriate penalty term. These measures are shown to satisfy the axioms of a quasi-metric. They are applied for a comparative analysis of synthetic segmentation maps to show their direct correlation with human intuition of similar segmentation. Since ultrasound images are difficult to segment and usually lack a ground truth, the measures are further used to compare the recently proposed spectral clustering algorithm (encoding spatial and edge information) with standard k-means over abdominal ultrasound images. Improving the parameterization and enlarging the feature space for k-means steadily increased segmentation quality to that of spectral clustering.

  1. An Efficient Character Segmentation Based on VNP Algorithm

    Directory of Open Access Journals (Sweden)

    S. Chitrakala

    2012-12-01

    Full Text Available Character segmentation is an important preprocessing stage in image processing applications such as OCR, License Plate Recognition, electronic processing of checks in banks, form processing and, label and barcode recognition. It is essential to have an efficient character segmentation technique because it affects the performance of all the processes that follow and hence, the overall system accuracy. Vertical projection profile is the most common segmentation technique. However, the segmentation results are not always correct in cases where pixels of adjacent characters fall on the same scan line and a minimum threshold is not observed in the histogram to segment the respective adjacent characters. In this study, a character segmentation technique based on Visited Neighbor Pixel (VNP Algorithm is proposed, which is an improvement to the vertical projection profile technique. VNP Algorithm performs segmentation based on the connectedness of the pixels on the scan line with that of the previously visited pixels. Therefore, a clear line of separation is found even when the threshold between two adjacent characters is not minimal. The segmentation results of the traditional vertical projection profile and the proposed method are compared with respect to a few selected fonts and the latter, with an average accuracy of approximately 94%, has shown encouraging results.

  2. FCM Clustering Algorithms for Segmentation of Brain MR Images

    Directory of Open Access Journals (Sweden)

    Yogita K. Dubey

    2016-01-01

    Full Text Available The study of brain disorders requires accurate tissue segmentation of magnetic resonance (MR brain images which is very important for detecting tumors, edema, and necrotic tissues. Segmentation of brain images, especially into three main tissue types: Cerebrospinal Fluid (CSF, Gray Matter (GM, and White Matter (WM, has important role in computer aided neurosurgery and diagnosis. Brain images mostly contain noise, intensity inhomogeneity, and weak boundaries. Therefore, accurate segmentation of brain images is still a challenging area of research. This paper presents a review of fuzzy c-means (FCM clustering algorithms for the segmentation of brain MR images. The review covers the detailed analysis of FCM based algorithms with intensity inhomogeneity correction and noise robustness. Different methods for the modification of standard fuzzy objective function with updating of membership and cluster centroid are also discussed.

  3. Modeling and segmentation of intra-cochlear anatomy in conventional CT

    Science.gov (United States)

    Noble, Jack H.; Rutherford, Robert B.; Labadie, Robert F.; Majdani, Omid; Dawant, Benoit M.

    2010-03-01

    Cochlear implant surgery is a procedure performed to treat profound hearing loss. Since the cochlea is not visible in surgery, the physician uses anatomical landmarks to estimate the pose of the cochlea. Research has indicated that implanting the electrode in a particular cavity of the cochlea, the scala tympani, results in better hearing restoration. The success of the scala tympani implantation is largely dependent on the point of entry and angle of electrode insertion. Errors can occur due to the imprecise nature of landmark-based, manual navigation as well as inter-patient variations between scala tympani and the anatomical landmarks. In this work, we use point distribution models of the intra-cochlear anatomy to study the inter-patient variations between the cochlea and the typical anatomic landmarks, and we implement an active shape model technique to automatically localize intra-cochlear anatomy in conventional CT images, where intra-cochlear structures are not visible. This fully automatic segmentation could aid the surgeon to choose the point of entry and angle of approach to maximize the likelihood of scala tympani insertion, resulting in more substantial hearing restoration.

  4. A segmentation algorithm of intracranial hemorrhage CT image

    Science.gov (United States)

    Wang, Haibo; Chen, Zhiguo; Wang, Jianzhi

    2011-10-01

    To develop a computer aided detection (CAD) system that improves diagnostic accuracy of intracranial hemorrhage on cerebral CT. A method for CT image segmentation of brain is proposed, with which, several regions that are suspicious of hemorrhage can be segmented rapidly and effectively. Extracting intracranial area algorithm is introduced firstly to extract intracranial area. Secondly, FCM is employed twice, we named it with TFCM. FCM is first employed to identify areas of intracranial hemorrhage. Finally, FCM is employed to segment the lesions. Experimental results on real medical images demonstrate the efficiency and effectiveness.

  5. Fingerprint Image Segmentation Algorithm Based on Contourlet Transform Technology

    Directory of Open Access Journals (Sweden)

    Guanghua Zhang

    2016-09-01

    Full Text Available This paper briefly introduces two classic algorithms for fingerprint image processing, which include the soft threshold denoise algorithm of wavelet domain based on wavelet domain and the fingerprint image enhancement algorithm based on Gabor function. Contourlet transform has good texture sensitivity and can be used for the segmentation enforcement of the fingerprint image. The method proposed in this paper has attained the final fingerprint segmentation image through utilizing a modified denoising for a high-frequency coefficient after Contourlet decomposition, highlighting the fingerprint ridge line through modulus maxima detection and finally connecting the broken fingerprint line using a value filter in direction. It can attain richer direction information than the method based on wavelet transform and Gabor function and can make the positioning of detailed features more accurate. However, its ridge should be more coherent. Experiments have shown that this algorithm is obviously superior in fingerprint features detection.

  6. An algorithm of image segmentation for overlapping grain image

    Institute of Scientific and Technical Information of China (English)

    WANG Zhi; JIN Guang; SUN Xiao-wei

    2005-01-01

    Aiming at measurement of granularity size of nonmetal grain, an algorithm of image segmentation and parameter calculation for microscopic overlapping grain image was studied. This algorithm presents some new attributes of graph sequence from discrete attribute of graph,and consequently achieves the geometrical characteristics from input graph, and the new graph sequence in favor of image segmentation is recombined. The conception that image edge denoted with "twin-point" is put forward, base on geometrical characters of point, image edge is transformed into serial edge, and on recombined serial image edge, based on direction vector definition of line and some additional restricted conditions, the segmentation twin-points are searched with, thus image segmentation is accomplished. Serial image edge is transformed into twin-point pattern, to realize calculation of area and granularity size of nonmetal grain. The inkling and uncertainty on selection of structure element which base on mathematical morphology are avoided in this algorithm, and image segmentation and parameter calculation are realized without changing grain's self statistical characters.

  7. Sensitivity field distributions for segmental bioelectrical impedance analysis based on real human anatomy

    International Nuclear Information System (INIS)

    In this work, an adaptive unstructured tetrahedral mesh generation technology is applied for simulation of segmental bioimpedance measurements using high-resolution whole-body model of the Visible Human Project man. Sensitivity field distributions for a conventional tetrapolar, as well as eight- and ten-electrode measurement configurations are obtained. Based on the ten-electrode configuration, we suggest an algorithm for monitoring changes in the upper lung area.

  8. Sensitivity field distributions for segmental bioelectrical impedance analysis based on real human anatomy

    Science.gov (United States)

    Danilov, A. A.; Kramarenko, V. K.; Nikolaev, D. V.; Rudnev, S. G.; Salamatova, V. Yu; Smirnov, A. V.; Vassilevski, Yu V.

    2013-04-01

    In this work, an adaptive unstructured tetrahedral mesh generation technology is applied for simulation of segmental bioimpedance measurements using high-resolution whole-body model of the Visible Human Project man. Sensitivity field distributions for a conventional tetrapolar, as well as eight- and ten-electrode measurement configurations are obtained. Based on the ten-electrode configuration, we suggest an algorithm for monitoring changes in the upper lung area.

  9. Split Bregman's algorithm for three-dimensional mesh segmentation

    Science.gov (United States)

    Habiba, Nabi; Ali, Douik

    2016-05-01

    Variational methods have attracted a lot of attention in the literature, especially for image and mesh segmentation. The methods aim at minimizing the energy to optimize both edge and region detections. We propose a spectral mesh decomposition algorithm to obtain disjoint but meaningful regions of an input mesh. The related optimization problem is nonconvex, and it is very difficult to find a good approximation or global optimum, which represents a challenge in computer vision. We propose an alternating split Bregman algorithm for mesh segmentation, where we extended the image-dedicated model to a three-dimensional (3-D) mesh one. By applying our scheme to 3-D mesh segmentation, we obtain fast solvers that can outperform various conventional ones, such as graph-cut and primal dual methods. A consistent evaluation of the proposed method on various public domain 3-D databases for different metrics is elaborated, and a comparison with the state-of-the-art is performed.

  10. Video Segmentation Using Fast Marching and Region Growing Algorithms

    Directory of Open Access Journals (Sweden)

    Eftychis Sifakis

    2002-04-01

    Full Text Available The algorithm presented in this paper is comprised of three main stages: (1 classification of the image sequence and, in the case of a moving camera, parametric motion estimation, (2 change detection having as reference a fixed frame, an appropriately selected frame or a displaced frame, and (3 object localization using local colour features. The image sequence classification is based on statistical tests on the frame difference. The change detection module uses a two-label fast marching algorithm. Finally, the object localization uses a region growing algorithm based on the colour similarity. Video object segmentation results are shown using the COST 211 data set.

  11. Object Recognition Algorithm Utilizing Graph Cuts Based Image Segmentation

    Directory of Open Access Journals (Sweden)

    Zhaofeng Li

    2014-02-01

    Full Text Available This paper concentrates on designing an object recognition algorithm utilizing image segmentation. The main innovations of this paper lie in that we convert the image segmentation problem into graph cut problem, and then the graph cut results can be obtained by calculating the probability of intensity for a given pixel which is belonged to the object and the background intensity. After the graph cut process, the pixels in a same component are similar, and the pixels in different components are dissimilar. To detect the objects in the test image, the visual similarity between the segments of the testing images and the object types deduced from the training images is estimated. Finally, a series of experiments are conducted to make performance evaluation. Experimental results illustrate that compared with existing methods, the proposed scheme can effectively detect the salient objects. Particularly, we testify that, in our scheme, the precision of object recognition is proportional to image segmentation accuracy

  12. A New Algorithm for Interactive Structural Image Segmentation

    CERN Document Server

    Noma, Alexandre; Consularo, Luis Augusto; Cesar, Roberto M Jr; Bloch, Isabelle

    2008-01-01

    This paper proposes a novel algorithm for the problem of structural image segmentation through an interactive model-based approach. Interaction is expressed in the model creation, which is done according to user traces drawn over a given input image. Both model and input are then represented by means of attributed relational graphs derived on the fly. Appearance features are taken into account as object attributes and structural properties are expressed as relational attributes. To cope with possible topological differences between both graphs, a new structure called the deformation graph is introduced. The segmentation process corresponds to finding a labelling of the input graph that minimizes the deformations introduced in the model when it is updated with input information. This approach has shown to be faster than other segmentation methods, with competitive output quality. Therefore, the method solves the problem of multiple label segmentation in an efficient way. Encouraging results on both natural and...

  13. A HYBRID FIREFLY ALGORITHM WITH FUZZY-C MEAN ALGORITHM FOR MRI BRAIN SEGMENTATION

    Directory of Open Access Journals (Sweden)

    Mutasem K. Alsmadi

    2014-01-01

    Full Text Available Image processing is one of the essential tasks to extract suspicious region and robust features from the Magnetic Resonance Imaging (MRI. A numbers of the segmentation algorithms were developed in order to satisfy and increasing the accuracy of brain tumor detection. In the medical image processing brain image segmentation is considered as a complex and challenging part. Fuzzy c-means is unsupervised method that has been implemented for clustering of the MRI and different purposes such as recognition of the pattern of interest and image segmentation. However; fuzzy c-means algorithm still suffers many drawbacks, such as low convergence rate, getting stuck in the local minima and vulnerable to initialization sensitivity. Firefly algorithm is a new population-based optimization method that has been used successfully for solving many complex problems. This paper proposed a new dynamic and intelligent clustering method for brain tumor segmentation using the hybridization of Firefly Algorithm (FA with Fuzzy C-Means algorithm (FCM. In order to automatically segment MRI brain images and improve the capability of the FCM to automatically elicit the proper number and location of cluster centres and the number of pixels in each cluster in the abnormal (multiple sclerosis lesions MRI images. The experimental results proved the effectiveness of the proposed FAFCM in enhancing the performance of the traditional FCM clustering. Moreover; the superiority of the FAFCM with other state-of-the-art segmentation methods is shown qualitatively and quantitatively. Conclusion: A novel efficient and reliable clustering algorithm presented in this work, which is called FAFCM based on the hybridization of the firefly algorithm with fuzzy c-mean clustering algorithm. Automatically; the hybridized algorithm has the capability to cluster and segment MRI brain images.

  14. A comparative study of Image Region-Based Segmentation Algorithms

    Directory of Open Access Journals (Sweden)

    Lahouaoui LALAOUI

    2013-07-01

    Full Text Available Image segmentation has recently become an essential step in image processing as it mainly conditions the interpretation which is done afterwards. It is still difficult to justify the accuracy of a segmentation algorithm, regardless of the nature of the treated image. In this paper we perform an objective comparison of region-based segmentation techniques such as supervised and unsupervised deterministic classification, non-parametric and parametric probabilistic classification. Eight methods among the well-known and used in the scientific community have been selected and compared. The Martin’s(GCE, LCE, probabilistic Rand Index (RI, Variation of Information (VI and Boundary Displacement Error (BDE criteria are used to evaluate the performance of these algorithms on Magnetic Resonance (MR brain images, synthetic MR image, and synthetic images. MR brain image are composed of the gray matter (GM, white matter (WM and cerebrospinal fluid (CSF and others, and the synthetic MR image composed of the same for real image and the plus edema, and the tumor. Results show that segmentation is an image dependent process and that some of the evaluated methods are well suited for a better segmentation.

  15. Optimization-Based Image Segmentation by Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Rosenberger C

    2008-01-01

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

  16. Joint graph cut and relative fuzzy connectedness image segmentation algorithm.

    Science.gov (United States)

    Ciesielski, Krzysztof Chris; Miranda, Paulo A V; Falcão, Alexandre X; Udupa, Jayaram K

    2013-12-01

    We introduce an image segmentation algorithm, called GC(sum)(max), which combines, in novel manner, the strengths of two popular algorithms: Relative Fuzzy Connectedness (RFC) and (standard) Graph Cut (GC). We show, both theoretically and experimentally, that GC(sum)(max) preserves robustness of RFC with respect to the seed choice (thus, avoiding "shrinking problem" of GC), while keeping GC's stronger control over the problem of "leaking though poorly defined boundary segments." The analysis of GC(sum)(max) is greatly facilitated by our recent theoretical results that RFC can be described within the framework of Generalized GC (GGC) segmentation algorithms. In our implementation of GC(sum)(max) we use, as a subroutine, a version of RFC algorithm (based on Image Forest Transform) that runs (provably) in linear time with respect to the image size. This results in GC(sum)(max) running in a time close to linear. Experimental comparison of GC(sum)(max) to GC, an iterative version of RFC (IRFC), and power watershed (PW), based on a variety medical and non-medical images, indicates superior accuracy performance of GC(sum)(max) over these other methods, resulting in a rank ordering of GC(sum)(max)>PW∼IRFC>GC.

  17. Joint graph cut and relative fuzzy connectedness image segmentation algorithm.

    Science.gov (United States)

    Ciesielski, Krzysztof Chris; Miranda, Paulo A V; Falcão, Alexandre X; Udupa, Jayaram K

    2013-12-01

    We introduce an image segmentation algorithm, called GC(sum)(max), which combines, in novel manner, the strengths of two popular algorithms: Relative Fuzzy Connectedness (RFC) and (standard) Graph Cut (GC). We show, both theoretically and experimentally, that GC(sum)(max) preserves robustness of RFC with respect to the seed choice (thus, avoiding "shrinking problem" of GC), while keeping GC's stronger control over the problem of "leaking though poorly defined boundary segments." The analysis of GC(sum)(max) is greatly facilitated by our recent theoretical results that RFC can be described within the framework of Generalized GC (GGC) segmentation algorithms. In our implementation of GC(sum)(max) we use, as a subroutine, a version of RFC algorithm (based on Image Forest Transform) that runs (provably) in linear time with respect to the image size. This results in GC(sum)(max) running in a time close to linear. Experimental comparison of GC(sum)(max) to GC, an iterative version of RFC (IRFC), and power watershed (PW), based on a variety medical and non-medical images, indicates superior accuracy performance of GC(sum)(max) over these other methods, resulting in a rank ordering of GC(sum)(max)>PW∼IRFC>GC. PMID:23880374

  18. 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.

  19. An Improved Image Segmentation Algorithm Based on MET Method

    Directory of Open Access Journals (Sweden)

    Z. A. Abo-Eleneen

    2012-09-01

    Full Text Available Image segmentation is a basic component of many computer vision systems and pattern recognition. Thresholding is a simple but effective method to separate objects from the background. A commonly used method, Kittler and Illingworth's minimum error thresholding (MET, improves the image segmentation effect obviously. Its simpler and easier to implement. However, it fails in the presence of skew and heavy-tailed class-conditional distributions or if the histogram is unimodal or close to unimodal. The Fisher information (FI measure is an important concept in statistical estimation theory and information theory. Employing the FI measure, an improved threshold image segmentation algorithm FI-based extension of MET is developed. Comparing with the MET method, the improved method in general can achieve more robust performance when the data for either class is skew and heavy-tailed.

  20. A Parallel Markov Cerebrovascular Segmentation Algorithm Based on Statistical Model

    Institute of Scientific and Technical Information of China (English)

    Rong-Fei Cao; Xing-Ce Wang; Zhong-Ke Wu; Ming-Quan Zhou; Xin-Yu Liu

    2016-01-01

    For segmenting cerebral blood vessels from the time-of-flight magnetic resonance angiography (TOF-MRA) images accurately, we propose a parallel segmentation algorithm based on statistical model with Markov random field (MRF). Firstly, we improve traditional non-local means filter with patch-based Fourier transformation to preprocess the TOF-MRA images. In this step, we mainly utilize the sparseness and self-similarity of the MRA brain images sequence. Secondly, we add the MRF information to the finite mixture mode (FMM) to fit the intensity distribution of medical images. We make use of the MRF in image sequence to estimate the proportion of cerebral tissues. Finally, we choose the particle swarm optimization (PSO) algorithm to parallelize the parameter estimation of FMM. A large number of experiments verify the high accuracy and robustness of our approach especially for narrow vessels. The work will offer significant assistance for physicians on the prevention and diagnosis of cerebrovascular diseases.

  1. Color Image Segmentation Method Based on Improved Spectral Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    Dong Qin

    2014-08-01

    Full Text Available Contraposing to the features of image data with high sparsity of and the problems on determination of clustering numbers, we try to put forward an color image segmentation algorithm, combined with semi-supervised machine learning technology and spectral graph theory. By the research of related theories and methods of spectral clustering algorithms, we introduce information entropy conception to design a method which can automatically optimize the scale parameter value. So it avoids the unstability in clustering result of the scale parameter input manually. In addition, we try to excavate available priori information existing in large number of non-generic data and apply semi-supervised algorithm to improve the clustering performance for rare class. We also use added tag data to compute similar matrix and perform clustering through FKCM algorithms. By the simulation of standard dataset and image segmentation, the experiments demonstrate our algorithm has overcome the defects of traditional spectral clustering methods, which are sensitive to outliers and easy to fall into local optimum, and also poor in the convergence rate

  2. A Genetic Algorithm for the Segmentation of Known Touching Objects

    Directory of Open Access Journals (Sweden)

    Edgar Scavino

    2009-01-01

    Full Text Available Problem statement: Segmentation is the first and fundamental step in the process of computer vision and object classification. However, complicate or similar colour pattern add complexity to the segmentation of touching objects. The objective of this study was to develop a robust technique for the automatic segmentation and classification of touching plastic bottles, whose features were previously stored in a database. Approach: Our technique was based on the possibility to separate the two objects by means of a segment of straight line, whose position was determined by a genetic approach. The initial population of the genetic algorithm was heuristically determined among a large set of cutting lines, while further generations were selected based on the likelihood of the two objects with the images stored in the database. Results: Extensive testing, which was performed on random couples out of a population of 50 bottles, showed that the correct segmentation could be achieved in success rates above 90% with only a limited number of both chromosomes and iterations, thus reducing the computing time. Conclusion: These findings proved the effectiveness of our method as far as touching plastic bottles are concerned. This technique, being absolutely general, can be extended to any situation in which the properties of single objects were previously stored in a database.

  3. Simulated annealing spectral clustering algorithm for image segmentation

    Institute of Scientific and Technical Information of China (English)

    Yifang Yang; and Yuping Wang

    2014-01-01

    The similarity measure is crucial to the performance of spectral clustering. The Gaussian kernel function based on the Euclidean distance is usual y adopted as the similarity mea-sure. However, the Euclidean distance measure cannot ful y reveal the complex distribution data, and the result of spectral clustering is very sensitive to the scaling parameter. To solve these problems, a new manifold distance measure and a novel simulated anneal-ing spectral clustering (SASC) algorithm based on the manifold distance measure are proposed. The simulated annealing based on genetic algorithm (SAGA), characterized by its rapid conver-gence to the global optimum, is used to cluster the sample points in the spectral mapping space. The proposed algorithm can not only reflect local and global consistency better, but also reduce the sensitivity of spectral clustering to the kernel parameter, which improves the algorithm’s clustering performance. To efficiently ap-ply the algorithm to image segmentation, the Nystr¨om method is used to reduce the computation complexity. Experimental re-sults show that compared with traditional clustering algorithms and those popular spectral clustering algorithms, the proposed algorithm can achieve better clustering performances on several synthetic datasets, texture images and real images.

  4. An Improved Convexity Based Segmentation Algorithm for Heavily Camouflaged Images

    Directory of Open Access Journals (Sweden)

    Amarjot Singh

    2013-03-01

    Full Text Available The paper proposes an advanced convexity based segmentation algorithm for heavily camouflaged images. The convexity of the intensity function is used to detect camouflaged objects from complex environments. We take advantage of operator for the detection of 3D concave or convex graylevels to exhibit the effectiveness of camouflage breaking based on convexity. The biological motivation behind operator and its high robustness make it suitable for camouflage breaking. The traditional convexity based algorithm identifies the desired targets but in addition also identifies sub-targets due to their three dimensional behavior. The problem is overcome by combining the conventional algorithm with thresholding. The proposed method is able to eliminate the sub-targets leaving behind only the target of interest in the input image. The proposed method is compared with the conventional operator. It is also compared with some conventional edge based operator for performance evaluation.

  5. Automatic segmentation of male pelvic anatomy on computed tomography images: a comparison with multiple observers in the context of a multicentre clinical trial

    International Nuclear Information System (INIS)

    algorithms based on image-registration as in iPlan, it is apparent that agreement between observer and automatic segmentation will be a function of patient-specific image characteristics, particularly for anatomy with poor contrast definition. For this reason, it is suggested that automatic registration based on transformation of a single reference dataset adds a significant systematic bias to the resulting volumes and their use in the context of a multicentre trial should be carefully considered

  6. Extended Approach to Water Flow Algorithm for Text Line Segmentation

    Institute of Scientific and Technical Information of China (English)

    Darko Brodi(c)

    2012-01-01

    This paper proposes a new approach to the water flow algorithm for text line segmentation.In the basic method the hypothetical water flows under few specified angles which have been defined by water flow angle as parameter.It is applied to the document image frame from left to right and vice versa.As a result,the unwetted and wetted areas are established.Thesc areas separate text from non-text elements in each text line,respectively.Hence,they represent the control areas that are of major importance for text line segmentation.Primarily,an extended approach means extraction of the connected-components by bounding boxes ovcr text.By this way,each connected component is mutually separated.Hence,the water flow angle,which defines the unwetted areas,is determined adaptively.By choosing appropriate water flow angle,the unwetted areas are lengthening which leads to the better text line segmentation.Results of this approach are encouraging due to the text line segmentation improvement which is the most challenging step in document image processing.

  7. Crowdsourcing the creation of image segmentation algorithms for connectomics

    Directory of Open Access Journals (Sweden)

    Ignacio eArganda-Carreras

    2015-11-01

    Full Text Available To stimulate progress in automating the reconstruction of neural circuits,we organized the first international challenge on 2D segmentationof electron microscopic (EM images of the brain. Participants submittedboundary maps predicted for a test set of images, and were scoredbased on their agreement with ground truth from human experts. Thewinning team had no prior experience with EM images, and employeda convolutional network. This ``deep learning'' approach has sincebecome accepted as a standard for segmentation of EM images. The challengehas continued to accept submissions, and the best so far has resultedfrom cooperation between two teams. The challenge has probably saturated,as algorithms cannot progress beyond limits set by ambiguities inherentin 2D scoring. Retrospective evaluation of the challenge scoring systemreveals that it was not sufficiently robust to variations in the widthsof neurite borders. We propose a solution to this problem, which shouldbe useful for a future 3D segmentation challenge.

  8. A New Approach to Lung Image Segmentation using Fuzzy Possibilistic C-Means Algorithm

    CERN Document Server

    Gomathi, M

    2010-01-01

    Image segmentation is a vital part of image processing. Segmentation has its application widespread in the field of medical images in order to diagnose curious diseases. The same medical images can be segmented manually. But the accuracy of image segmentation using the segmentation algorithms is more when compared with the manual segmentation. In the field of medical diagnosis an extensive diversity of imaging techniques is presently available, such as radiography, computed tomography (CT) and magnetic resonance imaging (MRI). Medical image segmentation is an essential step for most consequent image analysis tasks. Although the original FCM algorithm yields good results for segmenting noise free images, it fails to segment images corrupted by noise, outliers and other imaging artifact. This paper presents an image segmentation approach using Modified Fuzzy C-Means (FCM) algorithm and Fuzzy Possibilistic c-means algorithm (FPCM). This approach is a generalized version of standard Fuzzy CMeans Clustering (FCM) ...

  9. The Galileo Ground Segment Integrity Algorithms: Design and Performance

    Directory of Open Access Journals (Sweden)

    Carlos Hernández Medel

    2008-01-01

    Full Text Available Galileo, the European Global Navigation Satellite System, will provide to its users highly accurate global positioning services and their associated integrity information. The element in charge of the computation of integrity messages within the Galileo Ground Mission Segment is the integrity processing facility (IPF, which is developed by GMV Aerospace and Defence. The main objective of this paper is twofold: to present the integrity algorithms implemented in the IPF and to show the achieved performance with the IPF software prototype, including aspects such as: implementation of the Galileo overbounding concept, impact of safety requirements on the algorithm design including the threat models for the so-called feared events, and finally the achieved performance with real GPS and simulated Galileo scenarios.

  10. A 3D global-to-local deformable mesh model based registration and anatomy-constrained segmentation method for image guided prostate radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Zhou Jinghao; Kim, Sung; Jabbour, Salma; Goyal, Sharad; Haffty, Bruce; Chen, Ting; Levinson, Lydia; Metaxas, Dimitris; Yue, Ning J. [Department of Radiation Oncology, UMDNJ-Robert Wood Johnson Medical School, Cancer Institute of New Jersey, New Brunswick, New Jersey 08903 (United States); Department of Bioinformatics, UMDNJ-Robert Wood Johnson Medical School, Cancer Institute of New Jersey, New Brunswick, New Jersey 08903 (United States); Department of Radiation Oncology, UMDNJ-Robert Wood Johnson Medical School, Cancer Institute of New Jersey, New Brunswick, New Jersey 08903 (United States); Department of Computer Science, Rutgers, State University of New Jersey, Piscataway, New Jersey 08854 (United States); Department of Radiation Oncology, UMDNJ-Robert Wood Johnson Medical School, Cancer Institute of New Jersey, New Brunswick, New Jersey 08903 (United States)

    2010-03-15

    Purpose: In the external beam radiation treatment of prostate cancers, successful implementation of adaptive radiotherapy and conformal radiation dose delivery is highly dependent on precise and expeditious segmentation and registration of the prostate volume between the simulation and the treatment images. The purpose of this study is to develop a novel, fast, and accurate segmentation and registration method to increase the computational efficiency to meet the restricted clinical treatment time requirement in image guided radiotherapy. Methods: The method developed in this study used soft tissues to capture the transformation between the 3D planning CT (pCT) images and 3D cone-beam CT (CBCT) treatment images. The method incorporated a global-to-local deformable mesh model based registration framework as well as an automatic anatomy-constrained robust active shape model (ACRASM) based segmentation algorithm in the 3D CBCT images. The global registration was based on the mutual information method, and the local registration was to minimize the Euclidian distance of the corresponding nodal points from the global transformation of deformable mesh models, which implicitly used the information of the segmented target volume. The method was applied on six data sets of prostate cancer patients. Target volumes delineated by the same radiation oncologist on the pCT and CBCT were chosen as the benchmarks and were compared to the segmented and registered results. The distance-based and the volume-based estimators were used to quantitatively evaluate the results of segmentation and registration. Results: The ACRASM segmentation algorithm was compared to the original active shape model (ASM) algorithm by evaluating the values of the distance-based estimators. With respect to the corresponding benchmarks, the mean distance ranged from -0.85 to 0.84 mm for ACRASM and from -1.44 to 1.17 mm for ASM. The mean absolute distance ranged from 1.77 to 3.07 mm for ACRASM and from 2.45 to

  11. CSHURI - Modified HURI algorithm for Customer Segmentation and Transaction Profitability

    CERN Document Server

    Pillai, Jyothi

    2012-01-01

    Association rule mining (ARM) is the process of generating rules based on the correlation between the set of items that the customers purchase.Of late, data mining researchers have improved upon the quality of association rule mining for business development by incorporating factors like value (utility), quantity of items sold (weight) and profit. The rules mined without considering utility values (profit margin) will lead to a probable loss of profitable rules. The advantage of wealth of the customers' needs information and rules aids the retailer in designing his store layout[9]. An algorithm CSHURI, Customer Segmentation using HURI, is proposed, a modified version of HURI [6], finds customers who purchase high profitable rare items and accordingly classify the customers based on some criteria; for example, a retail business may need to identify valuable customers who are major contributors to a company's overall profit. For a potential customer arriving in the store, which customer group one should belong ...

  12. A modified region growing algorithm for multi-colored image object segmentation

    Institute of Scientific and Technical Information of China (English)

    Yuxi Chen; Chongzhao Han

    2007-01-01

    A hybrid algorithm based on seeded region growing and k-means clustering was proposed to improve image object segmentation result. A user friendly segmentation tool was provided for the definition of objects,then k-means algorithm was utilized to cluster the selected points into k seeds-clusters, finally the seeded region growing algorithm was used for object segmentation. Experimental results show that the proposed method is suitable for segmentation of multi-colored object, while conventional seeded region growing methods can only segment uniform-colored object.

  13. An Unsupervised Dynamic Image Segmentation using Fuzzy Hopfield Neural Network based Genetic Algorithm

    CERN Document Server

    Halder, Amiya

    2012-01-01

    This paper proposes a Genetic Algorithm based segmentation method that can automatically segment gray-scale images. The proposed method mainly consists of spatial unsupervised grayscale image segmentation that divides an image into regions. The aim of this algorithm is to produce precise segmentation of images using intensity information along with neighborhood relationships. In this paper, Fuzzy Hopfield Neural Network (FHNN) clustering helps in generating the population of Genetic algorithm which there by automatically segments the image. This technique is a powerful method for image segmentation and works for both single and multiple-feature data with spatial information. Validity index has been utilized for introducing a robust technique for finding the optimum number of components in an image. Experimental results shown that the algorithm generates good quality segmented image.

  14. New two-dimensional fuzzy C-means clustering algorithm for image segmentation

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    To solve the problem of poor anti-noise performance of the traditional fuzzy C-means (FCM) algorithm in image segmentation,a novel two-dimensional FCM clustering algorithm for image segmentation was proposed.In this method,the image segmentation was converted into an optimization problem.The fitness function containing neighbor information was set up based on the gray information and the neighbor relations between the pixcls described by the improved two-dimensional histogram.By making use of the global searching ability of the predator-prey particle swarm optimization,the optimal cluster center could be obtained by iterative optimization,and the image segmentation could be accomplished.The simulation results show that the segmentation accuracy ratio of the proposed method is above 99%.The proposed algorithm has strong anti-noise capability,high clustering accuracy and good segment effect,indicating that it is an effective algorithm for image segmentation.

  15. Fast interactive segmentation algorithm of image sequences based on relative fuzzy connectedness

    Institute of Scientific and Technical Information of China (English)

    Tian Chunna; Gao Xinbo

    2005-01-01

    A fast interactive segmentation algorithm of image-sequences based on relative fuzzy connectedness is presented. In comparison with the original algorithm, the proposed one, with the same accuracy, accelerates the segmentation speed by three times for single image. Meanwhile, this fast segmentation algorithm is extended from single object to multiple objects and from single-image to image-sequences. Thus the segmentation of multiple objects from complex background and batch segmentation of image-sequences can be achieved. In addition, a post-processing scheme is incorporated in this algorithm, which extracts smooth edge with one-pixel-width for each segmented object. The experimental results illustrate that the proposed algorithm can obtain the object regions of interest from medical image or image-sequences as well as man-made images quickly and reliably with only a little interaction.

  16. Categorizing segmentation quality using a quantitative quality assurance algorithm

    International Nuclear Information System (INIS)

    Obtaining high levels of contouring consistency is a major limiting step in optimizing the radiotherapeutic ratio. We describe a novel quantitative methodology for the quality assurance (QA) of contour compliance referenced against a community set of contouring experts. Two clinical tumour site scenarios (10 lung cases and one prostate case) were used with QA algorithm. For each case, multiple physicians (lung: n = 6, prostate: n = 25) segmented various target/organ at risk (OAR) structures to define a set of community reference contours. For each set of community contours, a consensus contour (Simultaneous Truth and Performance Level Estimation (STAPLE)) was created. Differences between each individual community contour versus the group consensus contour were quantified by consensus-based contouring penalty metric (PM) scores. New observers segmented these same cases to calculate individual PM scores (for each unique target/OAR) for each new observer–STAPLE pair for comparison against the community and consensus contours. Four physicians contoured the 10 lung cases for a total of 72 contours for quality assurance evaluation against the previously derived community consensus contours. A total of 16 outlier contours were identified by the QA system of which 11 outliers were due to over-contouring discrepancies, three were due to over-/under-contouring discrepancies, and two were due to missing/incorrect nodal contours. In the prostate scenario involving six physicians, the QA system detected a missing penile bulb contour, systematic inner-bladder contouring, and under-contouring of the upper/anterior rectum. A practical methodology for QA has been demonstrated with future clinical trial credentialing, medical education and auto-contouring assessment applications.

  17. Voxel classification and graph cuts for automated segmentation of pathological periprosthetic hip anatomy

    NARCIS (Netherlands)

    Malan, D.F.; Botha, C.P.; Valstar, E.R.

    2012-01-01

    Purpose Automated patient-specific image-based segmentation of tissues surrounding aseptically loose hip prostheses is desired. For this we present an automated segmentation pipeline that labels periprosthetic tissues in computed tomography (CT). The intended application of this pipeline is in pre-o

  18. Wound size measurement of lower extremity ulcers using segmentation algorithms

    Science.gov (United States)

    Dadkhah, Arash; Pang, Xing; Solis, Elizabeth; Fang, Ruogu; Godavarty, Anuradha

    2016-03-01

    Lower extremity ulcers are one of the most common complications that not only affect many people around the world but also have huge impact on economy since a large amount of resources are spent for treatment and prevention of the diseases. Clinical studies have shown that reduction in the wound size of 40% within 4 weeks is an acceptable progress in the healing process. Quantification of the wound size plays a crucial role in assessing the extent of healing and determining the treatment process. To date, wound healing is visually inspected and the wound size is measured from surface images. The extent of wound healing internally may vary from the surface. A near-infrared (NIR) optical imaging approach has been developed for non-contact imaging of wounds internally and differentiating healing from non-healing wounds. Herein, quantitative wound size measurements from NIR and white light images are estimated using a graph cuts and region growing image segmentation algorithms. The extent of the wound healing from NIR imaging of lower extremity ulcers in diabetic subjects are quantified and compared across NIR and white light images. NIR imaging and wound size measurements can play a significant role in potentially predicting the extent of internal healing, thus allowing better treatment plans when implemented for periodic imaging in future.

  19. Voxel classification and graph cuts for automated segmentation of pathological periprosthetic hip anatomy

    OpenAIRE

    Malan, D.F.; Botha, C.P.; Valstar, E.R.

    2012-01-01

    Purpose Automated patient-specific image-based segmentation of tissues surrounding aseptically loose hip prostheses is desired. For this we present an automated segmentation pipeline that labels periprosthetic tissues in computed tomography (CT). The intended application of this pipeline is in pre-operative planning. Methods Individual voxels were classified based on a set of automatically extracted image features. Minimum-cost graph cuts were computed on the classification results. The graph...

  20. Dynamic shared segment protection algorithm with differentiated reliability in GMPLS networks

    Institute of Scientific and Technical Information of China (English)

    Wang Yan; Zheng Junhui; Zeng Jiazhi

    2009-01-01

    To improve the resource utilization ratio and shorten the recovery time of the shared path protection with differentiated reliability (SPP-DiR) algorithm, an algorithm called dynamic shared segment protection with differentiated reliability (DSSP-DiR) is proposed for survivable GMPLS networks. In the proposed algorithm, a primary path is dynamically divided into several segments according to the differentiated reliability requirements of the customers. In the SPP-DiR algorithm, the whole primary path should be protected, while in the DSSP-DiR algorithm, only partial segments on the primary path need to be protected, which can reduce more backup bandwidths than that in the SPP-DiR algorithm. Simulation results show that the DSSP-DiR algorithm achieves higher resource utilization ratio, lower protection failure probability, and shorter recovery time than the SPP-DiR algorithm.

  1. Hybridizing Differential Evolution with a Genetic Algorithm for Color Image Segmentation

    Directory of Open Access Journals (Sweden)

    R. V. V. Krishna

    2016-10-01

    Full Text Available This paper proposes a hybrid of differential evolution and genetic algorithms to solve the color image segmentation problem. Clustering based color image segmentation algorithms segment an image by clustering the features of color and texture, thereby obtaining accurate prototype cluster centers. In the proposed algorithm, the color features are obtained using the homogeneity model. A new texture feature named Power Law Descriptor (PLD which is a modification of Weber Local Descriptor (WLD is proposed and further used as a texture feature for clustering. Genetic algorithms are competent in handling binary variables, while differential evolution on the other hand is more efficient in handling real parameters. The obtained texture feature is binary in nature and the color feature is a real value, which suits very well the hybrid cluster center optimization problem in image segmentation. Thus in the proposed algorithm, the optimum texture feature centers are evolved using genetic algorithms, whereas the optimum color feature centers are evolved using differential evolution.

  2. Automated segmentation of tumors on bone scans using anatomy-specific thresholding

    Science.gov (United States)

    Chu, Gregory H.; Lo, Pechin; Kim, Hyun J.; Lu, Peiyun; Ramakrishna, Bharath; Gjertson, David; Poon, Cheryce; Auerbach, Martin; Goldin, Jonathan; Brown, Matthew S.

    2012-03-01

    Quantification of overall tumor area on bone scans may be a potential biomarker for treatment response assessment and has, to date, not been investigated. Segmentation of bone metastases on bone scans is a fundamental step for this response marker. In this paper, we propose a fully automated computerized method for the segmentation of bone metastases on bone scans, taking into account characteristics of different anatomic regions. A scan is first segmented into anatomic regions via an atlas-based segmentation procedure, which involves non-rigidly registering a labeled atlas scan to the patient scan. Next, an intensity normalization method is applied to account for varying levels of radiotracer dosing levels and scan timing. Lastly, lesions are segmented via anatomic regionspecific intensity thresholding. Thresholds are chosen by receiver operating characteristic (ROC) curve analysis against manual contouring by board certified nuclear medicine physicians. A leave-one-out cross validation of our method on a set of 39 bone scans with metastases marked by 2 board-certified nuclear medicine physicians yielded a median sensitivity of 95.5%, and specificity of 93.9%. Our method was compared with a global intensity thresholding method. The results show a comparable sensitivity and significantly improved overall specificity, with a p-value of 0.0069.

  3. Alternative Fuzzy Cluster Segmentation of Remote Sensing Images Based on Adaptive Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    WANG Jing; TANG Jilong; LIU Jibin; REN Chunying; LIU Xiangnan; FENG Jiang

    2009-01-01

    Remote sensing image segmentation is the basis of image understanding and analysis. However, the precision and the speed of segmentation can not meet the need of image analysis, due to strong uncertainty and rich texture details of remote sensing images. We proposed a new segmentation method based on Adaptive Genetic Algorithm (AGA) and Alternative Fuzzy C-Means (AFCM). Segmentation thresholds were identified by AGA. Then the image was segmented by AFCM. The results indicate that the precision and the speed of segmentation have been greatly increased, and the accuracy of threshold selection is much higher compared with traditional Otsu and Fuzzy C-Means (FCM) segmentation methods. The segmentation results also show that multi-thresholds segmentation has been achieved by combining AGA with AFCM.

  4. An improved algorithm for coronary bypass anastomosis segmentation in epicardial ultrasound sequences

    DEFF Research Database (Denmark)

    Jørgensen, Alex Skovsbo; Schmidt, Samuel Emil; Staalsen, Niels-Henrik;

    2016-01-01

    Epicardial ultrasound (EUS) can be used for intra-operative quality assessment of coronary artery bypass anastomoses. To quantify the anastomotic quality from EUS images, the area of anastomotic structures has to be extracted from EUS sequences. Currently, this is done manually as no objective...... methods are available. We used an automatic anastomosis segmentation algorithm to extract the area of anastomotic structures from in vivo EUS sequences obtained from 16 porcine anastomoses. The algorithm consists of four major components: vessel detection, vessel segmentation, segmentation quality control...... and inter-frame contour alignment. The segmentation accuracy was assessed using m-fold cross-validation based on 830 manual segmentations of the anastomotic structures. A Dice coefficient of 0.879 (±0.073) and an absolute area difference of 16.95% (±17.94) were obtained. The proposed segmentation algorithm...

  5. Objective Performance Evaluation of Video Segmentation Algorithms with Ground-Truth

    Institute of Scientific and Technical Information of China (English)

    杨高波; 张兆扬

    2004-01-01

    While the development of particular video segmentation algorithms has attracted considerable research interest, relatively little effort has been devoted to provide a methodology for evaluating their performance. In this paper, we propose a methodology to objectively evaluate video segmentation algorithm with ground-truth, which is based on computing the deviation of segmentation results from the reference segmentation. Four different metrics based on classification pixels, edges, relative foreground area and relative position respectively are combined to address the spatial accuracy. Temporal coherency is evaluated by utilizing the difference of spatial accuracy between successive frames. The experimental results show the feasibility of our approach. Moreover, it is computationally more efficient than previous methods. It can be applied to provide an offline ranking among different segmentation algorithms and to optimally set the parameters for a given algorithm.

  6. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique

    Directory of Open Access Journals (Sweden)

    Yasira Beevi C P

    2009-12-01

    Full Text Available Automatic video segmentation plays an important role in real-time MPEG-4 encoding systems. This paper presents a video segmentation algorithm for MPEG-4 camera system with change detection, background registration techniques and real time adaptive thresholdtechniques. This algorithm can give satisfying segmentation results with low computation load. Besides, it has shadow cancellation mode, which can deal with light changing effect and shadow effect. Furthermore, this algorithm also implemented real time adaptive threshold techniques by which the parameters can be decided automatically.

  7. Robust protein microarray image segmentation using improved seeded region growing algorithm

    Institute of Scientific and Technical Information of China (English)

    Liqiang Wang(王立强); Xuxiang Ni(倪旭翔); Zukang Lu(陆祖康)

    2003-01-01

    Protein microarray technology has recently emerged as a powerful tool for biomedical research. Before automatic analysis the protein microarray images, protein spots in the images must be determined appropriately by spot segmentation algorithm. In this paper, an improved seeded region growing (ISRG)algorithm for protein microarray segmentation is presented, the seeds are obtained by finding the positions of the printed spots, and the protein spot regions are grown through these seeds. The experiment results show that the presented algorithm is accurate for adaptive shape segmentation and robust for protein microarray images contaminated by noise.

  8. AN INTELLIGENT SEGMENTATION ALGORITHM FOR MICROARRAY IMAGE PROCESSING

    Directory of Open Access Journals (Sweden)

    P.Rajkumar

    2013-06-01

    Full Text Available Microarray technology consists of an array of thousands of microscopic spots of DNA oligonucleotides attached to a solid surface. It is a very powerful technique for analyzing gene expressions as well as to explore the underlying genetic causes of many human diseases. There are numerous applications of this technology, including environmental health research, drug design and discovery, clinical diagnosis and treatment and in cancer detection. The spots, which represent genes in microarray experiment contains the quantitative information that needs to be extracted accurately. For this process, preprocessing of microarray plays an essential role and it is also influential in future steps of the analysis. The three microarray preprocessing steps include gridding, segmentation and quantification. The first step is gridding, refers to the identification of the centre coordinates of each spot. The second step is segmentation, refers to the process of separating foreground and background fluorescence intensities. Segmentation is very important step as it directly affects the accuracy of gene expression analysis in the data mining process that follows. Accurate segmentation is one of the vital steps in microarray image processing. A novel method for segmentation of microarray image is proposed which accurately segment the spots from background when compared with adaptive threshold, combined global and local thresholdand fuzzy c-means clustering methods. Experimental results show that our proposed method provides better segmentation and improved intensity values than the above existing methods.

  9. Flame Image Segmentation Based on the Bee Colony Algorithm with Characteristics of Levy Flights

    Directory of Open Access Journals (Sweden)

    Xiaolin Zhang

    2015-01-01

    Full Text Available The real-time processing of the image segmentation method with accuracy is very important in the application of the flame image detection system. This paper considers a novel method for flame image segmentation. It is the bee colony algorithm with characteristics enhancement of Levy flights against the problems of the algorithm during segmentation, including long calculation time and poor stability. By introducing the idea of Levy flights, this method designs a new local search strategy. By setting the current optimal value and based on the collaboration between the populations, it reinforces the overall convergence speed. By adopting the new fitness evaluation method and combining it with the two-dimensional entropy multithreshold segmentation principle, this paper develops a threshold segmentation test of the flame image. Test results show that this method has some advantages in terms of accuracy of threshold selection and calculation time. The robustness of the algorithm meets the actual demands in the engineering application.

  10. The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce

    Science.gov (United States)

    Chen, Xi; Zhou, Liqing

    2015-12-01

    With the development of satellite remote sensing technology and the remote sensing image data, traditional remote sensing image segmentation technology cannot meet the massive remote sensing image processing and storage requirements. This article put cloud computing and parallel computing technology in remote sensing image segmentation process, and build a cheap and efficient computer cluster system that uses parallel processing to achieve MeanShift algorithm of remote sensing image segmentation based on the MapReduce model, not only to ensure the quality of remote sensing image segmentation, improved split speed, and better meet the real-time requirements. The remote sensing image segmentation MeanShift algorithm parallel processing algorithm based on MapReduce shows certain significance and a realization of value.

  11. Segmentation of Mushroom and Cap width Measurement using Modified K-Means Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    Eser Sert

    2014-01-01

    Full Text Available Mushroom is one of the commonly consumed foods. Image processing is one of the effective way for examination of visual features and detecting the size of a mushroom. We developed software for segmentation of a mushroom in a picture and also to measure the cap width of the mushroom. K-Means clustering method is used for the process. K-Means is one of the most successful clustering methods. In our study we customized the algorithm to get the best result and tested the algorithm. In the system, at first mushroom picture is filtered, histograms are balanced and after that segmentation is performed. Results provided that customized algorithm performed better segmentation than classical K-Means algorithm. Tests performed on the designed software showed that segmentation on complex background pictures is performed with high accuracy, and 20 mushrooms caps are measured with 2.281 % relative error.

  12. Accuracy of patient specific organ-dose estimates obtained using an automated image segmentation algorithm

    Science.gov (United States)

    Gilat-Schmidt, Taly; Wang, Adam; Coradi, Thomas; Haas, Benjamin; Star-Lack, Josh

    2016-03-01

    The overall goal of this work is to develop a rapid, accurate and fully automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using a deterministic Boltzmann Transport Equation solver and automated CT segmentation algorithms. This work quantified the accuracy of organ dose estimates obtained by an automated segmentation algorithm. The investigated algorithm uses a combination of feature-based and atlas-based methods. A multiatlas approach was also investigated. We hypothesize that the auto-segmentation algorithm is sufficiently accurate to provide organ dose estimates since random errors at the organ boundaries will average out when computing the total organ dose. To test this hypothesis, twenty head-neck CT scans were expertly segmented into nine regions. A leave-one-out validation study was performed, where every case was automatically segmented with each of the remaining cases used as the expert atlas, resulting in nineteen automated segmentations for each of the twenty datasets. The segmented regions were applied to gold-standard Monte Carlo dose maps to estimate mean and peak organ doses. The results demonstrated that the fully automated segmentation algorithm estimated the mean organ dose to within 10% of the expert segmentation for regions other than the spinal canal, with median error for each organ region below 2%. In the spinal canal region, the median error was 7% across all data sets and atlases, with a maximum error of 20%. The error in peak organ dose was below 10% for all regions, with a median error below 4% for all organ regions. The multiple-case atlas reduced the variation in the dose estimates and additional improvements may be possible with more robust multi-atlas approaches. Overall, the results support potential feasibility of an automated segmentation algorithm to provide accurate organ dose estimates.

  13. A Class Of Iterative Thresholding Algorithms For Real-Time Image Segmentation

    Science.gov (United States)

    Hassan, M. H.

    1989-03-01

    Thresholding algorithms are developed for segmenting gray-level images under nonuniform illumination. The algorithms are based on learning models generated from recursive digital filters which yield to continuously varying threshold tracking functions. A real-time region growing algorithm, which locates the objects in the image while thresholding, is developed and implemented. The algorithms work in a raster-scan format, thus making them attractive for real-time image segmentation in situations requiring fast data throughput such as robot vision and character recognition.

  14. A New Image Threshold Segmentation based on Fuzzy Entropy and Improved Intelligent Optimization Algorithm

    OpenAIRE

    Yong-sheng Wang

    2014-01-01

    Image segmentation is one of the key techniques in the field of image understanding and computer vision. To determine the optimal threshold in image segmentation, an effective image threshold segmentation method based on fuzzy logic is presented. A new kind of fuzzy entropy is defined, that is not only related to the membership, but also related to probability distribution. According to the maximum entropy criterion, the improved particle swarm optimization algorithm based on chaos bee colony...

  15. Automatically Gradient Threshold Estimation of Anisotropic Diffusion for Meyer’s Watershed Algorithm Based Optimal Segmentation

    Directory of Open Access Journals (Sweden)

    Mithun Kumar PK

    2014-11-01

    Full Text Available Medical image segmentation is a fundamental task in the medical imaging field. Optimal segmentation is required for the accurate judgment or appropriate clinical diagnosis. In this paper, we proposed automatically gradient threshold estimator of anisotropic diffusion for Meyer’s Watershed algorithm based optimal segmentation. The Meyer’s Watershed algorithm is the most significant for a large number of regions separations but the over segmentation is the major drawback of the Meyer’s Watershed algorithm. We are able to remove over segmentation after using anisotropic diffusion as a preprocessing step of segmentation in the Meyer’s Watershed algorithm. We used a fixed window size for dynamically gradient threshold estimation. The gradient threshold is the most important parameter of the anisotropic diffusion for image smoothing. The proposed method is able to segment medical image accurately because of obtaining the enhancement image. The introducing method demonstrates better performance without loss of any clinical information while preserving edges. Our investigated method is more efficient and effective in order to segment the region of interests in the medical images indeed.

  16. PRESEE: an MDL/MML algorithm to time-series stream segmenting.

    Science.gov (United States)

    Xu, Kaikuo; Jiang, Yexi; Tang, Mingjie; Yuan, Changan; Tang, Changjie

    2013-01-01

    Time-series stream is one of the most common data types in data mining field. It is prevalent in fields such as stock market, ecology, and medical care. Segmentation is a key step to accelerate the processing speed of time-series stream mining. Previous algorithms for segmenting mainly focused on the issue of ameliorating precision instead of paying much attention to the efficiency. Moreover, the performance of these algorithms depends heavily on parameters, which are hard for the users to set. In this paper, we propose PRESEE (parameter-free, real-time, and scalable time-series stream segmenting algorithm), which greatly improves the efficiency of time-series stream segmenting. PRESEE is based on both MDL (minimum description length) and MML (minimum message length) methods, which could segment the data automatically. To evaluate the performance of PRESEE, we conduct several experiments on time-series streams of different types and compare it with the state-of-art algorithm. The empirical results show that PRESEE is very efficient for real-time stream datasets by improving segmenting speed nearly ten times. The novelty of this algorithm is further demonstrated by the application of PRESEE in segmenting real-time stream datasets from ChinaFLUX sensor networks data stream. PMID:23956693

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

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

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

    2015-12-01

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

  19. Image segmentation algorithm based on high-dimension fuzzy character and restrained clustering network

    Institute of Scientific and Technical Information of China (English)

    Baoping Wang; Yang Fang; Chao Sun

    2014-01-01

    An image segmentation algorithm of the restrained fuzzy Kohonen clustering network (RFKCN) based on high-dimension fuzzy character is proposed. The algorithm includes two steps. The first step is the fuzzification of pixels in which two redundant images are built by fuzzy mean value and fuzzy median value. The second step is to construct a three-dimensional (3-D) feature vector of redundant images and their original images and cluster the feature vector through RFKCN, to realize image seg-mentation. The proposed algorithm ful y takes into account not only gray distribution information of pixels, but also relevant information and fuzzy information among neighboring pixels in constructing 3-D character space. Based on the combination of competitiveness, redundancy and complementary of the information, the proposed algorithm improves the accuracy of clustering. Theoretical anal-yses and experimental results demonstrate that the proposed algorithm has a good segmentation performance.

  20. Study on Control Algorithm for Continuous Segments Trajectory Interpolation

    Institute of Scientific and Technical Information of China (English)

    SHI Chuan; YE Peiqing; LV Qiang

    2006-01-01

    In CNC machining, the complexity of the part contour causes a series of problems including the repeated start-stop of the motor, low machining efficiency, and poor machining quality. To relieve those problems, a new interpolation algorithm was put forward to realize the interpolation control of continuous sections trajectory. The relevant error analysis of the algorithm was also studied. The feasibility of the algorithm was proved by machining experiment using a laser machine to carve the interpolation trajectory in the CNC system GT100. This algorithm effectively improved the machining efficiency and the contour quality.

  1. PREPAID TELECOM CUSTOMERS SEGMENTATION USING THE K-MEAN ALGORITHM

    Directory of Open Access Journals (Sweden)

    Marar Liviu Ioan

    2012-07-01

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

  2. Segmentation of pomegranate MR images using spatial fuzzy c-means (SFCM) algorithm

    Science.gov (United States)

    Moradi, Ghobad; Shamsi, Mousa; Sedaaghi, M. H.; Alsharif, M. R.

    2011-10-01

    Segmentation is one of the fundamental issues of image processing and machine vision. It plays a prominent role in a variety of image processing applications. In this paper, one of the most important applications of image processing in MRI segmentation of pomegranate is explored. Pomegranate is a fruit with pharmacological properties such as being anti-viral and anti-cancer. Having a high quality product in hand would be critical factor in its marketing. The internal quality of the product is comprehensively important in the sorting process. The determination of qualitative features cannot be manually made. Therefore, the segmentation of the internal structures of the fruit needs to be performed as accurately as possible in presence of noise. Fuzzy c-means (FCM) algorithm is noise-sensitive and pixels with noise are classified inversely. As a solution, in this paper, the spatial FCM algorithm in pomegranate MR images' segmentation is proposed. The algorithm is performed with setting the spatial neighborhood information in FCM and modification of fuzzy membership function for each class. The segmentation algorithm results on the original and the corrupted Pomegranate MR images by Gaussian, Salt Pepper and Speckle noises show that the SFCM algorithm operates much more significantly than FCM algorithm. Also, after diverse steps of qualitative and quantitative analysis, we have concluded that the SFCM algorithm with 5×5 window size is better than the other windows.

  3. Tissue segmentation of computed tomography images using a Random Forest algorithm: a feasibility study.

    Science.gov (United States)

    Polan, Daniel F; Brady, Samuel L; Kaufman, Robert A

    2016-09-01

    There is a need for robust, fully automated whole body organ segmentation for diagnostic CT. This study investigates and optimizes a Random Forest algorithm for automated organ segmentation; explores the limitations of a Random Forest algorithm applied to the CT environment; and demonstrates segmentation accuracy in a feasibility study of pediatric and adult patients. To the best of our knowledge, this is the first study to investigate a trainable Weka segmentation (TWS) implementation using Random Forest machine-learning as a means to develop a fully automated tissue segmentation tool developed specifically for pediatric and adult examinations in a diagnostic CT environment. Current innovation in computed tomography (CT) is focused on radiomics, patient-specific radiation dose calculation, and image quality improvement using iterative reconstruction, all of which require specific knowledge of tissue and organ systems within a CT image. The purpose of this study was to develop a fully automated Random Forest classifier algorithm for segmentation of neck-chest-abdomen-pelvis CT examinations based on pediatric and adult CT protocols. Seven materials were classified: background, lung/internal air or gas, fat, muscle, solid organ parenchyma, blood/contrast enhanced fluid, and bone tissue using Matlab and the TWS plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance evaluated over a voxel radius of 2 (n) , (n from 0 to 4), along with noise reduction and edge preserving filters: Gaussian, bilateral, Kuwahara, and anisotropic diffusion. The Random Forest algorithm used 200 trees with 2 features randomly selected per node. The optimized auto-segmentation algorithm resulted in 16 image features including features derived from maximum, mean, variance Gaussian and Kuwahara filters. Dice similarity coefficient (DSC) calculations between manually segmented and Random Forest algorithm segmented images from 21

  4. Tissue segmentation of computed tomography images using a Random Forest algorithm: a feasibility study

    Science.gov (United States)

    Polan, Daniel F.; Brady, Samuel L.; Kaufman, Robert A.

    2016-09-01

    There is a need for robust, fully automated whole body organ segmentation for diagnostic CT. This study investigates and optimizes a Random Forest algorithm for automated organ segmentation; explores the limitations of a Random Forest algorithm applied to the CT environment; and demonstrates segmentation accuracy in a feasibility study of pediatric and adult patients. To the best of our knowledge, this is the first study to investigate a trainable Weka segmentation (TWS) implementation using Random Forest machine-learning as a means to develop a fully automated tissue segmentation tool developed specifically for pediatric and adult examinations in a diagnostic CT environment. Current innovation in computed tomography (CT) is focused on radiomics, patient-specific radiation dose calculation, and image quality improvement using iterative reconstruction, all of which require specific knowledge of tissue and organ systems within a CT image. The purpose of this study was to develop a fully automated Random Forest classifier algorithm for segmentation of neck–chest–abdomen–pelvis CT examinations based on pediatric and adult CT protocols. Seven materials were classified: background, lung/internal air or gas, fat, muscle, solid organ parenchyma, blood/contrast enhanced fluid, and bone tissue using Matlab and the TWS plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance evaluated over a voxel radius of 2 n , (n from 0 to 4), along with noise reduction and edge preserving filters: Gaussian, bilateral, Kuwahara, and anisotropic diffusion. The Random Forest algorithm used 200 trees with 2 features randomly selected per node. The optimized auto-segmentation algorithm resulted in 16 image features including features derived from maximum, mean, variance Gaussian and Kuwahara filters. Dice similarity coefficient (DSC) calculations between manually segmented and Random Forest algorithm segmented images from 21

  5. Tissue segmentation of computed tomography images using a Random Forest algorithm: a feasibility study

    Science.gov (United States)

    Polan, Daniel F.; Brady, Samuel L.; Kaufman, Robert A.

    2016-09-01

    There is a need for robust, fully automated whole body organ segmentation for diagnostic CT. This study investigates and optimizes a Random Forest algorithm for automated organ segmentation; explores the limitations of a Random Forest algorithm applied to the CT environment; and demonstrates segmentation accuracy in a feasibility study of pediatric and adult patients. To the best of our knowledge, this is the first study to investigate a trainable Weka segmentation (TWS) implementation using Random Forest machine-learning as a means to develop a fully automated tissue segmentation tool developed specifically for pediatric and adult examinations in a diagnostic CT environment. Current innovation in computed tomography (CT) is focused on radiomics, patient-specific radiation dose calculation, and image quality improvement using iterative reconstruction, all of which require specific knowledge of tissue and organ systems within a CT image. The purpose of this study was to develop a fully automated Random Forest classifier algorithm for segmentation of neck-chest-abdomen-pelvis CT examinations based on pediatric and adult CT protocols. Seven materials were classified: background, lung/internal air or gas, fat, muscle, solid organ parenchyma, blood/contrast enhanced fluid, and bone tissue using Matlab and the TWS plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance evaluated over a voxel radius of 2 n , (n from 0 to 4), along with noise reduction and edge preserving filters: Gaussian, bilateral, Kuwahara, and anisotropic diffusion. The Random Forest algorithm used 200 trees with 2 features randomly selected per node. The optimized auto-segmentation algorithm resulted in 16 image features including features derived from maximum, mean, variance Gaussian and Kuwahara filters. Dice similarity coefficient (DSC) calculations between manually segmented and Random Forest algorithm segmented images from 21

  6. Applied anatomy of the atlantal segment of the vertebral artery%椎动脉寰椎部的应用解剖

    Institute of Scientific and Technical Information of China (English)

    郭徐华; 高宜录; 金国华

    2012-01-01

    Objective: To study the anatomy of the atlantal segment of the vertebral artery and to provide the basis of micro-vascular anatomy for clinical treatment. Methods: Adult cadaver heads were dissected in the study, and the morphology of the atlantal segment of the vertebral arteries were observed; The dimensions of the atlantal segment of vertebral arteries and their adjacent structures were measured. Results: The atlantal segments of the vertebral artery was divided into occipo-atlan-tal segment and atlanto-axoidean segment. The atlantal segment of vertebral artery had four permanent and continuous blood vessel loops. There were abundant paravertebral venous plexus around the atlantal segment of the vertebral artery. The anterior root of C2 permanent sticking to dorsal of occipo-atlantal segment of atlantal segment of the vertebral artery. Conclusion: The anatomy of the atlantal segment of vertebral artery and their adjacent structures have great clinical significance to avoid damaging the vertebral artery in a far lateral operative approach.%目的:研究椎动脉寰椎部的解剖,为临床应用提供解剖学依据.方法:成人尸头标本,解剖观察椎动脉寰椎部的形态结构,测量椎动脉寰椎部及其毗邻结构.结果:椎动脉寰椎部可分为寰枕段及寰枢椎段2部分;椎动脉寰椎部有恒定而连续的4个血管襻;周围有丰富的椎旁静脉丛,第2颈椎神经前根恒定地紧贴于椎动脉寰椎部寰枕段背侧.结论:对椎动脉寰椎部的解剖及其毗邻结构的研究,对于远外侧手术入路中避免椎动脉的损伤有重大临床意义.

  7. DDoS Defense Algorithm Based on Multi-Segment Timeout Technology

    Institute of Scientific and Technical Information of China (English)

    DU Ruizhong; YANG Xiaohui; MA Xiaoxue; HE Xinfeng

    2006-01-01

    Through the analysis to the DDoS(distributed denial of service) attack, it will conclude that at different time segments, the arrive rate of normal SYN (Synchronization) package are similar, while the abnormal packages are different with the normal ones. Toward this situation a DDoS defense algorithm based on multi-segment timeout technology is presented, more than one timeout segment are set to control the net flow. Experiment results show that in the case of little flow, multi-segment timeout has the ability dynamic defense, so the system performance is improved and the system has high response rate.

  8. New CSC Segment Builder Algorithm with MC TeV Muons in CMS Experiment

    CERN Document Server

    Voytishin, Nikolay

    2016-01-01

    The performance of the new Cathode Strip Chamber segment builder algorithm with simulated TeV muons is considered. The comparison of some of the main reconstruction characteristics is made. Some case study events are visualized in order to illustrate the improvement that the new algorithm gives to the reconstruction process.

  9. Coupling Regular Tessellation with Rjmcmc Algorithm to Segment SAR Image with Unknown Number of Classes

    Science.gov (United States)

    Wang, Y.; Li, Y.; Zhao, Q. H.

    2016-06-01

    This paper presents a Synthetic Aperture Radar (SAR) image segmentation approach with unknown number of classes, which is based on regular tessellation and Reversible Jump Markov Chain Monte Carlo (RJMCMC') algorithm. First of all, an image domain is portioned into a set of blocks by regular tessellation. The image is modeled on the assumption that intensities of its pixels in each homogeneous region satisfy an identical and independent Gamma distribution. By Bayesian paradigm, the posterior distribution is obtained to build the region-based image segmentation model. Then, a RJMCMC algorithm is designed to simulate from the segmentation model to determine the number of homogeneous regions and segment the image. In order to further improve the segmentation accuracy, a refined operation is performed. To illustrate the feasibility and effectiveness of the proposed approach, two real SAR image is tested.

  10. Parallel Implementation of the Recursive Approximation of an Unsupervised Hierarchical Segmentation Algorithm. Chapter 5

    Science.gov (United States)

    Tilton, James C.; Plaza, Antonio J. (Editor); Chang, Chein-I. (Editor)

    2008-01-01

    The hierarchical image segmentation algorithm (referred to as HSEG) is a hybrid of hierarchical step-wise optimization (HSWO) and constrained spectral clustering that produces a hierarchical set of image segmentations. HSWO is an iterative approach to region grooving segmentation in which the optimal image segmentation is found at N(sub R) regions, given a segmentation at N(sub R+1) regions. HSEG's addition of constrained spectral clustering makes it a computationally intensive algorithm, for all but, the smallest of images. To counteract this, a computationally efficient recursive approximation of HSEG (called RHSEG) has been devised. Further improvements in processing speed are obtained through a parallel implementation of RHSEG. This chapter describes this parallel implementation and demonstrates its computational efficiency on a Landsat Thematic Mapper test scene.

  11. Optree: a learning-based adaptive watershed algorithm for neuron segmentation.

    Science.gov (United States)

    Uzunbaş, Mustafa Gökhan; Chen, Chao; Metaxas, Dimitris

    2014-01-01

    We present a new algorithm for automatic and interactive segmentation of neuron structures from electron microscopy (EM) images. Our method selects a collection of nodes from the watershed mergng tree as the proposed segmentation. This is achieved by building a onditional random field (CRF) whose underlying graph is the merging tree. The maximum a posteriori (MAP) prediction of the CRF is the output segmentation. Our algorithm outperforms state-of-the-art methods. Both the inference and the training are very efficient as the graph is tree-structured. Furthermore, we develop an interactive segmentation framework which selects uncertain regions for a user to proofread. The uncertainty is measured by the marginals of the graphical model. Based on user corrections, our framework modifies the merging tree and thus improves the segmentation globally. PMID:25333106

  12. Improved Fuzzy C-Means Algorithm for MR Brain Image Segmentation

    Directory of Open Access Journals (Sweden)

    P.Vasuda,

    2010-08-01

    Full Text Available Segmentation is an important aspect of medical image processing, where Clustering approach is widely used in biomedical applications particularly for brain tumor detection in abnormal Magnetic Resonance Images (MRI. Fuzzy clustering using Fuzzy C- Means (FCM algorithm proved to be superior over the other clustering approaches in terms of segmentation efficiency. But the major drawback of the FCM algorithm is the huge computational time required for convergence. Theeffectiveness of the FCM algorithm in terms of computational rate is improved by modifying the cluster center and membership value updation criterion. In this paper, convergence rate is compared between the conventional FCM and the Improved FCM.

  13. IMPROVED ALGORITHM FOR ROAD REGION SEGMENTATION BASED ON SEQUENTIAL MONTE-CARLO ESTIMATION

    Directory of Open Access Journals (Sweden)

    Zdenek Prochazka

    2014-12-01

    Full Text Available In recent years, many researchers and car makers put a lot of intensive effort into development of autonomous driving systems. Since visual information is the main modality used by human driver, a camera mounted on moving platform is very important kind of sensor, and various computer vision algorithms to handle vehicle surrounding situation are under intensive research. Our final goal is to develop a vision based lane detection system with ability to handle various types of road shapes, working on both structured and unstructured roads, ideally under presence of shadows. This paper presents a modified road region segmentation algorithm based on sequential Monte-Carlo estimation. Detailed description of the algorithm is given, and evaluation results show that the proposed algorithm outperforms the segmentation algorithm developed as a part of our previous work, as well as an conventional algorithm based on colour histogram.

  14. SEGMENTATION ALGORITHM BASED ON EDGE-SEARCHING FOR MUlTI-LINEAR STRUCTURED LIGHT IMAGES

    Institute of Scientific and Technical Information of China (English)

    LIU Baohua; LI Bing; JIANG Zhuangde

    2006-01-01

    Aiming at the problem that the existence of disturbances on the edges of light-stripe makes the segmentation of the light-stripes images difficult, a new segmentation algorithm based on edge-searching is presented. It firstly calculates every edge pixel's horizontal coordinate grads to produce the corresponding grads-edge, then uses a designed length-variable 1D template to scan the light-stripes' grads-edges. The template is able to fmd the disturbances with different width utilizing the distributing character of the edge disturbances. The found disturbances are eliminated finally. The algorithm not only can smoothly segment the light-stripes images, but also eliminate most disturbances on the light-stripes' edges without damaging the light-stripes images' 3D information. A practical example of using the proposed algorithm is given in the end. It is proved that the efficiency of the algorithm has been improved obviously by comparison.

  15. An Approach to a Comprehensive Test Framework for Analysis and Evaluation of Text Line Segmentation Algorithms

    Directory of Open Access Journals (Sweden)

    Zoran N. Milivojevic

    2011-09-01

    Full Text Available The paper introduces a testing framework for the evaluation and validation of text line segmentation algorithms. Text line segmentation represents the key action for correct optical character recognition. Many of the tests for the evaluation of text line segmentation algorithms deal with text databases as reference templates. Because of the mismatch, the reliable testing framework is required. Hence, a new approach to a comprehensive experimental framework for the evaluation of text line segmentation algorithms is proposed. It consists of synthetic multi-like text samples and real handwritten text as well. Although the tests are mutually independent, the results are cross-linked. The proposed method can be used for different types of scripts and languages. Furthermore, two different procedures for the evaluation of algorithm efficiency based on the obtained error type classification are proposed. The first is based on the segmentation line error description, while the second one incorporates well-known signal detection theory. Each of them has different capabilities and convenience, but they can be used as supplements to make the evaluation process efficient. Overall the proposed procedure based on the segmentation line error description has some advantages, characterized by five measures that describe measurement procedures.

  16. A hybrid algorithm for instant optimization of beam weights in anatomy-based intensity modulated radiotherapy: a performance evaluation study

    International Nuclear Information System (INIS)

    The study aims to introduce a hybrid optimization algorithm for anatomy-based intensity modulated radiotherapy (AB-IMRT). Our proposal is that by integrating an exact optimization algorithm with a heuristic optimization algorithm, the advantages of both the algorithms can be combined, which will lead to an efficient global optimizer solving the problem at a very fast rate. Our hybrid approach combines Gaussian elimination algorithm (exact optimizer) with fast simulated annealing algorithm (a heuristic global optimizer) for the optimization of beam weights in AB-IMRT. The algorithm has been implemented using MATLAB software. The optimization efficiency of the hybrid algorithm is clarified by (i) analysis of the numerical characteristics of the algorithm and (ii) analysis of the clinical capabilities of the algorithm. The numerical and clinical characteristics of the hybrid algorithm are compared with Gaussian elimination method (GEM) and fast simulated annealing (FSA). The numerical characteristics include convergence, consistency, number of iterations and overall optimization speed, which were analyzed for the respective cases of 8 patients. The clinical capabilities of the hybrid algorithm are demonstrated in cases of (a) prostate and (b) brain. The analyses reveal that (i) the convergence speed of the hybrid algorithm is approximately three times higher than that of FSA algorithm (ii) the convergence (percentage reduction in the cost function) in hybrid algorithm is about 20% improved as compared to that in GEM algorithm (iii) the hybrid algorithm is capable of producing relatively better treatment plans in terms of Conformity Index (CI) (∼ 2% - 5% improvement) and Homogeneity Index (HI) (∼ 4% - 10% improvement) as compared to GEM and FSA algorithms (iv) the sparing of organs at risk in hybrid algorithm-based plans is better than that in GEM-based plans and comparable to that in FSA-based plans; and (v) the beam weights resulting from the hybrid algorithm are

  17. Knowledge Automatic Indexing Based on Concept Lexicon and Segmentation Algorithm

    Institute of Scientific and Technical Information of China (English)

    WANG Lan-cheng; JIANG Dan; LE Jia-jin

    2005-01-01

    This paper is based on two existing theories about automatic indexing of thematic knowledge concept. The prohibit-word table with position information has been designed. The improved Maximum Matching-Minimum Backtracking method has been researched. Moreover it has been studied on improved indexing algorithm and application technology based on rules and thematic concept word table.

  18. A comparative study of automatic image segmentation algorithms for target tracking in MR-IGRT.

    Science.gov (United States)

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

    2016-01-01

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

  19. Side scan sonar image segmentation based on neutrosophic set and quantum-behaved particle swarm optimization algorithm

    Science.gov (United States)

    Zhao, Jianhu; Wang, Xiao; Zhang, Hongmei; Hu, Jun; Jian, Xiaomin

    2016-09-01

    To fulfill side scan sonar (SSS) image segmentation accurately and efficiently, a novel segmentation algorithm based on neutrosophic set (NS) and quantum-behaved particle swarm optimization (QPSO) is proposed in this paper. Firstly, the neutrosophic subset images are obtained by transforming the input image into the NS domain. Then, a co-occurrence matrix is accurately constructed based on these subset images, and the entropy of the gray level image is described to serve as the fitness function of the QPSO algorithm. Moreover, the optimal two-dimensional segmentation threshold vector is quickly obtained by QPSO. Finally, the contours of the interested target are segmented with the threshold vector and extracted by the mathematic morphology operation. To further improve the segmentation efficiency, the single threshold segmentation, an alternative algorithm, is recommended for the shadow segmentation by considering the gray level characteristics of the shadow. The accuracy and efficiency of the proposed algorithm are assessed with experiments of SSS image segmentation.

  20. A New Image Threshold Segmentation based on Fuzzy Entropy and Improved Intelligent Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Yong-sheng Wang

    2014-04-01

    Full Text Available Image segmentation is one of the key techniques in the field of image understanding and computer vision. To determine the optimal threshold in image segmentation, an effective image threshold segmentation method based on fuzzy logic is presented. A new kind of fuzzy entropy is defined, that is not only related to the membership, but also related to probability distribution. According to the maximum entropy criterion, the improved particle swarm optimization algorithm based on chaos bee colony is used to determine the optimal parameters of membership function to automatically determine the optimal threshold segmentation. The experiment results show that proposed algorithm based on fuzzy entropy and chaos bee colony particle swarm optimization has good performance.

  1. Analysis of Speed Sign Classification Algorithms Using Shape Based Segmentation of Binary Images

    OpenAIRE

    Muhammad, Azam Sheikh; Lavesson, Niklas; Davidsson, Paul; Nilsson, Mikael

    2009-01-01

    Traffic Sign Recognition is a widely studied problem and its dynamic nature calls for the application of a broad range of preprocessing, segmentation, and recognition techniques but few databases are available for evaluation. We have produced a database consisting of 1,300 images captured by a video camera. On this database we have conducted a systematic experimental study. We used four different preprocessing techniques and designed a generic speed sign segmentation algorithm. Then we select...

  2. Efficient Recursive Algorithms for Computing the Mean Diffusion Tensor and Applications to DTI Segmentation(★)

    Science.gov (United States)

    Cheng, Guang; Salehian, Hesamoddin; Vemuri, Baba C

    2012-01-01

    Computation of the mean of a collection of symmetric positive definite (SPD) matrices is a fundamental ingredient of many algorithms in diffusion tensor image (DTI) processing. For instance, in DTI segmentation, clustering, etc. In this paper, we present novel recursive algorithms for computing the mean of a set of diffusion tensors using several distance/divergence measures commonly used in DTI segmentation and clustering such as the Riemannian distance and symmetrized Kullback-Leibler divergence. To the best of our knowledge, to date, there are no recursive algorithms for computing the mean using these measures in literature. Recursive algorithms lead to a gain in computation time of several orders in magnitude over existing non-recursive algorithms. The key contributions of this paper are: (i) we present novel theoretical results on a recursive estimator for Karcher expectation in the space of SPD matrices, which in effect is a proof of the law of large numbers (with some restrictions) for the manifold of SPD matrices. (ii) We also present a recursive version of the symmetrized KL-divergence for computing the mean of a collection of SPD matrices. (iii) We present comparative timing results for computing the mean of a group of SPD matrices (diffusion tensors) depicting the gains in compute time using the proposed recursive algorithms over existing non-recursive counter parts. Finally, we also show results on gains in compute times obtained by applying these recursive algorithms to the task of DTI segmentation.

  3. Urinary stone size estimation: a new segmentation algorithm-based CT method

    Energy Technology Data Exchange (ETDEWEB)

    Liden, Mats; Geijer, Haakan [Oerebro University, School of Health and Medical Sciences, Oerebro (Sweden); Oerebro University Hospital, Department of Radiology, Oerebro (Sweden); Andersson, Torbjoern [Oerebro University, School of Health and Medical Sciences, Oerebro (Sweden); Broxvall, Mathias [Oerebro University, Centre for Modelling and Simulation, Oerebro (Sweden); Thunberg, Per [Oerebro University, School of Health and Medical Sciences, Oerebro (Sweden); Oerebro University Hospital, Department of Medical Physics, Oerebro (Sweden)

    2012-04-15

    The size estimation in CT images of an obstructing ureteral calculus is important for the clinical management of a patient presenting with renal colic. The objective of the present study was to develop a reader independent urinary calculus segmentation algorithm using well-known digital image processing steps and to validate the method against size estimations by several readers. Fifty clinical CT examinations demonstrating urinary calculi were included. Each calculus was measured independently by 11 readers. The mean value of their size estimations was used as validation data for each calculus. The segmentation algorithm consisted of interpolated zoom, binary thresholding and morphological operations. Ten examinations were used for algorithm optimisation and 40 for validation. Based on the optimisation results three segmentation method candidates were identified. Between the primary segmentation algorithm using cubic spline interpolation and the mean estimation by 11 readers, the bias was 0.0 mm, the standard deviation of the difference 0.26 mm and the Bland-Altman limits of agreement 0.0{+-}0.5 mm. The validation showed good agreement between the suggested algorithm and the mean estimation by a large number of readers. The limit of agreement was narrower than the inter-reader limit of agreement previously reported for the same data. (orig.)

  4. An audio-based sports video segmentation and event detection algorithm

    OpenAIRE

    Baillie, M.; Jose, J.M.

    2004-01-01

    In this paper, we present an audio-based event detection algorithm shown to be effective when applied to Soccer video. The main benefit of this approach is the ability to recognise patterns that display high levels of crowd response correlated to key events. The soundtrack from a Soccer sequence is first parameterised using Mel-frequency Cepstral coefficients. It is then segmented into homogenous components using a windowing algorithm with a decision process based on Bayesian model selection....

  5. An evolutionary algorithm for the segmentation of muscles and bones of the lower limb.

    Science.gov (United States)

    Lpez, Marco A.; Braidot, A.; Sattler, Anbal; Schira, Claudia; Uriburu, E.

    2016-04-01

    In the field of medical image segmentation, muscles segmentation is a problem that has not been fully resolved yet. This is due to the fact that the basic assumption of image segmentation, which asserts that a visual distinction should ex- ist between the different structures to be identified, is infringed. As the tissue composition of two different muscles is the same, it becomes extremely difficult to distinguish one another if they are near. We have developed an evolutionary algorithm which selects the set and the sequence of morphological operators that better segments muscles and bones from an MRI image. The achieved results shows that the developed algorithm presents average sensitivity values close to 75% in the segmentation of the different processed muscles and bones. It also presents average specificity values close to 93% for the same structures. Furthermore, the algorithm can identify muscles that are closely located through the path from their origin point to their insertions, with very low error values (below 7%) .

  6. Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge.

    Science.gov (United States)

    Litjens, Geert; Toth, Robert; van de Ven, Wendy; Hoeks, Caroline; Kerkstra, Sjoerd; van Ginneken, Bram; Vincent, Graham; Guillard, Gwenael; Birbeck, Neil; Zhang, Jindang; Strand, Robin; Malmberg, Filip; Ou, Yangming; Davatzikos, Christos; Kirschner, Matthias; Jung, Florian; Yuan, Jing; Qiu, Wu; Gao, Qinquan; Edwards, Philip Eddie; Maan, Bianca; van der Heijden, Ferdinand; Ghose, Soumya; Mitra, Jhimli; Dowling, Jason; Barratt, Dean; Huisman, Henkjan; Madabhushi, Anant

    2014-02-01

    Prostate MRI image segmentation has been an area of intense research due to the increased use of MRI as a modality for the clinical workup of prostate cancer. Segmentation is useful for various tasks, e.g. to accurately localize prostate boundaries for radiotherapy or to initialize multi-modal registration algorithms. In the past, it has been difficult for research groups to evaluate prostate segmentation algorithms on multi-center, multi-vendor and multi-protocol data. Especially because we are dealing with MR images, image appearance, resolution and the presence of artifacts are affected by differences in scanners and/or protocols, which in turn can have a large influence on algorithm accuracy. The Prostate MR Image Segmentation (PROMISE12) challenge was setup to allow a fair and meaningful comparison of segmentation methods on the basis of performance and robustness. In this work we will discuss the initial results of the online PROMISE12 challenge, and the results obtained in the live challenge workshop hosted by the MICCAI2012 conference. In the challenge, 100 prostate MR cases from 4 different centers were included, with differences in scanner manufacturer, field strength and protocol. A total of 11 teams from academic research groups and industry participated. Algorithms showed a wide variety in methods and implementation, including active appearance models, atlas registration and level sets. Evaluation was performed using boundary and volume based metrics which were combined into a single score relating the metrics to human expert performance. The winners of the challenge where the algorithms by teams Imorphics and ScrAutoProstate, with scores of 85.72 and 84.29 overall. Both algorithms where significantly better than all other algorithms in the challenge (palgorithm performance was good to excellent and the Imorphics algorithm outperformed the second observer on average, we showed that algorithm combination might lead to further improvement, indicating

  7. Statistical Analysis for Performance Evaluation of Image Segmentation Quality Using Edge Detection Algorithms

    Directory of Open Access Journals (Sweden)

    T. Venkat Narayana Rao

    2011-11-01

    Full Text Available Edge detection is the most important feature of image processing for object detection, it is crucial to have a good understanding of edge detection algorithms/operators. Computer vision is rapidly expanding field that depends on the capability to perform faster segments and thus to classify and infer images. Segmentation is central to the successful extraction of image features and their ensuing classification. Powerful segmentation techniques are available; however each technique is ad hoc. In this paper, the computer vision investigates the sub regions of the composite image, brings out commonly used and most important edge detection algorithms/operators with a wide-ranging comparative along with the statistical approach. This paper implements popular algorithms such as Sobel, Roberts, Prewitt, Laplacian of Gaussian and canny. A standard metric is used for evaluating the performance degradation of edge detection algorithms as a function of Peak Signal to Noise Ratio (PSNR along with the elapsed time for generating the segmented output image. A statistical approach to evaluate the variance among the PSNR and the time elapsed in output image is also incorporated. This paper provides a basis for objectively comparing the performance of different techniques and quantifies relative noise tolerance. Results shown allow selection of the most optimum method for application to image.

  8. A Decision-Tree-Based Algorithm for Speech/Music Classification and Segmentation

    Directory of Open Access Journals (Sweden)

    Lavner Yizhar

    2009-01-01

    Full Text Available We present an efficient algorithm for segmentation of audio signals into speech or music. The central motivation to our study is consumer audio applications, where various real-time enhancements are often applied. The algorithm consists of a learning phase and a classification phase. In the learning phase, predefined training data is used for computing various time-domain and frequency-domain features, for speech and music signals separately, and estimating the optimal speech/music thresholds, based on the probability density functions of the features. An automatic procedure is employed to select the best features for separation. In the test phase, initial classification is performed for each segment of the audio signal, using a three-stage sieve-like approach, applying both Bayesian and rule-based methods. To avoid erroneous rapid alternations in the classification, a smoothing technique is applied, averaging the decision on each segment with past segment decisions. Extensive evaluation of the algorithm, on a database of more than 12 hours of speech and more than 22 hours of music showed correct identification rates of 99.4% and 97.8%, respectively, and quick adjustment to alternating speech/music sections. In addition to its accuracy and robustness, the algorithm can be easily adapted to different audio types, and is suitable for real-time operation.

  9. An Adaptive Frame Skipping and VOP Interpolation Algorithm for Video Object Segmentation

    Institute of Scientific and Technical Information of China (English)

    YANGGaobo; ZHANGZhaoyang

    2004-01-01

    Video object segmentation is a key step for the successful use of MPEG-4. However, most of the current available segmentation algorithms are still far away from real-time performance. In order to improve the processing speed, an adaptive frame skipping and VOP interpolation algorithm is proposed in this paper. It adaptively determines the number of skipped frames based on the rigidity and motion complexity of video object. To interpolate the VOPs for skipped frames, a hi-directional projection scheme is adopted. Its principle is to perform a classification of those regions obtained by spatial segmentation for every frame in the sequence. It is valid for both rigid object and non-rigid object and can get good localization of object boundaries. Experimental results show that the proposed approach can improve the processing speed greatly while maintaining visually pleasant results.

  10. On the importance of FIB-SEM specific segmentation algorithms for porous media

    Energy Technology Data Exchange (ETDEWEB)

    Salzer, Martin, E-mail: martin.salzer@uni-ulm.de [Institute of Stochastics, Faculty of Mathematics and Economics, Ulm University, D-89069 Ulm (Germany); Thiele, Simon, E-mail: simon.thiele@imtek.uni-freiburg.de [Laboratory for MEMS Applications, IMTEK, Department of Microsystems Engineering, University of Freiburg, D-79110 Freiburg (Germany); Zengerle, Roland, E-mail: zengerle@imtek.uni-freiburg.de [Laboratory for MEMS Applications, IMTEK, Department of Microsystems Engineering, University of Freiburg, D-79110 Freiburg (Germany); Schmidt, Volker, E-mail: volker.schmidt@uni-ulm.de [Institute of Stochastics, Faculty of Mathematics and Economics, Ulm University, D-89069 Ulm (Germany)

    2014-09-15

    A new algorithmic approach to segmentation of highly porous three dimensional image data gained by focused ion beam tomography is described which extends the key-principle of local threshold backpropagation described in Salzer et al. (2012). The technique of focused ion beam tomography has shown to be capable of imaging the microstructure of functional materials. In order to perform a quantitative analysis on the corresponding microstructure a segmentation task needs to be performed. However, algorithmic segmentation of images obtained with focused ion beam tomography is a challenging problem for highly porous materials if filling the pore phase, e.g. with epoxy resin, is difficult. The gray intensities of individual voxels are not sufficient to determine the phase represented by them and usual thresholding methods are not applicable. We thus propose a new approach to segmentation that pays respect to the specifics of the imaging process of focused ion beam tomography. As an application of our approach, the segmentation of three dimensional images for a cathode material used in polymer electrolyte membrane fuel cells is discussed. We show that our approach preserves significantly more of the original nanostructure than a thresholding approach. - Highlights: • We describe a new approach to the segmentation of FIB-SEM images of porous media. • The first and last occurrences of structures are detected by analysing the z-profiles. • The algorithm is validated by comparing it to a manual segmentation. • The new approach shows significantly less artifacts than a thresholding approach. • A structural analysis also shows improved results for the obtained microstructure.

  11. Segmentation and Classification of Brain MRI Images Using Improved Logismos-B Algorithm

    Directory of Open Access Journals (Sweden)

    S. Dilip kumar

    2014-12-01

    Full Text Available Automated reconstruction and diagnosis of brain MRI images is one of the most challenging problems in medical imaging. Accurate segmentation of MRI images is a key step in contouring during radiotherapy analysis. Computed tomography (CT and Magnetic resonance (MR imaging are the most widely used radiographic techniques in diagnosis and treatment planning. Segmentation techniques used for the brain Magnetic Resonance Imaging (MRI is one of the methods used by the radiographer to detect any abnormality specifically in brain. The method also identifies important regions in brain such as white matter (WM, gray matter (GM and cerebrospinal fluid spaces (CSF. These regions are significant for physician or radiographer to analyze and diagnose the disease. We propose a novel clustering algorithm, improved LOGISMOS-B to classify tissue regions based on probabilistic tissue classification, generalized gradient vector flows with cost and distance function. The LOGISMOS graph segmentation framework. Expand the framework to allow regionally-aware graph construction and segmentation

  12. High-speed MRF-based segmentation algorithm using pixonal images

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan; Hassanpour, H.; Naimi, H. M.

    2013-01-01

    Segmentation is one of the most complicated procedures in the image processing that has important role in the image analysis. In this paper, an improved pixon-based method for image segmentation is proposed. In proposed algorithm, complex partial differential equations (PDEs) is used as a kernel...... function to make pixonal image. Using this kernel function causes noise on images to reduce and an image not to be over-segment when the pixon-based method is used. Utilising the PDE-based method leads to elimination of some unnecessary details and results in a fewer pixon number, faster performance...... and more robustness against unwanted environmental noises. As the next step, the appropriate pixons are extracted and eventually, we segment the image with the use of a Markov random field. The experimental results indicate that the proposed pixon-based approach has a reduced computational load...

  13. 3D segmentation of medical images using a fast multistage hybrid algorithm

    International Nuclear Information System (INIS)

    In this paper, we propose a fast multistage hybrid algorithm for 3D segmentation of medical images. We first employ a morphological recursive erosion operation to reduce the connectivity between the object to be segmented and its neighborhood; then the fast marching method is used to greatly accelerate the initial propagation of a surface front from the user defined seed structure to a surface close to the desired boundary; a morphological reconstruction method then operates on this surface to achieve an initial segmentation result; and finally morphological recursive dilation is employed to recover any structure lost in the first stage of the algorithm. This approach is tested on 60 CT or MRI images of the brain, heart and urinary system, to demonstrate the robustness of this technique across a variety of imaging modalities and organ systems. The algorithm is also validated against datasets for which ''truth'' is known. These measurements revealed that the algorithm achieved a mean ''similarity index'' of 0.966 across the three organ systems. The execution time for this algorithm, when run on a 550 MHz Dual PIII-based PC runningWindows NT, and extracting the cortex from brain MRIs, the cardiac surface from dynamic CT, and the kidneys from 3D CT, was 38, 46 and 23 s, respectively. (orig.)

  14. Hopfield-K-Means clustering algorithm: A proposal for the segmentation of electricity customers

    Energy Technology Data Exchange (ETDEWEB)

    Lopez, Jose J.; Aguado, Jose A.; Martin, F.; Munoz, F.; Rodriguez, A.; Ruiz, Jose E. [Department of Electrical Engineering, University of Malaga, C/ Dr. Ortiz Ramos, sn., Escuela de Ingenierias, 29071 Malaga (Spain)

    2011-02-15

    Customer classification aims at providing electric utilities with a volume of information to enable them to establish different types of tariffs. Several methods have been used to segment electricity customers, including, among others, the hierarchical clustering, Modified Follow the Leader and K-Means methods. These, however, entail problems with the pre-allocation of the number of clusters (Follow the Leader), randomness of the solution (K-Means) and improvement of the solution obtained (hierarchical algorithm). Another segmentation method used is Hopfield's autonomous recurrent neural network, although the solution obtained only guarantees that it is a local minimum. In this paper, we present the Hopfield-K-Means algorithm in order to overcome these limitations. This approach eliminates the randomness of the initial solution provided by K-Means based algorithms and it moves closer to the global optimun. The proposed algorithm is also compared against other customer segmentation and characterization techniques, on the basis of relative validation indexes. Finally, the results obtained by this algorithm with a set of 230 electricity customers (residential, industrial and administrative) are presented. (author)

  15. Vessel Segmentation in Medical Imaging Using a Tight-Frame Based Algorithm

    CERN Document Server

    Cai, Xiaohao; Morigi, Serena; Sgallari, Fiorella

    2011-01-01

    Tight-frame, a generalization of orthogonal wavelets, has been used successfully in various problems in image processing, including inpainting, impulse noise removal, super-resolution image restoration, etc. Segmentation is the process of identifying object outlines within images. There are quite a few efficient algorithms for segmentation that depend on the variational approach and the partial differential equation (PDE) modeling. In this paper, we propose to apply the tight-frame approach to automatically identify tube-like structures such as blood vessels in Magnetic Resonance Angiography (MRA) images. Our method iteratively refines a region that encloses the possible boundary or surface of the vessels. In each iteration, we apply the tight-frame algorithm to denoise and smooth the possible boundary and sharpen the region. We prove the convergence of our algorithm. Numerical experiments on real 2D/3D MRA images demonstrate that our method is very efficient with convergence usually within a few iterations, ...

  16. The Research of ECG Signal Automatic Segmentation Algorithm Based on Fractal Dimension Trajectory

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    <正>In this paper a kind of ECG signal automatic segmentation algorithm based on ECG fractal dimension trajectory is put forward.First,the ECG signal will be analyzed,then constructing the fractal dimension trajectory of ECG signal according to the fractal dimension trajectory constructing algorithm,finally,obtaining ECG signal feature points and ECG automatic segmentation will be realized by the feature of ECG signal fractal dimension trajectory and the feature of ECG frequency domain characteristics.Through Matlab simulation of the algorithm,the results showed that by constructing the ECG fractal dimension trajectory enables ECG location of each component displayed clearly and obtains high success rate of sub-ECG,providing a basis to identify the various components of ECG signal accurately.

  17. A Novel Pixon-Based Image Segmentation Process Using Fuzzy Filtering and Fuzzy C-mean Algorithm

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan; Barari, Amin

    2011-01-01

    Image segmentation, which is an important stage of many image processing algorithms, is the process of partitioning an image into nonintersecting regions, such that each region is homogeneous and the union of no two adjacent regions is homogeneous. This paper presents a novel pixon-based algorithm...... for image segmentation. The key idea is to create a pixon model by combining fuzzy filtering as a kernel function and a fuzzy c-means clustering algorithm for image segmentation. Use of fuzzy filters reduces noise and slightly smoothes the image. Use of the proposed pixon model prevented image over-segmentation...

  18. Analyzing the medical image by using clustering algorithms through segmentation process

    Science.gov (United States)

    Kumar, Papendra; Kumar, Suresh

    2012-01-01

    Basic aim of our study is to analyze the medical image. In computer vision, segmentationRefers to the process of partitioning a digital image into multiple regions. The goal ofSegmentation is to simplify and/or change the representation of an image into something thatIs more meaningful and easier to analyze. Image segmentation is typically used to locateObjects and boundaries (lines, curves, etc.) in images.There is a lot of scope of the analysis that we have done in our project; our analysis couldBe used for the purpose of monitoring the medical image. Medical imaging refers to theTechniques and processes used to create images of the human body (or parts thereof) forClinical purposes (medical procedures seeking to reveal, diagnose or examine disease) orMedical science (including the study of normal anatomy and function).As a discipline and in its widest sense, it is part of biological imaging and incorporatesRadiology (in the wider sense), radiological sciences, endoscopy, (medical) thermography, Medical photography and microscopy (e.g. for human pathological investigations).Measurement and recording techniques which are not primarily designed to produce images.

  19. Brain tumor segmentation in MR slices using improved GrowCut algorithm

    Science.gov (United States)

    Ji, Chunhong; Yu, Jinhua; Wang, Yuanyuan; Chen, Liang; Shi, Zhifeng; Mao, Ying

    2015-12-01

    The detection of brain tumor from MR images is very significant for medical diagnosis and treatment. However, the existing methods are mostly based on manual or semiautomatic segmentation which are awkward when dealing with a large amount of MR slices. In this paper, a new fully automatic method for the segmentation of brain tumors in MR slices is presented. Based on the hypothesis of the symmetric brain structure, the method improves the interactive GrowCut algorithm by further using the bounding box algorithm in the pre-processing step. More importantly, local reflectional symmetry is used to make up the deficiency of the bounding box method. After segmentation, 3D tumor image is reconstructed. We evaluate the accuracy of the proposed method on MR slices with synthetic tumors and actual clinical MR images. Result of the proposed method is compared with the actual position of simulated 3D tumor qualitatively and quantitatively. In addition, our automatic method produces equivalent performance as manual segmentation and the interactive GrowCut with manual interference while providing fully automatic segmentation.

  20. Characterization of mammographic masses using a gradient-based segmentation algorithm and a neural classifier

    CERN Document Server

    Delogu, P; Kasae, P; Retico, A

    2008-01-01

    The computer-aided diagnosis system we developed for the mass characterization is mainly based on a segmentation algorithm and on the neural classification of several features computed on the segmented mass. Mass segmentation plays a key role in most computerized systems. Our technique is a gradient-based one, showing the main characteristic that no free parameters have been evaluated on the dataset used in this analysis, thus it can directly be applied to datasets acquired in different conditions without any ad-hoc modification. A dataset of 226 masses (109 malignant and 117 benign) has been used in this study. The segmentation algorithm works with a comparable efficiency both on malignant and benign masses. Sixteen features based on shape, size and intensity of the segmented masses are analyzed by a multi-layered perceptron neural network. A feature selection procedure has been carried out on the basis of the feature discriminating power and of the linear correlations interplaying among them. The comparison...

  1. A Light-and-Fast SLAM Algorithm for Robots in Indoor Environments Using Line Segment Map

    Directory of Open Access Journals (Sweden)

    Bor-Woei Kuo

    2011-01-01

    Full Text Available Simultaneous Localization and Mapping (SLAM is an important technique for robotic system navigation. Due to the high complexity of the algorithm, SLAM usually needs long computational time or large amount of memory to achieve accurate results. In this paper, we present a lightweight Rao-Blackwellized particle filter- (RBPF- based SLAM algorithm for indoor environments, which uses line segments extracted from the laser range finder as the fundamental map structure so as to reduce the memory usage. Since most major structures of indoor environments are usually orthogonal to each other, we can also efficiently increase the accuracy and reduce the complexity of our algorithm by exploiting this orthogonal property of line segments, that is, we treat line segments that are parallel or perpendicular to each other in a special way when calculating the importance weight of each particle. Experimental results shows that our work is capable of drawing maps in complex indoor environments, needing only very low amount of memory and much less computational time as compared to other grid map-based RBPF SLAM algorithms.

  2. An effective method for segmentation of MR brain images using the ant colony optimization algorithm.

    Science.gov (United States)

    Taherdangkoo, Mohammad; Bagheri, Mohammad Hadi; Yazdi, Mehran; Andriole, Katherine P

    2013-12-01

    Since segmentation of magnetic resonance images is one of the most important initial steps in brain magnetic resonance image processing, success in this part has a great influence on the quality of outcomes of subsequent steps. In the past few decades, numerous methods have been introduced for classification of such images, but typically they perform well only on a specific subset of images, do not generalize well to other image sets, and have poor computational performance. In this study, we provided a method for segmentation of magnetic resonance images of the brain that despite its simplicity has a high accuracy. We compare the performance of our proposed algorithm with similar evolutionary algorithms on a pixel-by-pixel basis. Our algorithm is tested across varying sets of magnetic resonance images and demonstrates high speed and accuracy. It should be noted that in initial steps, the algorithm is computationally intensive requiring a large number of calculations; however, in subsequent steps of the search process, the number is reduced with the segmentation focused only in the target area. PMID:23563793

  3. Enhancement dark channel algorithm of color fog image based on the local segmentation

    Science.gov (United States)

    Yun, Lijun; Gao, Yin; Shi, Jun-sheng; Xu, Ling-zhang

    2015-04-01

    The classical dark channel theory algorithm has yielded good results in the processing of single fog image, but in some larger contrast regions, it appears image hue, brightness and saturation distortion problems to a certain degree, and also produces halo phenomenon. In the view of the above situation, through a lot of experiments, this paper has found some factors causing the halo phenomenon. The enhancement dark channel algorithm of color fog image based on the local segmentation is proposed. On the basis of the dark channel theory, first of all, the classic dark channel theory of mathematical model is modified, which is mainly to correct the brightness and saturation of image. Then, according to the local adaptive segmentation theory, it process the block of image, and overlap the local image. On the basis of the statistical rules, it obtains each pixel value from the segmentation processing, so as to obtain the local image. At last, using the dark channel theory, it achieves the enhanced fog image. Through the subjective observation and objective evaluation, the algorithm is better than the classic dark channel algorithm in the overall and details.

  4. Hepatic Arterial Configuration in Relation to the Segmental Anatomy of the Liver; Observations on MDCT and DSA Relevant to Radioembolization Treatment

    International Nuclear Information System (INIS)

    PurposeCurrent anatomical classifications do not include all variants relevant for radioembolization (RE). The purpose of this study was to assess the individual hepatic arterial configuration and segmental vascularization pattern and to develop an individualized RE treatment strategy based on an extended classification.MethodsThe hepatic vascular anatomy was assessed on MDCT and DSA in patients who received a workup for RE between February 2009 and November 2012. Reconstructed MDCT studies were assessed to determine the hepatic arterial configuration (origin of every hepatic arterial branch, branching pattern and anatomical course) and the hepatic segmental vascularization territory of all branches. Aberrant hepatic arteries were defined as hepatic arterial branches that did not originate from the celiac axis/CHA/PHA. Early branching patterns were defined as hepatic arterial branches originating from the celiac axis/CHA.ResultsThe hepatic arterial configuration and segmental vascularization pattern could be assessed in 110 of 133 patients. In 59 patients (54 %), no aberrant hepatic arteries or early branching was observed. Fourteen patients without aberrant hepatic arteries (13 %) had an early branching pattern. In the 37 patients (34 %) with aberrant hepatic arteries, five also had an early branching pattern. Sixteen different hepatic arterial segmental vascularization patterns were identified and described, differing by the presence of aberrant hepatic arteries, their respective vascular territory, and origin of the artery vascularizing segment four.ConclusionsThe hepatic arterial configuration and segmental vascularization pattern show marked individual variability beyond well-known classifications of anatomical variants. We developed an individualized RE treatment strategy based on an extended anatomical classification

  5. The cascaded moving k-means and fuzzy c-means clustering algorithms for unsupervised segmentation of malaria images

    Science.gov (United States)

    Abdul-Nasir, Aimi Salihah; Mashor, Mohd Yusoff; Halim, Nurul Hazwani Abd; Mohamed, Zeehaida

    2015-05-01

    Malaria is a life-threatening parasitic infectious disease that corresponds for nearly one million deaths each year. Due to the requirement of prompt and accurate diagnosis of malaria, the current study has proposed an unsupervised pixel segmentation based on clustering algorithm in order to obtain the fully segmented red blood cells (RBCs) infected with malaria parasites based on the thin blood smear images of P. vivax species. In order to obtain the segmented infected cell, the malaria images are first enhanced by using modified global contrast stretching technique. Then, an unsupervised segmentation technique based on clustering algorithm has been applied on the intensity component of malaria image in order to segment the infected cell from its blood cells background. In this study, cascaded moving k-means (MKM) and fuzzy c-means (FCM) clustering algorithms has been proposed for malaria slide image segmentation. After that, median filter algorithm has been applied to smooth the image as well as to remove any unwanted regions such as small background pixels from the image. Finally, seeded region growing area extraction algorithm has been applied in order to remove large unwanted regions that are still appeared on the image due to their size in which cannot be cleaned by using median filter. The effectiveness of the proposed cascaded MKM and FCM clustering algorithms has been analyzed qualitatively and quantitatively by comparing the proposed cascaded clustering algorithm with MKM and FCM clustering algorithms. Overall, the results indicate that segmentation using the proposed cascaded clustering algorithm has produced the best segmentation performances by achieving acceptable sensitivity as well as high specificity and accuracy values compared to the segmentation results provided by MKM and FCM algorithms.

  6. Code Synchronization Algorithm Based on Segment Correlation in Spread Spectrum Communication

    Directory of Open Access Journals (Sweden)

    Aohan Li

    2015-10-01

    Full Text Available Spread Spectrum (SPSP Communication is the theoretical basis of Direct Sequence Spread Spectrum (DSSS transceiver technology. Spreading code, modulation, demodulation, carrier synchronization and code synchronization in SPSP communications are the core parts of DSSS transceivers. This paper focuses on the code synchronization problem in SPSP communications. A novel code synchronization algorithm based on segment correlation is proposed. The proposed algorithm can effectively deal with the informational misjudgment caused by the unreasonable data acquisition times. This misjudgment may lead to an inability of DSSS receivers to restore transmitted signals. Simulation results show the feasibility of a DSSS transceiver design based on the proposed code synchronization algorithm. Finally, the communication functions of the DSSS transceiver based on the proposed code synchronization algorithm are implemented on Field Programmable Gate Array (FPGA.

  7. Application of Micro-segmentation Algorithms to the Healthcare Market:A Case Study

    Energy Technology Data Exchange (ETDEWEB)

    Sukumar, Sreenivas R [ORNL; Aline, Frank [ORNL

    2013-01-01

    We draw inspiration from the recent success of loyalty programs and targeted personalized market campaigns of retail companies such as Kroger, Netflix, etc. to understand beneficiary behaviors in the healthcare system. Our posit is that we can emulate the financial success the companies have achieved by better understanding and predicting customer behaviors and translating such success to healthcare operations. Towards that goal, we survey current practices in market micro-segmentation research and analyze health insurance claims data using those algorithms. We present results and insights from micro-segmentation of the beneficiaries using different techniques and discuss how the interpretation can assist with matching the cost-effective insurance payment models to the beneficiary micro-segments.

  8. Multispectral image segmentation using parallel mean shift algorithm and CUDA technology

    Science.gov (United States)

    Zghidi, Hafedh; Walczak, Maksym; Świtoński, Adam

    2016-06-01

    We present a parallel mean shift algorithm running on CUDA and its possible application in segmentation of multispectral images. The aim of this paper is to present a method of analyzing highly noised multispectral images of various objects, so that important features are enhanced and easier to identify. The algorithm finds applications in analysis of multispectral images of eyes so that certain features visible only in specific wavelengths are made clearly visible despite high level of noise, for which processing time is very long.

  9. AUTOMATED DIGITAL MAMMOGRAM SEGMENTATION FOR DETECTION OF ABNORMAL MASSES USING BINARY HOMOGENEITY ENHANCEMENT ALGORITHM

    Directory of Open Access Journals (Sweden)

    Indra Kanta Maitra

    2011-06-01

    Full Text Available Many image processing techniques have been developed over the past two decades to help radiologists in diagnosing breast cancer. At the same time, many studies proven that an early diagnosis of breastcancer can increase the survival rate, thus making screening programmes a mandatory step for females.Radiologists have to examine a large number of images. Digital Mammogram has emerged as the most popular screening technique for early detection of Breast Cancer and other abnormalities. Raw digital mammograms are medical images that are difficult to interpret so we need to develop Computer Aided Diagnosis (CAD systems that will improve detection of abnormalities in mammogram images. Extraction of the breast region by delineation of the breast contour and pectoral muscle allows the search for abnormalities to be limited to the region of the breast without undue influence from the background of the mammogram. We need to performessential pre-processing steps to suppress artifacts, enhance the breast region and then extract breast region by the process of segmentation. In this paper we present a fully automated scheme for detection of abnormal masses by anatomical segmentation of Breast Region of Interest (ROI. We are using medio-lateral oblique (MLO view of mammograms. We have proposed a new homogeneity enhancement process namely Binary Homogeneity Enhancement Algorithm (BHEA, followed by an innovative approach for edge detection (EDA. Then obtain the breast boundary by using our proposed Breast Boundary Detection Algorithm (BBDA. After we use our proposed Pectoral Muscle Detection Algorithm (PMDA to suppress the pectoral muscle thus obtaining the breast ROI, we use our proposed Anatomical Segmentation of Breast ROI (ASB algorithm to differentiate various regions within the breast. After segregating the different breast regions we use our proposed Seeded Region Growing Algorithm (SRGA to isolate normal and abnormal regions in the breast tissue. If any

  10. US-Cut: interactive algorithm for rapid detection and segmentation of liver tumors in ultrasound acquisitions

    Science.gov (United States)

    Egger, Jan; Voglreiter, Philip; Dokter, Mark; Hofmann, Michael; Chen, Xiaojun; Zoller, Wolfram G.; Schmalstieg, Dieter; Hann, Alexander

    2016-04-01

    Ultrasound (US) is the most commonly used liver imaging modality worldwide. It plays an important role in follow-up of cancer patients with liver metastases. We present an interactive segmentation approach for liver tumors in US acquisitions. Due to the low image quality and the low contrast between the tumors and the surrounding tissue in US images, the segmentation is very challenging. Thus, the clinical practice still relies on manual measurement and outlining of the tumors in the US images. We target this problem by applying an interactive segmentation algorithm to the US data, allowing the user to get real-time feedback of the segmentation results. The algorithm has been developed and tested hand-in-hand by physicians and computer scientists to make sure a future practical usage in a clinical setting is feasible. To cover typical acquisitions from the clinical routine, the approach has been evaluated with dozens of datasets where the tumors are hyperechoic (brighter), hypoechoic (darker) or isoechoic (similar) in comparison to the surrounding liver tissue. Due to the interactive real-time behavior of the approach, it was possible even in difficult cases to find satisfying segmentations of the tumors within seconds and without parameter settings, and the average tumor deviation was only 1.4mm compared with manual measurements. However, the long term goal is to ease the volumetric acquisition of liver tumors in order to evaluate for treatment response. Additional aim is the registration of intraoperative US images via the interactive segmentations to the patient's pre-interventional CT acquisitions.

  11. Cell motility dynamics: a novel segmentation algorithm to quantify multi-cellular bright field microscopy images.

    Directory of Open Access Journals (Sweden)

    Assaf Zaritsky

    Full Text Available Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional

  12. INFARCT DETECTION IN BRAIN MRI USING IMPROVED SEGMENTATION ALGORITHM AND VOLUME VISUALIZATION

    OpenAIRE

    Praveen Kumar E; Sumithra M G; Sunil Kumar P

    2013-01-01

    In the present days, for the human body anatomical study and for the treatment planning medicalscience very much depend on the medical imaging technology and medical images. Specifically for thehuman brain, MRI widely prefers and using for the imaging. But by nature medical images are complex andnoisy.This leads to the necessity of processes that reduces difficulties in analysis and improves quality ofoutput.This paper discuss about an improved segmentation algorithm for infarct detection in ...

  13. A Modified Fuzzy C-Means Algorithm for Brain MR Image Segmentation and Bias Field Correction

    Institute of Scientific and Technical Information of China (English)

    Wen-Qian Deng; Xue-Mei Li; Xifeng Gao; Cai-Ming Zhang

    2016-01-01

    In quantitative brain image analysis, accurate brain tissue segmentation from brain magnetic resonance image (MRI) is a critical step. It is considered to be the most important and difficult issue in the field of medical image processing. The quality of MR images is influenced by partial volume effect, noise, and intensity inhomogeneity, which render the segmentation task extremely challenging. We present a novel fuzzy c-means algorithm (RCLFCM) for segmentation and bias field correction of brain MR images. We employ a new gray-difference coefficient and design a new impact factor to measure the effect of neighbor pixels, so that the robustness of anti-noise can be enhanced. Moreover, we redefine the objective function of FCM (fuzzy c-means) by adding the bias field estimation model to overcome the intensity inhomogeneity in the image and segment the brain MR images simultaneously. We also construct a new spatial function by combining pixel gray value dissimilarity with its membership, and make full use of the space information between pixels to update the membership. Compared with other state-of-the-art approaches by using similarity accuracy on synthetic MR images with different levels of noise and intensity inhomogeneity, the proposed algorithm generates the results with high accuracy and robustness to noise.

  14. Application of K-Means Algorithm for Efficient Customer Segmentation: A Strategy for Targeted Customer Services

    Directory of Open Access Journals (Sweden)

    Chinedu Pascal Ezenkwu

    2015-10-01

    Full Text Available The emergence of many business competitors has engendered severe rivalries among competing businesses in gaining new customers and retaining old ones. Due to the preceding, the need for exceptional customer services becomes pertinent, notwithstanding the size of the business. Furthermore, the ability of any business to understand each of its customers’ needs will earn it greater leverage in providing targeted customer services and developing customised marketing programs for the customers. This understanding can be possible through systematic customer segmentation. Each segment comprises customers who share similar market characteristics. The ideas of Big data and machine learning have fuelled a terrific adoption of an automated approach to customer segmentation in preference to traditional market analyses that are often inefficient especially when the number of customers is too large. In this paper, the k-Means clustering algorithm is applied for this purpose. A MATLAB program of the k-Means algorithm was developed (available in the appendix and the program is trained using a z-score normalised two-feature dataset of 100 training patterns acquired from a retail business. The features are the average amount of goods purchased by customer per month and the average number of customer visits per month. From the dataset, four customer clusters or segments were identified with 95% accuracy, and they were labeled: High-Buyers-Regular-Visitors (HBRV, High-Buyers-Irregular-Visitors (HBIV, Low-Buyers-Regular-Visitors (LBRV and Low-Buyers-Irregular-Visitors (LBIV.

  15. Image Segmentation Algorithm Based on Spectral Clustering Algorithm%谱聚类图像分割算法研究

    Institute of Scientific and Technical Information of China (English)

    张权; 胡玉兰

    2012-01-01

    针对谱聚类算法对图像分割效果差强人意的特点,研究了一种改进的Nystr(o)m算法进行谱聚类图像分割,使谱聚类算法应用于图像分割的效果有所改善.该算法首先对图像进行预处理,变换图像的分布数据空间,再分别计算对选定样本空间的数据间以及样本与其他空间的数据间的距离矩阵,并转化为相似矩阵;然后对相似矩阵正交化并且特征分解,进行K-Means聚类;最后将聚类结果进行后期处理.通过实验验证了该算法的有效性.%Spectral clustering algorithm to image segmentation was not perfect. An algorithm is proposed for spectral clustering image segmentation, which makes the effect of image segmentation better. Firstly, the image was pre-processed, transformed the distribution of the image data space, and calculated the distance matrix between the data of the selected sample space as well as samples and other space. It is transformed into a similarity matrix,what is more,the similarity matrix is made by orthogonal . The characteristics is decomposing by K-Means clustering; Finally, it took some steps for clustering results to be processed . Effectiveness of the algorithm is verified by experiment reasults.

  16. A de-noising algorithm to improve SNR of segmented gamma scanner for spectrum analysis

    Science.gov (United States)

    Li, Huailiang; Tuo, Xianguo; Shi, Rui; Zhang, Jinzhao; Henderson, Mark Julian; Courtois, Jérémie; Yan, Minhao

    2016-05-01

    An improved threshold shift-invariant wavelet transform de-noising algorithm for high-resolution gamma-ray spectroscopy is proposed to optimize the threshold function of wavelet transforms and reduce signal resulting from pseudo-Gibbs artificial fluctuations. This algorithm was applied to a segmented gamma scanning system with large samples in which high continuum levels caused by Compton scattering are routinely encountered. De-noising data from the gamma ray spectrum measured by segmented gamma scanning system with improved, shift-invariant and traditional wavelet transform algorithms were all evaluated. The improved wavelet transform method generated significantly enhanced performance of the figure of merit, the root mean square error, the peak area, and the sample attenuation correction in the segmented gamma scanning system assays. We also found that the gamma energy spectrum can be viewed as a low frequency signal as well as high frequency noise superposition by the spectrum analysis. Moreover, a smoothed spectrum can be appropriate for straightforward automated quantitative analysis.

  17. Image Segmentation and Maturity Recognition Algorithm based on Color Features of Lingwu Long Jujube

    Directory of Open Access Journals (Sweden)

    Yutan Wang

    2013-12-01

    Full Text Available Fruits’ recognition under natural scenes is a key technology to intelligent automatic picking. In this study, an image segmentation method based on color difference fusion in RGB color space was proposed in order to implement image segmentation and recognition maturity intelligently according to Lingwu long jujubes’ color features under the complex environment. Firstly, the three-dimensional histograms of each color component which is widely used in color space currently are compared; and then the jujubes’ red area and non-red area was extracted respectively, thus, the whole target area is obtained by sum of those areas; then, watershed algorithm combined with mathematical morphology distance and gradient was utilized to overcome adhesion and occlusion phenomena; finally, the maturity level was recognized by the established recognition model of Lingwu long jujubes. The segmentation was tested through 100 sample set and 93.27% of precision rate was attained, so was correct estimating rate of maturity level recognition above 90%. The results indicate that a smaller average segmentation error probability is in this method, which is more efficient in the extraction and recognition of jujubes with red and green and the problem of segmentation and maturity level judgment of adhesive fruits is solved by the method as well.

  18. A new segmentation algorithm for lunar surface terrain based on CCD images

    Science.gov (United States)

    Jiang, Hong-Kun; Tian, Xiao-Lin; Xu, Ao-Ao

    2015-09-01

    Terrain classification is one of the critical steps used in lunar geomorphologic analysis and landing site selection. Most of the published works have focused on a Digital Elevation Model (DEM) to distinguish different regions of lunar terrain. This paper presents an algorithm that can be applied to lunar CCD images by blocking and clustering according to image features, which can accurately distinguish between lunar highland and lunar mare. The new algorithm, compared with the traditional algorithm, can improve classification accuracy. The new algorithm incorporates two new features and one Tamura texture feature. The new features are generating an enhanced image histogram and modeling the properties of light reflection, which can represent the geological characteristics based on CCD gray level images. These features are applied to identify texture in order to perform image clustering and segmentation by a weighted Euclidean distance to distinguish between lunar mare and lunar highlands. The new algorithm has been tested on Chang'e-1 CCD data and the testing result has been compared with geological data published by the U.S. Geological Survey. The result has shown that the algorithm can effectively distinguish the lunar mare from highlands in CCD images. The overall accuracy of the proposed algorithm is satisfactory, and the Kappa coefficient is 0.802, which is higher than the result of combining the DEM with CCD images.

  19. A Novel Pixon-Based Image Segmentation Process Using Fuzzy Filtering and Fuzzy C-mean Algorithm

    DEFF Research Database (Denmark)

    Nadernejad, E; Barari, Amin

    2011-01-01

    Image segmentation, which is an important stage of many image processing algorithms, is the process of partitioning an image into nonintersecting regions, such that each region is homogeneous and the union of no two adjacent regions is homogeneous. This paper presents a novel pixon-based algorithm...... for image segmentation. The key idea is to create a pixon model by combining fuzzy filtering as a kernel function and a fuzzy c-means clustering algorithm for image segmentation. Use of fuzzy filters reduces noise and slightly smoothes the image. Use of the proposed pixon model prevented image over...

  20. Parallel Implementation of Bias Field Correction Fuzzy C-Means Algorithm for Image Segmentation

    Directory of Open Access Journals (Sweden)

    Nouredine AITALI

    2016-03-01

    Full Text Available Image segmentation in the medical field is one of the most important phases to diseases diagnosis. The bias field estimation algorithm is the most interesting techniques to correct the in-homogeneity intensity artifact on the image. However, the use of such technique requires a powerful processing and quite expensive for big size as medical images. Hence the idea of parallelism becomes increasingly required. Several researchers have followed this path mainly in the bioinformatics field where they have suggested different algorithms implementations. In this paper, a novel Single Instruction Multiple Data (SIMD architecture for bias field estimation and image segmentation algorithm is proposed. In order to accelerate compute-intensive portions of the sequential implementation, we have implemented this algorithm on three different graphics processing units (GPU cards named GT740m, GTX760 and GTX580 respectively, using Compute Unified Device Architecture (CUDA software programming tool. Numerical obtained results for the computation speed up, allowed us to conclude on the suitable GPU architecture for this kind of applications and closest ones.

  1. Image Based Hair Segmentation Algorithm for the Application of Automatic Facial Caricature Synthesis

    Directory of Open Access Journals (Sweden)

    Yehu Shen

    2014-01-01

    Full Text Available Hair is a salient feature in human face region and are one of the important cues for face analysis. Accurate detection and presentation of hair region is one of the key components for automatic synthesis of human facial caricature. In this paper, an automatic hair detection algorithm for the application of automatic synthesis of facial caricature based on a single image is proposed. Firstly, hair regions in training images are labeled manually and then the hair position prior distributions and hair color likelihood distribution function are estimated from these labels efficiently. Secondly, the energy function of the test image is constructed according to the estimated prior distributions of hair location and hair color likelihood. This energy function is further optimized according to graph cuts technique and initial hair region is obtained. Finally, K-means algorithm and image postprocessing techniques are applied to the initial hair region so that the final hair region can be segmented precisely. Experimental results show that the average processing time for each image is about 280 ms and the average hair region detection accuracy is above 90%. The proposed algorithm is applied to a facial caricature synthesis system. Experiments proved that with our proposed hair segmentation algorithm the facial caricatures are vivid and satisfying.

  2. SEGMENTATION OF CT SCAN LUMBAR SPINE IMAGE USING MEDIAN FILTER AND CANNY EDGE DETECTION ALGORITHM

    Directory of Open Access Journals (Sweden)

    E.Punarselvam

    2013-09-01

    Full Text Available The lumbar vertebrae are the largest segments of the movable part of the vertebral column, they are elected L1 to L5, starting at the top. The spinal column, more commonly called the backbone, is made up primarily of vertebrae discs, and the spinal cord. Acting as a communication conduit for the brain, signals are transmitted and received through the spinal cord. It is otherwise known as vertebralcolumn consists of 24 separate bony vertebrae together with 5 fused vertebrae, it is the unique interaction between the solid and fluid components that provides the disc strength and flexibility required to bear loading of the lumbar spine. In this work the Segmentation of Spine Image using Median Filter and Canny Edge Detection Algorithm between lumbar spine CT scan spine disc image. The result shows thatthe canny edge detection algorithm produced better result when compared other edge detection algorithm. Finding the correct boundary in a noisy image of spine disc is still a difficult one. To find outabsolute edges from noisy images, the comparative result can be verified and validated with the standard medical values. The result shows that the canny edge detection algorithm performs well and produced a solution very nearer to the optimal solution. This method is vigorous for all kinds of noisy images.

  3. Co-adaptability solution to conflict events in construction projects by segmented hierarchical algorithm

    Institute of Scientific and Technical Information of China (English)

    HOU XueLiang; LU Mei

    2008-01-01

    In order to seek the co-adaptability solution to conflict events in construction en-gineering projects,a new method referred to as segmented hierarchical algorithm is proposed in this paper by means of comparing co-adaptability evolution process of conflict events to the stackelberg model.By this new algorithm,local solutions to the first-order transformation of co-adaptability for conflict events can be ob-tained,based upon which,a global solution to the second-order transformation of co-adaptability for conflict events can also be decided by judging satisfaction de-gree of local solutions.The research results show that this algorithm can be used not only for obtaining co-adaptability solution to conflict events efficiently,but also for other general decision-making problems with multi-layers and multi-subsidi-aries in project management field.

  4. Co-adaptability solution to conflict events in construction projects by segmented hierarchical algorithm

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    In order to seek the co-adaptability solution to conflict events in construction engineering projects, a new method referred to as segmented hierarchical algorithm is proposed in this paper by means of comparing co-adaptability evolution process of conflict events to the stackelberg model. By this new algorithm, local solutions to the first-order transformation of co-adaptability for conflict events can be obtained, based upon which, a global solution to the second-order transformation of co-adaptability for conflict events can also be decided by judging satisfaction degree of local solutions. The research results show that this algorithm can be used not only for obtaining co-adaptability solution to conflict events efficiently, but also for other general decision-making problems with multi-layers and multi-subsidi-aries in project management field.

  5. CT liver volumetry using geodesic active contour segmentation with a level-set algorithm

    Science.gov (United States)

    Suzuki, Kenji; Epstein, Mark L.; Kohlbrenner, Ryan; Obajuluwa, Ademola; Xu, Jianwu; Hori, Masatoshi; Baron, Richard

    2010-03-01

    Automatic liver segmentation on CT images is challenging because the liver often abuts other organs of a similar density. Our purpose was to develop an accurate automated liver segmentation scheme for measuring liver volumes. We developed an automated volumetry scheme for the liver in CT based on a 5 step schema. First, an anisotropic smoothing filter was applied to portal-venous phase CT images to remove noise while preserving the liver structure, followed by an edge enhancer to enhance the liver boundary. By using the boundary-enhanced image as a speed function, a fastmarching algorithm generated an initial surface that roughly estimated the liver shape. A geodesic-active-contour segmentation algorithm coupled with level-set contour-evolution refined the initial surface so as to more precisely fit the liver boundary. The liver volume was calculated based on the refined liver surface. Hepatic CT scans of eighteen prospective liver donors were obtained under a liver transplant protocol with a multi-detector CT system. Automated liver volumes obtained were compared with those manually traced by a radiologist, used as "gold standard." The mean liver volume obtained with our scheme was 1,520 cc, whereas the mean manual volume was 1,486 cc, with the mean absolute difference of 104 cc (7.0%). CT liver volumetrics based on an automated scheme agreed excellently with "goldstandard" manual volumetrics (intra-class correlation coefficient was 0.95) with no statistically significant difference (p(Fliver volumes.

  6. A contiguity-enhanced k-means clustering algorithm for unsupervised multispectral image segmentation

    Energy Technology Data Exchange (ETDEWEB)

    Theiler, J.; Gisler, G.

    1997-07-01

    The recent and continuing construction of multi and hyper spectral imagers will provide detailed data cubes with information in both the spatial and spectral domain. This data shows great promise for remote sensing applications ranging from environmental and agricultural to national security interests. The reduction of this voluminous data to useful intermediate forms is necessary both for downlinking all those bits and for interpreting them. Smart onboard hardware is required, as well as sophisticated earth bound processing. A segmented image (in which the multispectral data in each pixel is classified into one of a small number of categories) is one kind of intermediate form which provides some measure of data compression. Traditional image segmentation algorithms treat pixels independently and cluster the pixels according only to their spectral information. This neglects the implicit spatial information that is available in the image. We will suggest a simple approach; a variant of the standard k-means algorithm which uses both spatial and spectral properties of the image. The segmented image has the property that pixels which are spatially contiguous are more likely to be in the same class than are random pairs of pixels. This property naturally comes at some cost in terms of the compactness of the clusters in the spectral domain, but we have found that the spatial contiguity and spectral compactness properties are nearly orthogonal, which means that we can make considerable improvements in the one with minimal loss in the other.

  7. Microsurgical anatomy of the third segment of vertebral artery%椎动脉第三段的显微解剖研究

    Institute of Scientific and Technical Information of China (English)

    杨帆; 佟小光; 洪健; 靳峥

    2009-01-01

    Objective To accumulate the morphological data of the third segment of vertebral artery and to provide the basis of microvascular anatomy for clinical treatment. Method Ten adult cadaver heads (20 sides)were used in the study. The morphology of the third segment of vertebral arteries was observed and their dimensions were measured with the aid of an operating microscope. Results The third segments of the vertebral arteries were tortuous. The external diameters of left vertebral arteries(4. 01 ±1.12)mm were larger than that of the right ones (3.45± 0. 32) mm. The length of the third segment of the vertebral artery was(50. 93 ±8. 23)ram. There was no significant anatomic variation. Conclusions The third segment of vertebral artery is tortuous to enable the movements of neck. The far-lateral approach is often used to expose the third segment of vertebral artery. The suboccipital triangle may be an anatomic marker for the third segment of vertebral artery.%目的 研究椎动脉第三段(V3)的形态特点,为临床应用提供解剖学依据.方法 10例(20侧)成人尸头标本,解剖观察V3段形态结构,测量椎动脉和枕动脉长度、外径等解剖数据.结果 V3段有明显而连续的多个弯曲,V3段全长(50.93±8.23)mm,未见明显解剖变异.结论 V3段的连续弯曲可适应头颈部复杂的运动,V3段的显露常采用枕下远外侧入路,枕下三角是术中暴露识别V3段的重要标志.

  8. Reconstruction-by-Dilation and Top-Hat Algorithms for Contrast Enhancement and Segmentation of Microcalcifications in Digital Mammograms

    Science.gov (United States)

    Diaz, Claudia C.

    2007-11-01

    I present some results of contrast enhancement and segmentation of microcalcifications in digital mammograms. These mammograms were obtained from MIAS-minidatabase and using a CR to digitize images. White-top-hat and black-top-hat transformations were used to improve the contrast of images, while reconstruction-by-dilation algorithm was used to emphasize the microcalcifications over the tissues. Segmentation was done using different gradient matrices. These algorithms intended to show some details which were not evident in original images.

  9. Digital Terrain from a Two-Step Segmentation and Outlier-Based Algorithm

    Science.gov (United States)

    Hingee, Kassel; Caccetta, Peter; Caccetta, Louis; Wu, Xiaoliang; Devereaux, Drew

    2016-06-01

    We present a novel ground filter for remotely sensed height data. Our filter has two phases: the first phase segments the DSM with a slope threshold and uses gradient direction to identify candidate ground segments; the second phase fits surfaces to the candidate ground points and removes outliers. Digital terrain is obtained by a surface fit to the final set of ground points. We tested the new algorithm on digital surface models (DSMs) for a 9600km2 region around Perth, Australia. This region contains a large mix of land uses (urban, grassland, native forest and plantation forest) and includes both a sandy coastal plain and a hillier region (elevations up to 0.5km). The DSMs are captured annually at 0.2m resolution using aerial stereo photography, resulting in 1.2TB of input data per annum. Overall accuracy of the filter was estimated to be 89.6% and on a small semi-rural subset our algorithm was found to have 40% fewer errors compared to Inpho's Match-T algorithm.

  10. Optimized adaptation algorithm for HEVC/H.265 dynamic adaptive streaming over HTTP using variable segment duration

    Science.gov (United States)

    Irondi, Iheanyi; Wang, Qi; Grecos, Christos

    2016-04-01

    Adaptive video streaming using HTTP has become popular in recent years for commercial video delivery. The recent MPEG-DASH standard allows interoperability and adaptability between servers and clients from different vendors. The delivery of the MPD (Media Presentation Description) files in DASH and the DASH client behaviours are beyond the scope of the DASH standard. However, the different adaptation algorithms employed by the clients do affect the overall performance of the system and users' QoE (Quality of Experience), hence the need for research in this field. Moreover, standard DASH delivery is based on fixed segments of the video. However, there is no standard segment duration for DASH where various fixed segment durations have been employed by different commercial solutions and researchers with their own individual merits. Most recently, the use of variable segment duration in DASH has emerged but only a few preliminary studies without practical implementation exist. In addition, such a technique requires a DASH client to be aware of segment duration variations, and this requirement and the corresponding implications on the DASH system design have not been investigated. This paper proposes a segment-duration-aware bandwidth estimation and next-segment selection adaptation strategy for DASH. Firstly, an MPD file extension scheme to support variable segment duration is proposed and implemented in a realistic hardware testbed. The scheme is tested on a DASH client, and the tests and analysis have led to an insight on the time to download next segment and the buffer behaviour when fetching and switching between segments of different playback durations. Issues like sustained buffering when switching between segments of different durations and slow response to changing network conditions are highlighted and investigated. An enhanced adaptation algorithm is then proposed to accurately estimate the bandwidth and precisely determine the time to download the next

  11. 浅谈中文切词算法%A Tentative Study on Chinese Segmentation Algorithm

    Institute of Scientific and Technical Information of China (English)

    黎佳

    2013-01-01

    如何高效率的获取满足个性化的需求成为了新时代的一个热门话题,搜索引擎在一定程度上体现了这一点。然而在搜索引擎中,内部分词算法机制是关键环节,它的目的在于选取好的关键字。一个好的分词算法会降低用户搜索信息的时间和难度,大大提高查询信息的效率。然而目前有很多分词算法,它们的性能和效率各不相同,本文的主要研究目的是探讨目前几种比较流行分词器算法的工作机制,根据它们自身的不同特点,在准确率和召回率这两个方面来比较它们的性能,并进一步研究它们是如何处理用户关键字的。%How to efifcient access to meet the personalized needs have become a hot topic in the new era, the search engine in a certain extent, a relfection of this. However, in the search engine, the internal segmentation algorithm mechanism is the key link, it is to choose best keywords. A good segmentation algorithm can reduce the time and dififculty for users to search for information, improve the efifciency of query information greatly. However, there are a lot of word segmentation algorithms, their performance and efifciency are different, the main purpose of this study is to investigate the mechanism of several popular word segmentation algorithms, and compare the performance in the precision rate and recall rate based on different characteristics of their own, and further study on how they dispose user key.

  12. Full Object Boundary Detection by Applying Scale Invariant Features in A Region Merging Segmentation Algorithm

    Directory of Open Access Journals (Sweden)

    Reza Oji

    2012-10-01

    Full Text Available Object detection is a fundamental task in computer vision and has many applications in image processing.This paper proposes a new approach for object detection by applying scale invariant feature transform(SIFT in an automatic segmentation algorithm. SIFT is an invariant algorithm respect to scale, translationand rotation. The features are very distinct and provide stable keypoints that can be used for matching anobject in different images. At first, an object is trained with different aspects for finding best keypoints. Theobject can be recognized in the other images by using achieved keypoints. Then, a robust segmentationalgorithm is used to detect the object with full boundary based on SIFT keypoints. In segmentationalgorithm, a merging role is defined to merge the regions in image with the assistance of keypoints. Theresults show that the proposed approach is reliable for object detection and can extract object boundarywell.

  13. DICOM Image Retrieval Using Novel Geometric Moments and Image Segmentation Algorithm

    Directory of Open Access Journals (Sweden)

    Amol Bhagat

    2013-09-01

    Full Text Available The Medical image database is growing day by day [1]. Most of the medical images are stored in DICOM (Digital Imaging and Communications in Medicine format. There are various categories of medical images such as CT scan, X- Ray, Ultrasound, Pathology, MRI, Microscopy, etc [2]. Physicians compare previous and current medical images associated patients to provide right treatment. Medical Imaging is a leading role in modern diagnosis. Efficient image retrieval tools are needed to retrieve the intended images from large growing medical image databases. Such tools must provide more precise retrieval results with less computational complexity. This paper compares the various techniques for DICOM medical image retrieval and shows that the proposed geometric and image segmentation based image retrieval algorithm performs better as compared to other algorithms.

  14. Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study.

    Science.gov (United States)

    Rudyanto, Rina D; Kerkstra, Sjoerd; van Rikxoort, Eva M; Fetita, Catalin; Brillet, Pierre-Yves; Lefevre, Christophe; Xue, Wenzhe; Zhu, Xiangjun; Liang, Jianming; Öksüz, Ilkay; Ünay, Devrim; Kadipaşaoğlu, Kamuran; Estépar, Raúl San José; Ross, James C; Washko, George R; Prieto, Juan-Carlos; Hoyos, Marcela Hernández; Orkisz, Maciej; Meine, Hans; Hüllebrand, Markus; Stöcker, Christina; Mir, Fernando Lopez; Naranjo, Valery; Villanueva, Eliseo; Staring, Marius; Xiao, Changyan; Stoel, Berend C; Fabijanska, Anna; Smistad, Erik; Elster, Anne C; Lindseth, Frank; Foruzan, Amir Hossein; Kiros, Ryan; Popuri, Karteek; Cobzas, Dana; Jimenez-Carretero, Daniel; Santos, Andres; Ledesma-Carbayo, Maria J; Helmberger, Michael; Urschler, Martin; Pienn, Michael; Bosboom, Dennis G H; Campo, Arantza; Prokop, Mathias; de Jong, Pim A; Ortiz-de-Solorzano, Carlos; Muñoz-Barrutia, Arrate; van Ginneken, Bram

    2014-10-01

    The VESSEL12 (VESsel SEgmentation in the Lung) challenge objectively compares the performance of different algorithms to identify vessels in thoracic computed tomography (CT) scans. Vessel segmentation is fundamental in computer aided processing of data generated by 3D imaging modalities. As manual vessel segmentation is prohibitively time consuming, any real world application requires some form of automation. Several approaches exist for automated vessel segmentation, but judging their relative merits is difficult due to a lack of standardized evaluation. We present an annotated reference dataset containing 20 CT scans and propose nine categories to perform a comprehensive evaluation of vessel segmentation algorithms from both academia and industry. Twenty algorithms participated in the VESSEL12 challenge, held at International Symposium on Biomedical Imaging (ISBI) 2012. All results have been published at the VESSEL12 website http://vessel12.grand-challenge.org. The challenge remains ongoing and open to new participants. Our three contributions are: (1) an annotated reference dataset available online for evaluation of new algorithms; (2) a quantitative scoring system for objective comparison of algorithms; and (3) performance analysis of the strengths and weaknesses of the various vessel segmentation methods in the presence of various lung diseases.

  15. A quantum mechanics-based algorithm for vessel segmentation in retinal images

    Science.gov (United States)

    Youssry, Akram; El-Rafei, Ahmed; Elramly, Salwa

    2016-06-01

    Blood vessel segmentation is an important step in retinal image analysis. It is one of the steps required for computer-aided detection of ophthalmic diseases. In this paper, a novel quantum mechanics-based algorithm for retinal vessel segmentation is presented. The algorithm consists of three major steps. The first step is the preprocessing of the images to prepare the images for further processing. The second step is feature extraction where a set of four features is generated at each image pixel. These features are then combined using a nonlinear transformation for dimensionality reduction. The final step is applying a recently proposed quantum mechanics-based framework for image processing. In this step, pixels are mapped to quantum systems that are allowed to evolve from an initial state to a final state governed by Schrödinger's equation. The evolution is controlled by the Hamiltonian operator which is a function of the extracted features at each pixel. A measurement step is consequently performed to determine whether the pixel belongs to vessel or non-vessel classes. Many functional forms of the Hamiltonian are proposed, and the best performing form was selected. The algorithm is tested on the publicly available DRIVE database. The average results for sensitivity, specificity, and accuracy are 80.29, 97.34, and 95.83 %, respectively. These results are compared to some recently published techniques showing the superior performance of the proposed method. Finally, the implementation of the algorithm on a quantum computer and the challenges facing this implementation are introduced.

  16. Anatomy-Based Algorithms for Detecting Oral Cancer Using Reflectance and Fluorescence Spectroscopy

    OpenAIRE

    McGee, Sasha; Mardirossian, Vartan; Elackattu, Alphi; Mirkovic, Jelena; Pistey, Robert; Gallagher, George; Kabani, Sadru; Yu, Chung-Chieh; Wang, Zimmern; Badizadegan, Kamran; Grillone, Gregory; Feld, Michael S.

    2009-01-01

    OBJECTIVES: We used reflectance and fluorescence spectroscopy to noninvasively and quantitatively distinguish benign from dysplastic/malignant oral lesions. We designed diagnostic algorithms to account for differences in the spectral properties among anatomic sites (gingiva, buccal mucosa, etc). METHODS: In vivo reflectance and fluorescence spectra were collected from 71 patients with oral lesions. The tissue was then biopsied and the specimen evaluated by histopathology. Quantitative par...

  17. Binarization of MRI with Intensity Inhomogeneity using K- Means Clustering for Segmenting Hippocampus

    OpenAIRE

    T. Genish; Somasundaram, K

    2013-01-01

    Medical image segmentation plays a crucial role in identifying the shape and structure of human anatomy. The most widely used image segmentation algorithms are edge-based and typically rely on the intensity inhomogeneity of the image at the edges, which often fail to provide accurate segmentation results. This paper proposes a boundary detection technique for segmenting the hippocampus (the subcortical structure in medial temporal lobe) from MRI with intensity inhomogeneity without ruining it...

  18. An Algorithm for Obtaining the Distribution of 1-Meter Lightning Channel Segment Altitudes for Application in Lightning NOx Production Estimation

    Science.gov (United States)

    Peterson, Harold; Koshak, William J.

    2009-01-01

    An algorithm has been developed to estimate the altitude distribution of one-meter lightning channel segments. The algorithm is required as part of a broader objective that involves improving the lightning NOx emission inventories of both regional air quality and global chemistry/climate models. The algorithm was tested and applied to VHF signals detected by the North Alabama Lightning Mapping Array (NALMA). The accuracy of the algorithm was characterized by comparing algorithm output to the plots of individual discharges whose lengths were computed by hand; VHF source amplitude thresholding and smoothing were applied to optimize results. Several thousands of lightning flashes within 120 km of the NALMA network centroid were gathered from all four seasons, and were analyzed by the algorithm. The mean, standard deviation, and median statistics were obtained for all the flashes, the ground flashes, and the cloud flashes. One-meter channel segment altitude distributions were also obtained for the different seasons.

  19. SAR Image Segmentation with Unknown Number of Classes Combined Voronoi Tessellation and Rjmcmc Algorithm

    Science.gov (United States)

    Zhao, Q. H.; Li, Y.; Wang, Y.

    2016-06-01

    This paper presents a novel segmentation method for automatically determining the number of classes in Synthetic Aperture Radar (SAR) images by combining Voronoi tessellation and Reversible Jump Markov Chain Monte Carlo (RJMCMC) strategy. Instead of giving the number of classes a priori, it is considered as a random variable and subject to a Poisson distribution. Based on Voronoi tessellation, the image is divided into homogeneous polygons. By Bayesian paradigm, a posterior distribution which characterizes the segmentation and model parameters conditional on a given SAR image can be obtained up to a normalizing constant; Then, a Revisable Jump Markov Chain Monte Carlo(RJMCMC) algorithm involving six move types is designed to simulate the posterior distribution, the move types including: splitting or merging real classes, updating parameter vector, updating label field, moving positions of generating points, birth or death of generating points and birth or death of an empty class. Experimental results with real and simulated SAR images demonstrate that the proposed method can determine the number of classes automatically and segment homogeneous regions well.

  20. Local Pixel Value Collection Algorithm for Spot Segmentation in Two-Dimensional Gel Electrophoresis Research

    Directory of Open Access Journals (Sweden)

    Peter Peer

    2007-01-01

    Full Text Available Two-dimensional gel-electrophoresis (2-DE images show the expression levels of several hundreds of proteins where each protein is represented as a blob-shaped spot of grey level values. The spot detection, that is, the segmentation process has to be efficient as it is the first step in the gel processing. Such extraction of information is a very complex task. In this paper, we propose a novel spot detector that is basically a morphology-based method with the use of a seeded region growing as a central paradigm and which relies on the spot correlation information. The method is tested on our synthetic as well as on real gels with human samples from SWISS-2DPAGE (two-dimensional polyacrylamide gel electrophoresis database. A comparison of results is done with a method called pixel value collection (PVC. Since our algorithm efficiently uses local spot information, segments the spot by collecting pixel values and its affinity with PVC, we named it local pixel value collection (LPVC. The results show that LPVC achieves similar segmentation results as PVC, but is much faster than PVC.

  1. Square-Cut: A Segmentation Algorithm on the Basis of a Rectangle Shape

    CERN Document Server

    Egger, Jan; Dukatz, Thomas; Kolodziej, Malgorzata; Zukic, Dzenan; Freisleben, Bernd; Nimsky, Christopher; 10.1371/journal.pone.0031064

    2012-01-01

    We present a rectangle-based segmentation algorithm that sets up a graph and performs a graph cut to separate an object from the background. However, graph-based algorithms distribute the graph's nodes uniformly and equidistantly on the image. Then, a smoothness term is added to force the cut to prefer a particular shape. This strategy does not allow the cut to prefer a certain structure, especially when areas of the object are indistinguishable from the background. We solve this problem by referring to a rectangle shape of the object when sampling the graph nodes, i.e., the nodes are distributed nonuniformly and non-equidistantly on the image. This strategy can be useful, when areas of the object are indistinguishable from the background. For evaluation, we focus on vertebrae images from Magnetic Resonance Imaging (MRI) datasets to support the time consuming manual slice-by-slice segmentation performed by physicians. The ground truth of the vertebrae boundaries were manually extracted by two clinical experts...

  2. PHEW: a parallel segmentation algorithm for three-dimensional AMR datasets - application to structure detection in self-gravitating flows

    CERN Document Server

    Bleuler, Andreas; Carassou, Sébastien; Martizzi, Davide

    2014-01-01

    We introduce PHEW (Parallel HiErarchical Watershed), a new segmentation algorithm to detect structures in astrophysical fluid simulations, and its implementation into the adaptive mesh refinement (AMR) code ramses. PHEW works on the density field defined on the adaptive mesh, and can thus be used on the gas density or the dark matter density after a projection of the particles onto the grid. The algorithm is based on a "watershed" segmentation of the computational volume into dense regions, followed by a merging of the segmented patches based on the saddle point topology of the density field. PHEW is capable of automatically detecting connected regions above the adopted density threshold, as well as the entire set of substructures within. Our algorithm is fully parallel and uses the MPI library. We describe in great detail the parallel algorithm and perform a scaling experiment which proves the capability of phew to run efficiently on massively parallel systems.

  3. Shadow Detection from Very High Resoluton Satellite Image Using Grabcut Segmentation and Ratio-Band Algorithms

    Science.gov (United States)

    Kadhim, N. M. S. M.; Mourshed, M.; Bray, M. T.

    2015-03-01

    Very-High-Resolution (VHR) satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour), the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates significant performance of

  4. Practical Constraint K-Segment Principal Curve Algorithms for Generating Railway GPS Digital Map

    Directory of Open Access Journals (Sweden)

    Dewang Chen

    2013-01-01

    Full Text Available In order to obtain a decent trade-off between the low-cost, low-accuracy Global Positioning System (GPS receivers and the requirements of high-precision digital maps for modern railways, using the concept of constraint K-segment principal curves (CKPCS and the expert knowledge on railways, we propose three practical CKPCS generation algorithms with reduced computational complexity, and thereafter more suitable for engineering applications. The three algorithms are named ALLopt, MPMopt, and DCopt, in which ALLopt exploits global optimization and MPMopt and DCopt apply local optimization with different initial solutions. We compare the three practical algorithms according to their performance on average projection error, stability, and the fitness for simple and complex simulated trajectories with noise data. It is found that ALLopt only works well for simple curves and small data sets. The other two algorithms can work better for complex curves and large data sets. Moreover, MPMopt runs faster than DCopt, but DCopt can work better for some curves with cross points. The three algorithms are also applied in generating GPS digital maps for two railway GPS data sets measured in Qinghai-Tibet Railway (QTR. Similar results like the ones in synthetic data are obtained. Because the trajectory of a railway is relatively simple and straight, we conclude that MPMopt works best according to the comprehensive considerations on the speed of computation and the quality of generated CKPCS. MPMopt can be used to obtain some key points to represent a large amount of GPS data. Hence, it can greatly reduce the data storage requirements and increase the positioning speed for real-time digital map applications.

  5. Development and validation of a segmentation-free polyenergetic algorithm for dynamic perfusion computed tomography.

    Science.gov (United States)

    Lin, Yuan; Samei, Ehsan

    2016-07-01

    Dynamic perfusion imaging can provide the morphologic details of the scanned organs as well as the dynamic information of blood perfusion. However, due to the polyenergetic property of the x-ray spectra, beam hardening effect results in undesirable artifacts and inaccurate CT values. To address this problem, this study proposes a segmentation-free polyenergetic dynamic perfusion imaging algorithm (pDP) to provide superior perfusion imaging. Dynamic perfusion usually is composed of two phases, i.e., a precontrast phase and a postcontrast phase. In the precontrast phase, the attenuation properties of diverse base materials (e.g., in a thorax perfusion exam, base materials can include lung, fat, breast, soft tissue, bone, and metal implants) can be incorporated to reconstruct artifact-free precontrast images. If patient motions are negligible or can be corrected by registration, the precontrast images can then be employed as a priori information to derive linearized iodine projections from the postcontrast images. With the linearized iodine projections, iodine perfusion maps can be reconstructed directly without the influence of various influential factors, such as iodine location, patient size, x-ray spectrum, and background tissue type. A series of simulations were conducted on a dynamic iodine calibration phantom and a dynamic anthropomorphic thorax phantom to validate the proposed algorithm. The simulations with the dynamic iodine calibration phantom showed that the proposed algorithm could effectively eliminate the beam hardening effect and enable quantitative iodine map reconstruction across various influential factors. The error range of the iodine concentration factors ([Formula: see text]) was reduced from [Formula: see text] for filtered back-projection (FBP) to [Formula: see text] for pDP. The quantitative results of the simulations with the dynamic anthropomorphic thorax phantom indicated that the maximum error of iodine concentrations can be reduced from

  6. Pharynx Anatomy

    Science.gov (United States)

    ... e.g. -historical Searches are case-insensitive Pharynx Anatomy Add to My Pictures View /Download : Small: 720x576 ... View Download Large: 3000x2400 View Download Title: Pharynx Anatomy Description: Anatomy of the pharynx; drawing shows the ...

  7. Vulva Anatomy

    Science.gov (United States)

    ... e.g. -historical Searches are case-insensitive Vulva Anatomy Add to My Pictures View /Download : Small: 720x634 ... View Download Large: 3000x2640 View Download Title: Vulva Anatomy Description: Anatomy of the vulva; drawing shows the ...

  8. Larynx Anatomy

    Science.gov (United States)

    ... e.g. -historical Searches are case-insensitive Larynx Anatomy Add to My Pictures View /Download : Small: 648x576 ... View Download Large: 2700x2400 View Download Title: Larynx Anatomy Description: Anatomy of the larynx; drawing shows the ...

  9. KmsGC: An Unsupervised Color Image Segmentation Algorithm Based on K-Means Clustering and Graph Cut

    Directory of Open Access Journals (Sweden)

    Binmei Liang

    2014-01-01

    Full Text Available For unsupervised color image segmentation, we propose a two-stage algorithm, KmsGC, that combines K-means clustering with graph cut. In the first stage, K-means clustering algorithm is applied to make an initial clustering, and the optimal number of clusters is automatically determined by a compactness criterion that is established to find clustering with maximum intercluster distance and minimum intracluster variance. In the second stage, a multiple terminal vertices weighted graph is constructed based on an energy function, and the image is segmented according to a minimum cost multiway cut. A large number of performance evaluations are carried out, and the experimental results indicate the proposed approach is effective compared to other existing image segmentation algorithms on the Berkeley image database.

  10. A region segmentation based algorithm for building crystal position lookup table in scintillation detector

    CERN Document Server

    Wang, Hai Peng; Liu, Shuang Quan; Fan, Xin; Cao, Xue Xiang; Chai, Pei; Shan, Bao Ci

    2014-01-01

    In scintillation detector, scintillation crystals are typically made into 2-dimension modular array. The location of incident gamma-ray need be calibrated due to spatial response nonlinearity. Generally, position histograms, the characteristic flood response of scintillation detectors, are used for position calibration. In this paper, a position calibration method based on crystal position lookup table which maps the inaccurate location calculated by Anger logic to the exact hitting crystal position has been proposed, Firstly, position histogram is segmented into disconnected regions. Then crystal marking points are labeled by finding the centroids of regions. Finally, crystal boundaries are determined and crystal position lookup table is generated. The scheme is evaluated by the whole-body PET scanner and breast dedicated SPECT detector developed by Institute of High Energy Physics, Chinese Academy of Sciences. The results demonstrate that the algorithm is accurate, efficient, robust and general purpose.

  11. A multiple-feature and multiple-kernel scene segmentation algorithm for humanoid robot.

    Science.gov (United States)

    Liu, Zhi; Xu, Shuqiong; Zhang, Yun; Chen, Chun Lung Philip

    2014-11-01

    This technical correspondence presents a multiple-feature and multiple-kernel support vector machine (MFMK-SVM) methodology to achieve a more reliable and robust segmentation performance for humanoid robot. The pixel wise intensity, gradient, and C1 SMF features are extracted via the local homogeneity model and Gabor filter, which would be used as inputs of MFMK-SVM model. It may provide multiple features of the samples for easier implementation and efficient computation of MFMK-SVM model. A new clustering method, which is called feature validity-interval type-2 fuzzy C-means (FV-IT2FCM) clustering algorithm, is proposed by integrating a type-2 fuzzy criterion in the clustering optimization process to improve the robustness and reliability of clustering results by the iterative optimization. Furthermore, the clustering validity is employed to select the training samples for the learning of the MFMK-SVM model. The MFMK-SVM scene segmentation method is able to fully take advantage of the multiple features of scene image and the ability of multiple kernels. Experiments on the BSDS dataset and real natural scene images demonstrate the superior performance of our proposed method. PMID:25248211

  12. An Iris Segmentation Algorithm based on Edge Orientation for Off-angle Iris Recognition

    Energy Technology Data Exchange (ETDEWEB)

    Karakaya, Mahmut [ORNL; Barstow, Del R [ORNL; Santos-Villalobos, Hector J [ORNL; Boehnen, Chris Bensing [ORNL

    2013-01-01

    Iris recognition is known as one of the most accurate and reliable biometrics. However, the accuracy of iris recognition systems depends on the quality of data capture and is negatively affected by several factors such as angle, occlusion, and dilation. In this paper, we present a segmentation algorithm for off-angle iris images that uses edge detection, edge elimination, edge classification, and ellipse fitting techniques. In our approach, we first detect all candidate edges in the iris image by using the canny edge detector; this collection contains edges from the iris and pupil boundaries as well as eyelash, eyelids, iris texture etc. Edge orientation is used to eliminate the edges that cannot be part of the iris or pupil. Then, we classify the remaining edge points into two sets as pupil edges and iris edges. Finally, we randomly generate subsets of iris and pupil edge points, fit ellipses for each subset, select ellipses with similar parameters, and average to form the resultant ellipses. Based on the results from real experiments, the proposed method shows effectiveness in segmentation for off-angle iris images.

  13. An iris segmentation algorithm based on edge orientation for off-angle iris recognition

    Science.gov (United States)

    Karakaya, Mahmut; Barstow, Del; Santos-Villalobos, Hector; Boehnen, Christopher

    2013-03-01

    Iris recognition is known as one of the most accurate and reliable biometrics. However, the accuracy of iris recognition systems depends on the quality of data capture and is negatively affected by several factors such as angle, occlusion, and dilation. In this paper, we present a segmentation algorithm for off-angle iris images that uses edge detection, edge elimination, edge classification, and ellipse fitting techniques. In our approach, we first detect all candidate edges in the iris image by using the canny edge detector; this collection contains edges from the iris and pupil boundaries as well as eyelash, eyelids, iris texture etc. Edge orientation is used to eliminate the edges that cannot be part of the iris or pupil. Then, we classify the remaining edge points into two sets as pupil edges and iris edges. Finally, we randomly generate subsets of iris and pupil edge points, fit ellipses for each subset, select ellipses with similar parameters, and average to form the resultant ellipses. Based on the results from real experiments, the proposed method shows effectiveness in segmentation for off-angle iris images.

  14. INTEGRATION OF SELF ORGANIZING FEATURE MAPS AND HONEY BEE MATING OPTIMIZATION ALGORITHM FOR MARKET SEGMENTATION

    Directory of Open Access Journals (Sweden)

    Babak Amiri

    2007-09-01

    Full Text Available This study is dedicated to proposing a two-stage method, which first uses Self-Organizing Feature Maps (SOM neural network to determine the number of clusters and cluster centroids, then uses honey bee mating optimization algorithm based on K-means algorithm to find the final solution. The results of simulated data via a Monte Carlo study show that the proposed method outperforms two other methods, SOM followed by K-means (Kuo, Ho & Hu, 2002a and SOM followed by GAK (Kuo, An, Wang & Chung, 2006, based on both within-cluster variations (SSW and the number of misclassification. In order to further demonstrate the proposed approach’s capability, a real-world problem of an internet bookstore market segmentation based on customer loyalty is employed. The RFM model is used for comparison of customers' loyalty. Then the proposed method is used to cluster the customers. The results also indicate that the proposed method is better than the other two methods.

  15. ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography

    Science.gov (United States)

    Berthon, Beatrice; Marshall, Christopher; Evans, Mererid; Spezi, Emiliano

    2016-07-01

    Accurate and reliable tumour delineation on positron emission tomography (PET) is crucial for radiotherapy treatment planning. PET automatic segmentation (PET-AS) eliminates intra- and interobserver variability, but there is currently no consensus on the optimal method to use, as different algorithms appear to perform better for different types of tumours. This work aimed to develop a predictive segmentation model, trained to automatically select and apply the best PET-AS method, according to the tumour characteristics. ATLAAS, the automatic decision tree-based learning algorithm for advanced segmentation is based on supervised machine learning using decision trees. The model includes nine PET-AS methods and was trained on a 100 PET scans with known true contour. A decision tree was built for each PET-AS algorithm to predict its accuracy, quantified using the Dice similarity coefficient (DSC), according to the tumour volume, tumour peak to background SUV ratio and a regional texture metric. The performance of ATLAAS was evaluated for 85 PET scans obtained from fillable and printed subresolution sandwich phantoms. ATLAAS showed excellent accuracy across a wide range of phantom data and predicted the best or near-best segmentation algorithm in 93% of cases. ATLAAS outperformed all single PET-AS methods on fillable phantom data with a DSC of 0.881, while the DSC for H&N phantom data was 0.819. DSCs higher than 0.650 were achieved in all cases. ATLAAS is an advanced automatic image segmentation algorithm based on decision tree predictive modelling, which can be trained on images with known true contour, to predict the best PET-AS method when the true contour is unknown. ATLAAS provides robust and accurate image segmentation with potential applications to radiation oncology.

  16. Global left ventricular function in cardiac CT. Evaluation of an automated 3D region-growing segmentation algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Muehlenbruch, Georg; Das, Marco; Hohl, Christian; Wildberger, Joachim E.; Guenther, Rolf W.; Mahnken, Andreas H. [University Hospital (RWTH) Aachen, Department of Diagnostic Radiology, Aachen (Germany); Rinck, Daniel; Flohr, Thomas G. [Siemens Medical Solutions, Forchheim (Germany); Koos, Ralf; Knackstedt, Christian [University Hospital (RWTH) Aachen, Department of Cardiology, Aachen (Germany)

    2006-05-15

    The purpose was to evaluate a new semi-automated 3D region-growing segmentation algorithm for functional analysis of the left ventricle in multislice CT (MSCT) of the heart. Twenty patients underwent contrast-enhanced MSCT of the heart (collimation 16 x 0.75 mm; 120 kV; 550 mAseff). Multiphase image reconstructions with 1-mm axial slices and 8-mm short-axis slices were performed. Left ventricular volume measurements (end-diastolic volume, end-systolic volume, ejection fraction and stroke volume) from manually drawn endocardial contours in the short axis slices were compared to semi-automated region-growing segmentation of the left ventricle from the 1-mm axial slices. The post-processing-time for both methods was recorded. Applying the new region-growing algorithm in 13/20 patients (65%), proper segmentation of the left ventricle was feasible. In these patients, the signal-to-noise ratio was higher than in the remaining patients (3.2{+-}1.0 vs. 2.6{+-}0.6). Volume measurements of both segmentation algorithms showed an excellent correlation (all P{<=}0.0001); the limits of agreement for the ejection fraction were 2.3{+-}8.3 ml. In the patients with proper segmentation the mean post-processing time using the region-growing algorithm was diminished by 44.2%. On the basis of a good contrast-enhanced data set, a left ventricular volume analysis using the new semi-automated region-growing segmentation algorithm is technically feasible, accurate and more time-effective. (orig.)

  17. 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

  18. Correction of oral contrast artifacts in CT-based attenuation correction of PET images using an automated segmentation algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Ahmadian, Alireza; Ay, Mohammad R.; Sarkar, Saeed [Medical Sciences/University of Tehran, Research Center for Science and Technology in Medicine, Tehran (Iran); Medical Sciences/University of Tehran, Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran (Iran); Bidgoli, Javad H. [Medical Sciences/University of Tehran, Research Center for Science and Technology in Medicine, Tehran (Iran); East Tehran Azad University, Department of Electrical and Computer Engineering, Tehran (Iran); Zaidi, Habib [Geneva University Hospital, Division of Nuclear Medicine, Geneva (Switzerland)

    2008-10-15

    Oral contrast is usually administered in most X-ray computed tomography (CT) examinations of the abdomen and the pelvis as it allows more accurate identification of the bowel and facilitates the interpretation of abdominal and pelvic CT studies. However, the misclassification of contrast medium with high-density bone in CT-based attenuation correction (CTAC) is known to generate artifacts in the attenuation map ({mu}map), thus resulting in overcorrection for attenuation of positron emission tomography (PET) images. In this study, we developed an automated algorithm for segmentation and classification of regions containing oral contrast medium to correct for artifacts in CT-attenuation-corrected PET images using the segmented contrast correction (SCC) algorithm. The proposed algorithm consists of two steps: first, high CT number object segmentation using combined region- and boundary-based segmentation and second, object classification to bone and contrast agent using a knowledge-based nonlinear fuzzy classifier. Thereafter, the CT numbers of pixels belonging to the region classified as contrast medium are substituted with their equivalent effective bone CT numbers using the SCC algorithm. The generated CT images are then down-sampled followed by Gaussian smoothing to match the resolution of PET images. A piecewise calibration curve was then used to convert CT pixel values to linear attenuation coefficients at 511 keV. The visual assessment of segmented regions performed by an experienced radiologist confirmed the accuracy of the segmentation and classification algorithms for delineation of contrast-enhanced regions in clinical CT images. The quantitative analysis of generated {mu}maps of 21 clinical CT colonoscopy datasets showed an overestimation ranging between 24.4% and 37.3% in the 3D-classified regions depending on their volume and the concentration of contrast medium. Two PET/CT studies known to be problematic demonstrated the applicability of the technique

  19. Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: The VESSEL12 study

    NARCIS (Netherlands)

    Rudyanto, R.D.; Kerkstra, S.; Rikxoort, E.M. van; Fetita, C.; Brillet, P.-Y.; Lefevre, C.; Xue, W.; Zhu, X; Liang, J.; Öksüz, I.; Ünay, D.; Kadipasaoglu, K.; Estépar, R.S.J.; Ross, J.C.; Washko, G.R.; Prieto, J.-C.; Hoyos, M.H.a.; Orkisz, M.; Meine, H.; Hüllebrand, M.; Stöcker, C.; Mir, F.L.; Naranjo, V.; Villanueva, E.; Staring, M.; Xiao, C.; Stoel, B.C.; Fabijanska, A.; Smistad, E.; Elster, A.C.; Lindseth, F.; Foruzan, A.H.; Kiros, R.; Popuri, K.; Cobzas, D.; Jimenez-Carretero, D.; Santos, A.; Ledesma-Carbayo, M.J.; Helmberger, M.; Urschler, M.; Pienn, M.; Bosboom, D.G.H.; Campo, A.; Prokop, M.; Jong, P.A. de; Solorzano, C.O. de; Muñoz-Barrutia, A.; Ginneken, B. van

    2014-01-01

    The {VESSEL12} ({VES}sel {SE}mentation in the {L}ung) challenge objectively compares the performance of different algorithms to identify vessels in thoracic computed tomography ({CT}) scans. Vessel segmentation is fundamental in computer aided processing of data generated by 3D imaging modalities. A

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

    International Nuclear Information System (INIS)

    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

  1. An Improved Character Segmentation Algorithm Based on Local Adaptive Thresholding Technique for Chinese NvShu Documents

    Directory of Open Access Journals (Sweden)

    Yangguang Sun

    2014-06-01

    Full Text Available For the structural characteristics of Chinese NvShu character, by combining the basic idea in LLT local threshold algorithm and introducing the maximal between-class variance algorithm into local windows, an improved character segmentation algorithm based on local adaptive thresholding technique for Chinese NvShu documents was presented in this paper. Because of designing the corresponding correction parameters for the threshold and using secondary search mechanism, our proposed method could not only automatically obtain local threshold, but also avoid the loss of the character image information and improve the accuracy of the character image segmentation. Experimental results demonstrated its capability to reduce the effect of background noise, especially for Chinese NvShu character images with uneven illumination and low contrast

  2. Segmentation of Coronary Angiograms Using Gabor Filters and Boltzmann Univariate Marginal Distribution Algorithm

    Science.gov (United States)

    Cervantes-Sanchez, Fernando; Hernandez-Aguirre, Arturo; Solorio-Meza, Sergio; Ornelas-Rodriguez, Manuel; Torres-Cisneros, Miguel

    2016-01-01

    This paper presents a novel method for improving the training step of the single-scale Gabor filters by using the Boltzmann univariate marginal distribution algorithm (BUMDA) in X-ray angiograms. Since the single-scale Gabor filters (SSG) are governed by three parameters, the optimal selection of the SSG parameters is highly desirable in order to maximize the detection performance of coronary arteries while reducing the computational time. To obtain the best set of parameters for the SSG, the area (Az) under the receiver operating characteristic curve is used as fitness function. Moreover, to classify vessel and nonvessel pixels from the Gabor filter response, the interclass variance thresholding method has been adopted. The experimental results using the proposed method obtained the highest detection rate with Az = 0.9502 over a training set of 40 images and Az = 0.9583 with a test set of 40 images. In addition, the experimental results of vessel segmentation provided an accuracy of 0.944 with the test set of angiograms. PMID:27738422

  3. Segmentation of Coronary Angiograms Using Gabor Filters and Boltzmann Univariate Marginal Distribution Algorithm

    Directory of Open Access Journals (Sweden)

    Fernando Cervantes-Sanchez

    2016-01-01

    Full Text Available This paper presents a novel method for improving the training step of the single-scale Gabor filters by using the Boltzmann univariate marginal distribution algorithm (BUMDA in X-ray angiograms. Since the single-scale Gabor filters (SSG are governed by three parameters, the optimal selection of the SSG parameters is highly desirable in order to maximize the detection performance of coronary arteries while reducing the computational time. To obtain the best set of parameters for the SSG, the area (Az under the receiver operating characteristic curve is used as fitness function. Moreover, to classify vessel and nonvessel pixels from the Gabor filter response, the interclass variance thresholding method has been adopted. The experimental results using the proposed method obtained the highest detection rate with Az=0.9502 over a training set of 40 images and Az=0.9583 with a test set of 40 images. In addition, the experimental results of vessel segmentation provided an accuracy of 0.944 with the test set of angiograms.

  4. Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm.

    Science.gov (United States)

    Onoma, D P; Ruan, S; Thureau, S; Nkhali, L; Modzelewski, R; Monnehan, G A; Vera, P; Gardin, I

    2014-12-01

    A segmentation algorithm based on the random walk (RW) method, called 3D-LARW, has been developed to delineate small tumors or tumors with a heterogeneous distribution of FDG on PET images. Based on the original algorithm of RW [1], we propose an improved approach using new parameters depending on the Euclidean distance between two adjacent voxels instead of a fixed one and integrating probability densities of labels into the system of linear equations used in the RW. These improvements were evaluated and compared with the original RW method, a thresholding with a fixed value (40% of the maximum in the lesion), an adaptive thresholding algorithm on uniform spheres filled with FDG and FLAB method, on simulated heterogeneous spheres and on clinical data (14 patients). On these three different data, 3D-LARW has shown better segmentation results than the original RW algorithm and the three other methods. As expected, these improvements are more pronounced for the segmentation of small or tumors having heterogeneous FDG uptake.

  5. An algorithm for target airplane segmentation & extraction%一种目标飞机分割提取方法

    Institute of Scientific and Technical Information of China (English)

    谷东格

    2016-01-01

    In this paper, an algorithm for target airplane segmentation & extraction was proposed. In order to segment &extract the target airplane quickly and accurately, the algorithm adopted GrabCut algorithm which was improved by using pyramid segment tactics and based on color Gaussian Mixture Model and iterative energy minimum. The test results show that in the majority situation, this algorithm can accurately segment&extract the target airplane without using any other interaction while its processing speed is almost five times in comparison to the primary algorithm.%提出了一种目标飞机分割提取方法,该方法采用改进的使用金字塔式分割策略的以彩色高斯混合模型GMM (Gaussian Mixture Model)和迭代能量最小化为基础的GrabCut算法,达到将目标飞机快速精确分割提取的目的。实验结果表明在多数情况下,只需围绕目标飞机画一个框无需额外交互,就可以快速的将目标飞机精确分割提取出来,即便是在某些情况下不能够将目标飞机精确提取分割也只需额外的少数交互就可以达到将目标飞机精确分割提取的目的。

  6. Consensus embedding: theory, algorithms and application to segmentation and classification of biomedical data

    Directory of Open Access Journals (Sweden)

    Viswanath Satish

    2012-02-01

    of high-dimensional biomedical data classification and segmentation problems. Our generalizable framework allows for improved representation and classification in the context of both imaging and non-imaging data. The algorithm offers a promising solution to problems that currently plague DR methods, and may allow for extension to other areas of biomedical data analysis.

  7. Paraganglioma Anatomy

    Science.gov (United States)

    ... e.g. -historical Searches are case-insensitive Paraganglioma Anatomy Add to My Pictures View /Download : Small: 648x576 ... View Download Large: 2700x2400 View Download Title: Paraganglioma Anatomy Description: Paraganglioma of the head and neck; drawing ...

  8. Tooth anatomy

    Science.gov (United States)

    ... page: //medlineplus.gov/ency/article/002214.htm Tooth anatomy To use the sharing features on this page, ... upper jawbone is called the maxilla. Images Tooth anatomy References Lingen MW. Head and neck. In: Kumar ...

  9. Eye Anatomy

    Science.gov (United States)

    ... News About Us Donate In This Section Eye Anatomy en Español email Send this article to a ... You at Risk For Glaucoma? Childhood Glaucoma Eye Anatomy Five Common Glaucoma Tests Glaucoma Facts and Stats ...

  10. Robottens Anatomi

    DEFF Research Database (Denmark)

    Antabi, Mimo

    Artiklen "Robottens Anatomi - mellem kunst og videnskab". Handler om brugen af robotter i kunstens og videnskabens verden.......Artiklen "Robottens Anatomi - mellem kunst og videnskab". Handler om brugen af robotter i kunstens og videnskabens verden....

  11. Hand Anatomy

    Science.gov (United States)

    ... Topics A-Z Videos Infographics Symptom Picker Hand Anatomy Hand Safety Fireworks Safety Lawnmower Safety Snowblower safety ... Topics A-Z Videos Infographics Symptom Picker Hand Anatomy Hand Safety Fireworks Safety Lawnmower Safety Snowblower safety ...

  12. Heart Anatomy

    Science.gov (United States)

    ... Incredible Machine Bonus poster (PDF) The Human Heart Anatomy Blood The Conduction System The Coronary Arteries The ... of the Leg Vasculature of the Torso Heart anatomy illustrations and animations for grades K-6. Heart ...

  13. Fingerprint Segmentation

    OpenAIRE

    Jomaa, Diala

    2009-01-01

    In this thesis, a new algorithm has been proposed to segment the foreground of the fingerprint from the image under consideration. The algorithm uses three features, mean, variance and coherence. Based on these features, a rule system is built to help the algorithm to efficiently segment the image. In addition, the proposed algorithm combine split and merge with modified Otsu. Both enhancements techniques such as Gaussian filter and histogram equalization are applied to enhance and improve th...

  14. Validation of Point Clouds Segmentation Algorithms Through Their Application to Several Case Studies for Indoor Building Modelling

    Science.gov (United States)

    Macher, H.; Landes, T.; Grussenmeyer, P.

    2016-06-01

    Laser scanners are widely used for the modelling of existing buildings and particularly in the creation process of as-built BIM (Building Information Modelling). However, the generation of as-built BIM from point clouds involves mainly manual steps and it is consequently time consuming and error-prone. Along the path to automation, a three steps segmentation approach has been developed. This approach is composed of two phases: a segmentation into sub-spaces namely floors and rooms and a plane segmentation combined with the identification of building elements. In order to assess and validate the developed approach, different case studies are considered. Indeed, it is essential to apply algorithms to several datasets and not to develop algorithms with a unique dataset which could influence the development with its particularities. Indoor point clouds of different types of buildings will be used as input for the developed algorithms, going from an individual house of almost one hundred square meters to larger buildings of several thousand square meters. Datasets provide various space configurations and present numerous different occluding objects as for example desks, computer equipments, home furnishings and even wine barrels. For each dataset, the results will be illustrated. The analysis of the results will provide an insight into the transferability of the developed approach for the indoor modelling of several types of buildings.

  15. A Fast Superpixel Segmentation Algorithm for PolSAR Images Based on Edge Refinement and Revised Wishart Distance

    Directory of Open Access Journals (Sweden)

    Yue Zhang

    2016-10-01

    Full Text Available The superpixel segmentation algorithm, as a preprocessing technique, should show good performance in fast segmentation speed, accurate boundary adherence and homogeneous regularity. A fast superpixel segmentation algorithm by iterative edge refinement (IER works well on optical images. However, it may generate poor superpixels for Polarimetric synthetic aperture radar (PolSAR images due to the influence of strong speckle noise and many small-sized or slim regions. To solve these problems, we utilized a fast revised Wishart distance instead of Euclidean distance in the local relabeling of unstable pixels, and initialized unstable pixels as all the pixels substituted for the initial grid edge pixels in the initialization step. Then, postprocessing with the dissimilarity measure is employed to remove the generated small isolated regions as well as to preserve strong point targets. Finally, the superiority of the proposed algorithm is validated with extensive experiments on four simulated and two real-world PolSAR images from Experimental Synthetic Aperture Radar (ESAR and Airborne Synthetic Aperture Radar (AirSAR data sets, which demonstrate that the proposed method shows better performance with respect to several commonly used evaluation measures, even with about nine times higher computational efficiency, as well as fine boundary adherence and strong point targets preservation, compared with three state-of-the-art methods.

  16. [Segmentation of Winter Wheat Canopy Image Based on Visual Spectral and Random Forest Algorithm].

    Science.gov (United States)

    Liu, Ya-dong; Cui, Ri-xian

    2015-12-01

    Digital image analysis has been widely used in non-destructive monitoring of crop growth and nitrogen nutrition status due to its simplicity and efficiency. It is necessary to segment winter wheat plant from soil background for accessing canopy cover, intensity level of visible spectrum (R, G, and B) and other color indices derived from RGB. In present study, according to the variation in R, G, and B components of sRGB color space and L*, a*, and b* components of CIEL* a* b* color space between wheat plant and soil background, the segmentation of wheat plant from soil background were conducted by the Otsu's method based on a* component of CIEL* a* b* color space, and RGB based random forest method, and CIEL* a* b* based random forest method, respectively. Also the ability to segment wheat plant from soil background was evaluated with the value of segmentation accuracy. The results showed that all three methods had revealed good ability to segment wheat plant from soil background. The Otsu's method had lowest segmentation accuracy in comparison with the other two methods. There were only little difference in segmentation error between the two random forest methods. In conclusion, the random forest method had revealed its capacity to segment wheat plant from soil background with only the visual spectral information of canopy image without any color components combinations or any color space transformation.

  17. [Segmentation of Winter Wheat Canopy Image Based on Visual Spectral and Random Forest Algorithm].

    Science.gov (United States)

    Liu, Ya-dong; Cui, Ri-xian

    2015-12-01

    Digital image analysis has been widely used in non-destructive monitoring of crop growth and nitrogen nutrition status due to its simplicity and efficiency. It is necessary to segment winter wheat plant from soil background for accessing canopy cover, intensity level of visible spectrum (R, G, and B) and other color indices derived from RGB. In present study, according to the variation in R, G, and B components of sRGB color space and L*, a*, and b* components of CIEL* a* b* color space between wheat plant and soil background, the segmentation of wheat plant from soil background were conducted by the Otsu's method based on a* component of CIEL* a* b* color space, and RGB based random forest method, and CIEL* a* b* based random forest method, respectively. Also the ability to segment wheat plant from soil background was evaluated with the value of segmentation accuracy. The results showed that all three methods had revealed good ability to segment wheat plant from soil background. The Otsu's method had lowest segmentation accuracy in comparison with the other two methods. There were only little difference in segmentation error between the two random forest methods. In conclusion, the random forest method had revealed its capacity to segment wheat plant from soil background with only the visual spectral information of canopy image without any color components combinations or any color space transformation. PMID:26964234

  18. Quantification of the myocardial area at risk using coronary CT angiography and Voronoi algorithm-based myocardial segmentation

    Energy Technology Data Exchange (ETDEWEB)

    Kurata, Akira; Kono, Atsushi; Coenen, Adriaan; Saru-Chelu, Raluca G.; Krestin, Gabriel P. [Erasmus University Medical Center, Department of Radiology, Rotterdam (Netherlands); Sakamoto, Tsuyoshi [AZE inc, Development Division, Chiyoda, Tokyo (Japan); Kido, Teruhito; Mochizuki, Teruhito [Ehime University Graduate School of Medicine, Department of Radiology, Toon, Ehime (Japan); Higashino, Hiroshi [Yotsuba Circulation Clinic, Department of Radiology, Matsuyama, Ehime (Japan); Abe, Mitsunori [Yotsuba Circulation Clinic, Department of Cardiology, Matsuyama, Ehime (Japan); Feyter, Pim J. de; Nieman, Koen [Erasmus University Medical Center, Department of Radiology, Rotterdam (Netherlands); Erasmus University Medical Center, Department of Cardiology, Rotterdam (Netherlands)

    2015-01-15

    The purpose of this study was to estimate the myocardial area at risk (MAAR) using coronary computed tomography angiography (CTA) and Voronoi algorithm-based myocardial segmentation in comparison with single-photon emission computed tomography (SPECT). Thirty-four patients with coronary artery disease underwent 128-slice coronary CTA, stress/rest thallium-201 SPECT, and coronary angiography (CAG). CTA-based MAAR was defined as the sum of all CAG stenosis (>50 %) related territories (the ratio of the left ventricular volume). Using automated quantification software (17-segment model, 5-point scale), SPECT-based MAAR was defined as the number of segments with a score above zero as compared to the total 17 segments by summed stress score (SSS), difference (SDS) score map, and comprehensive SPECT interpretation with either SSS or SDS best correlating CAG findings (SSS/SDS). Results were compared using Pearson's correlation coefficient. Forty-nine stenoses were observed in 102 major coronary territories. Mean value of CTA-based MAAR was 28.3 ± 14.0 %. SSS-based, SDS-based, and SSS/SDS-based MAAR was 30.1 ± 6.1 %, 20.1 ± 15.8 %, and 26.8 ± 15.7 %, respectively. CTA-based MAAR was significantly related to SPECT-based MAAR (r = 0.531 for SSS; r = 0.494 for SDS; r = 0.814 for SSS/SDS; P < 0.05 in each). CTA-based Voronoi algorithm myocardial segmentation reliably quantifies SPECT-based MAAR. (orig.)

  19. An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Xiao Ling

    2016-08-01

    Full Text Available This paper presents a novel image matching method for multi-source satellite images, which integrates global Shuttle Radar Topography Mission (SRTM data and image segmentation to achieve robust and numerous correspondences. This method first generates the epipolar lines as a geometric constraint assisted by global SRTM data, after which the seed points are selected and matched. To produce more reliable matching results, a region segmentation-based matching propagation is proposed in this paper, whereby the region segmentations are extracted by image segmentation and are considered to be a spatial constraint. Moreover, a similarity measure integrating Distance, Angle and Normalized Cross-Correlation (DANCC, which considers geometric similarity and radiometric similarity, is introduced to find the optimal correspondences. Experiments using typical satellite images acquired from Resources Satellite-3 (ZY-3, Mapping Satellite-1, SPOT-5 and Google Earth demonstrated that the proposed method is able to produce reliable and accurate matching results.

  20. Morphologic segmentation algorithms for extracting individual surface features from areal surface topography maps

    International Nuclear Information System (INIS)

    Areal segmentation, i.e. the partitioning of areal surface topography data into regions, has recently attracted significant research interest in surface metrology. In particular morphologic segmentation, i.e. partitioning into Maxwellian hills and dales—currently the only segmentation approach endorsed by ISO specification standards—has shown potential for capturing the salient traits of a surface, so that its surface texture can be better encoded by parameters. However, recent developments in dimensional metrology applied to structured surfaces with features of dimensions on the order of micrometres (micro-electromechanical system, microfluidics, etc), and many other studies aimed at characterizing individual features in unstructured surfaces (scratches, bumps, holes, etc), are showing the importance of segmentation for extracting localized features from areal data. In this work, morphologic segmentation is applied to a selected set of case studies of industrial relevance, involving structured, semi-structured and unstructured surfaces, where the main goal is not the assessment of surface texture, but the extraction of individual surface features. The examples are designed to provide an overview of the main advantages and issues when applying morphologic segmentation in a comprehensive set of application scenarios. (paper)

  1. Hemodynamic segmentation of brain perfusion images with delay and dispersion effects using an expectation-maximization algorithm.

    Directory of Open Access Journals (Sweden)

    Chia-Feng Lu

    Full Text Available Automatic identification of various perfusion compartments from dynamic susceptibility contrast magnetic resonance brain images can assist in clinical diagnosis and treatment of cerebrovascular diseases. The principle of segmentation methods was based on the clustering of bolus transit-time profiles to discern areas of different tissues. However, the cerebrovascular diseases may result in a delayed and dispersed local perfusion and therefore alter the hemodynamic signal profiles. Assessing the accuracy of the segmentation technique under delayed/dispersed circumstance is critical to accurately evaluate the severity of the vascular disease. In this study, we improved the segmentation method of expectation-maximization algorithm by using the results of hierarchical clustering on whitened perfusion data as initial parameters for a mixture of multivariate Gaussians model. In addition, Monte Carlo simulations were conducted to evaluate the performance of proposed method under different levels of delay, dispersion, and noise of signal profiles in tissue segmentation. The proposed method was used to classify brain tissue types using perfusion data from five normal participants, a patient with unilateral stenosis of the internal carotid artery, and a patient with moyamoya disease. Our results showed that the normal, delayed or dispersed hemodynamics can be well differentiated for patients, and therefore the local arterial input function for impaired tissues can be recognized to minimize the error when estimating the cerebral blood flow. Furthermore, the tissue in the risk of infarct and the tissue with or without the complementary blood supply from the communicating arteries can be identified.

  2. MUSE: MUlti-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters, and locally optimal atlas selection.

    Science.gov (United States)

    Doshi, Jimit; Erus, Guray; Ou, Yangming; Resnick, Susan M; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D; Furth, Susan; Davatzikos, Christos

    2016-02-15

    Atlas-based automated anatomical labeling is a fundamental tool in medical image segmentation, as it defines regions of interest for subsequent analysis of structural and functional image data. The extensive investigation of multi-atlas warping and fusion techniques over the past 5 or more years has clearly demonstrated the advantages of consensus-based segmentation. However, the common approach is to use multiple atlases with a single registration method and parameter set, which is not necessarily optimal for every individual scan, anatomical region, and problem/data-type. Different registration criteria and parameter sets yield different solutions, each providing complementary information. Herein, we present a consensus labeling framework that generates a broad ensemble of labeled atlases in target image space via the use of several warping algorithms, regularization parameters, and atlases. The label fusion integrates two complementary sources of information: a local similarity ranking to select locally optimal atlases and a boundary modulation term to refine the segmentation consistently with the target image's intensity profile. The ensemble approach consistently outperforms segmentations using individual warping methods alone, achieving high accuracy on several benchmark datasets. The MUSE methodology has been used for processing thousands of scans from various datasets, producing robust and consistent results. MUSE is publicly available both as a downloadable software package, and as an application that can be run on the CBICA Image Processing Portal (https://ipp.cbica.upenn.edu), a web based platform for remote processing of medical images. PMID:26679328

  3. Integer anatomy

    Energy Technology Data Exchange (ETDEWEB)

    Doolittle, R. [ONR, Arlington, VA (United States)

    1994-11-15

    The title integer anatomy is intended to convey the idea of a systematic method for displaying the prime decomposition of the integers. Just as the biological study of anatomy does not teach us all things about behavior of species neither would we expect to learn everything about the number theory from a study of its anatomy. But, some number-theoretic theorems are illustrated by inspection of integer anatomy, which tend to validate the underlying structure and the form as developed and displayed in this treatise. The first statement to be made in this development is: the way structure of the natural numbers is displayed depends upon the allowed operations.

  4. Multi-color space threshold segmentation and self-learning k-NN algorithm for surge test EUT status identification

    Science.gov (United States)

    Huang, Jian; Liu, Gui-xiong

    2016-09-01

    The identification of targets varies in different surge tests. A multi-color space threshold segmentation and self-learning k-nearest neighbor algorithm ( k-NN) for equipment under test status identification was proposed after using feature matching to identify equipment status had to train new patterns every time before testing. First, color space (L*a*b*, hue saturation lightness (HSL), hue saturation value (HSV)) to segment was selected according to the high luminance points ratio and white luminance points ratio of the image. Second, the unknown class sample S r was classified by the k-NN algorithm with training set T z according to the feature vector, which was formed from number of pixels, eccentricity ratio, compactness ratio, and Euler's numbers. Last, while the classification confidence coefficient equaled k, made S r as one sample of pre-training set T z '. The training set T z increased to T z+1 by T z ' if T z ' was saturated. In nine series of illuminant, indicator light, screen, and disturbances samples (a total of 21600 frames), the algorithm had a 98.65%identification accuracy, also selected five groups of samples to enlarge the training set from T 0 to T 5 by itself.

  5. Multi-color space threshold segmentation and self-learning k-NN algorithm for surge test EUT status identification

    Science.gov (United States)

    Huang, Jian; Liu, Gui-xiong

    2016-04-01

    The identification of targets varies in different surge tests. A multi-color space threshold segmentation and self-learning k-nearest neighbor algorithm (k-NN) for equipment under test status identification was proposed after using feature matching to identify equipment status had to train new patterns every time before testing. First, color space (L*a*b*, hue saturation lightness (HSL), hue saturation value (HSV)) to segment was selected according to the high luminance points ratio and white luminance points ratio of the image. Second, the unknown class sample S r was classified by the k-NN algorithm with training set T z according to the feature vector, which was formed from number of pixels, eccentricity ratio, compactness ratio, and Euler's numbers. Last, while the classification confidence coefficient equaled k, made S r as one sample of pre-training set T z '. The training set T z increased to T z+1 by T z if T z was saturated. In nine series of illuminant, indicator light, screen, and disturbances samples (a total of 21600 frames), the algorithm had a 98.65%identification accuracy, also selected five groups of samples to enlarge the training set from T 0 to T 5 by itself.

  6. Comparative evaluation of a novel 3D segmentation algorithm on in-treatment radiotherapy cone beam CT images

    Science.gov (United States)

    Price, Gareth; Moore, Chris

    2007-03-01

    Image segmentation and delineation is at the heart of modern radiotherapy, where the aim is to deliver as high a radiation dose as possible to a cancerous target whilst sparing the surrounding healthy tissues. This, of course, requires that a radiation oncologist dictates both where the tumour and any nearby critical organs are located. As well as in treatment planning, delineation is of vital importance in image guided radiotherapy (IGRT): organ motion studies demand that features across image databases are accurately segmented, whilst if on-line adaptive IGRT is to become a reality, speedy and correct target identification is a necessity. Recently, much work has been put into the development of automatic and semi-automatic segmentation tools, often using prior knowledge to constrain some grey level, or derivative thereof, interrogation algorithm. It is hoped that such techniques can be applied to organ at risk and tumour segmentation in radiotherapy. In this work, however, we make the assumption that grey levels do not necessarily determine a tumour's extent, especially in CT where the attenuation coefficient can often vary little between cancerous and normal tissue. In this context we present an algorithm that generates a discontinuity free delineation surface driven by user placed, evidence based support points. In regions of sparse user supplied information, prior knowledge, in the form of a statistical shape model, provides guidance. A small case study is used to illustrate the method. Multiple observers (between 3 and 7) used both the presented tool and a commercial manual contouring package to delineate the bladder on a serially imaged (10 cone beam CT volumes ) prostate patient. A previously presented shape analysis technique is used to quantitatively compare the observer variability.

  7. BIANCA (Brain Intensity AbNormality Classification Algorithm): A new tool for automated segmentation of white matter hyperintensities.

    Science.gov (United States)

    Griffanti, Ludovica; Zamboni, Giovanna; Khan, Aamira; Li, Linxin; Bonifacio, Guendalina; Sundaresan, Vaanathi; Schulz, Ursula G; Kuker, Wilhelm; Battaglini, Marco; Rothwell, Peter M; Jenkinson, Mark

    2016-11-01

    Reliable quantification of white matter hyperintensities of presumed vascular origin (WMHs) is increasingly needed, given the presence of these MRI findings in patients with several neurological and vascular disorders, as well as in elderly healthy subjects. We present BIANCA (Brain Intensity AbNormality Classification Algorithm), a fully automated, supervised method for WMH detection, based on the k-nearest neighbour (k-NN) algorithm. Relative to previous k-NN based segmentation methods, BIANCA offers different options for weighting the spatial information, local spatial intensity averaging, and different options for the choice of the number and location of the training points. BIANCA is multimodal and highly flexible so that the user can adapt the tool to their protocol and specific needs. We optimised and validated BIANCA on two datasets with different MRI protocols and patient populations (a "predominantly neurodegenerative" and a "predominantly vascular" cohort). BIANCA was first optimised on a subset of images for each dataset in terms of overlap and volumetric agreement with a manually segmented WMH mask. The correlation between the volumes extracted with BIANCA (using the optimised set of options), the volumes extracted from the manual masks and visual ratings showed that BIANCA is a valid alternative to manual segmentation. The optimised set of options was then applied to the whole cohorts and the resulting WMH volume estimates showed good correlations with visual ratings and with age. Finally, we performed a reproducibility test, to evaluate the robustness of BIANCA, and compared BIANCA performance against existing methods. Our findings suggest that BIANCA, which will be freely available as part of the FSL package, is a reliable method for automated WMH segmentation in large cross-sectional cohort studies. PMID:27402600

  8. Hepatic surgical anatomy.

    Science.gov (United States)

    Skandalakis, John E; Skandalakis, Lee J; Skandalakis, Panajiotis N; Mirilas, Petros

    2004-04-01

    The liver, the largest organ in the body, has been misunderstood at nearly all levels of organization, and there is a tendency to ignore details that do not fit the preconception. A complete presentation of the surgical anatomy of the liver includes the study of hepatic surfaces, margins, and fissures; the various classifications of lobes and segments; and the vasculature and lymphatics. A brief overview of the intrahepatic biliary tract is also presented.

  9. 基于小波分形的图像分割算法%Wavelet Fractal-Based Image Segment Algorithm

    Institute of Scientific and Technical Information of China (English)

    叶俊勇; 汪同庆; 彭健; 杨波

    2002-01-01

    The image of shoe leather lumen is not very satisfaction because of technology of CT. The smart imagesegment is the base of getting smart measurement data. An algorithm of image segment based on wavelet and fractalhas been proposed after analyzing the specialty of images. The image is decomposed through wavelet multi-resolutiondecomposition , and the fractal dimension is calculated by the decomposed image. This approach is more satisfied thangeneral method in image segment of shoe leather lumen image by CT. This algorithm can segment the edge of shoe lu-men exactly. The experimentations prove the approach is rational.

  10. Comparison of segmentation algorithms for cow contour extraction from natural barn background in side view images

    NARCIS (Netherlands)

    Hertem, van T.; Alchanatis, V.; Antler, A.; Maltz, E.; Halachmi, I.; Schlageter Tello, A.A.; Lokhorst, C.; Viazzi, S.; Romanini, C.E.B.; Pluk, A.; Bahr, C.; Berckmans, D.

    2013-01-01

    Computer vision techniques are a means to extract individual animal information such as weight, activity and calving time in intensive farming. Automatic detection requires adequate image pre-processing such as segmentation to precisely distinguish the animal from its background. For some analyses s

  11. THE SEGMENTATION OF A TEXT LINE FOR A HANDWRITTEN UNCONSTRAINED DOCUMENT USING THINING ALGORITHM

    NARCIS (Netherlands)

    Tsuruoka, S.; Adachi, Y.; Yoshikawa, T.

    2004-01-01

    For printed documents, the projection analysis of black pixels is widely used for the segmentation of a text line. However, for handwritten documents, we think that the projection analysis is not appropriate, as the separating border line of a text line is not a straight line on a paper with no rule

  12. 基于线段特征匹配的EKF-SLAM算法%EKF-SLAM Algorithm Based on Line Segment Matching

    Institute of Scientific and Technical Information of China (English)

    张国良; 汤文俊; 敬斌; 程展欣

    2012-01-01

    针对EKF-SLAM算法在机器人被“绑架”时失效的问题,提出一种新的基于线段特征匹配的EKF-SLAM算法——EKFLineSLAM算法.该算法在线段特征观测模型和改进的基于逐点搜索的线段提取算法的基础上,将线段特征匹配引入EKF-SLAM算法,并对线段长度和姿态角进行EKF更新,创建环境的线段特征地图.在未知室内结构化环境中,将该算法与弱匹配EKFLineSLAM算法进行比较,验证了EKFLineSLAM算法在结构化环境中克服机器人“绑架”问题的可行性和有效性.%For the problem of EKF-SLAM algorithm being invalid when robot is kidnapped, a new EKF-SLAM algorithm called "EKF-LineSLAM Algorithm" based on line segment matching is presented. This algorithm is based on the line segment observation model, and the improved line segment extraction algorithm based on point by point search. It introduces the line segment match in the EKF-SLAM algorithm, and renews the line segment's length and posture angle by EKF to find the line segment characteristic map. Finally, the presented algorithm and the weak matching EKFLineSLAM algorithm are compared in an unknown structured indoor environment. The comparison results confirm the feasibility and the effectiveness of the EKFLineSLAM algorithm for the kidnapped robot problem in structured environments.

  13. A Semiautomatic Segmentation Algorithm for Extracting the Complete Structure of Acini from Synchrotron Micro-CT Images

    Directory of Open Access Journals (Sweden)

    Luosha Xiao

    2013-01-01

    Full Text Available Pulmonary acinus is the largest airway unit provided with alveoli where blood/gas exchange takes place. Understanding the complete structure of acinus is necessary to measure the pathway of gas exchange and to simulate various mechanical phenomena in the lungs. The usual manual segmentation of a complete acinus structure from their experimentally obtained images is difficult and extremely time-consuming, which hampers the statistical analysis. In this study, we develop a semiautomatic segmentation algorithm for extracting the complete structure of acinus from synchrotron micro-CT images of the closed chest of mouse lungs. The algorithm uses a combination of conventional binary image processing techniques based on the multiscale and hierarchical nature of lung structures. Specifically, larger structures are removed, while smaller structures are isolated from the image by repeatedly applying erosion and dilation operators in order, adjusting the parameter referencing to previously obtained morphometric data. A cluster of isolated acini belonging to the same terminal bronchiole is obtained without floating voxels. The extracted acinar models above 98% agree well with those extracted manually. The run time is drastically shortened compared with manual methods. These findings suggest that our method may be useful for taking samples used in the statistical analysis of acinus.

  14. A Benchmark Data Set to Evaluate the Illumination Robustness of Image Processing Algorithms for Object Segmentation and Classification.

    Science.gov (United States)

    Khan, Arif Ul Maula; Mikut, Ralf; Reischl, Markus

    2015-01-01

    Developers of image processing routines rely on benchmark data sets to give qualitative comparisons of new image analysis algorithms and pipelines. Such data sets need to include artifacts in order to occlude and distort the required information to be extracted from an image. Robustness, the quality of an algorithm related to the amount of distortion is often important. However, using available benchmark data sets an evaluation of illumination robustness is difficult or even not possible due to missing ground truth data about object margins and classes and missing information about the distortion. We present a new framework for robustness evaluation. The key aspect is an image benchmark containing 9 object classes and the required ground truth for segmentation and classification. Varying levels of shading and background noise are integrated to distort the data set. To quantify the illumination robustness, we provide measures for image quality, segmentation and classification success and robustness. We set a high value on giving users easy access to the new benchmark, therefore, all routines are provided within a software package, but can as well easily be replaced to emphasize other aspects.

  15. SAR IMAGE SEGMENTATION WITH UNKNOWN NUMBER OF CLASSES COMBINED VORONOI TESSELLATION AND RJMCMC ALGORITHM

    OpenAIRE

    Zhao, Q. H.; Li, Y.; Y Wang

    2016-01-01

    This paper presents a novel segmentation method for automatically determining the number of classes in Synthetic Aperture Radar (SAR) images by combining Voronoi tessellation and Reversible Jump Markov Chain Monte Carlo (RJMCMC) strategy. Instead of giving the number of classes a priori, it is considered as a random variable and subject to a Poisson distribution. Based on Voronoi tessellation, the image is divided into homogeneous polygons. By Bayesian paradigm, a posterior distribut...

  16. Silence and Speech Segmentation for Noisy Speech Using a Wavelet Based Algorithm

    Institute of Scientific and Technical Information of China (English)

    MEI Xiaodan; SUN Shenghe

    2001-01-01

    In this paper, we present a newmethod to segment silence and speech for noisy con-dition. Conventional segmentation methods usuallylack in robustness under high background noise be-cause they are mostly dependent on amplitude or en-ergy of speech signal. For speech signal, the corre-lation between the neighbor frequency bands includ-ing most speech energy is high and little effected bynoise, but the correlation between the neighbor fre-quency bands of noise is low. So we employ the cross-correlation of neighbor sub-bands of signal to locatespeech and noise. We first performed the wavelettransform to denoise and further calculated the cross-correlation between the wavelet coefficients in two se-lected sub-bands and then used the standard deviationof cross-correlation coefficients to segment speech andnoise duration. The simulation and the result analysisshow that this method is efficient for the low-energyphonemes even in low signal-to-noise ratio, and theamount of computation is less.

  17. Study of the vocal signal in the amplitude-time representation. Speech segmentation and recognition algorithms

    International Nuclear Information System (INIS)

    This dissertation exposes an acoustical and phonetical study of vocal signal. The complex pattern of the signal is segmented into simple sub-patterns and each one of these sub-patterns may be segmented again into another more simplest patterns with lower level. Application of pattern recognition techniques facilitates on one hand this segmentation and on the other hand the definition of the structural relations between the sub-patterns. Particularly, we have developed syntactic techniques in which the rewriting rules, context-sensitive, are controlled by predicates using parameters evaluated on the sub-patterns themselves. This allow to generalize a pure syntactic analysis by adding a semantic information. The system we expose, realizes pre-classification and a partial identification of the phonemes as also the accurate detection of each pitch period. The voice signal is analysed directly using the amplitude-time representation. This system has been implemented on a mini-computer and it works in the real time. (author)

  18. A Clustering Algorithm for Ecological Stream Segment Identification from Spatially Extensive Digital Databases

    Science.gov (United States)

    Brenden, T. O.; Clark, R. D.; Wiley, M. J.; Seelbach, P. W.; Wang, L.

    2005-05-01

    Remote sensing and geographic information systems have made it possible to attribute variables for streams at increasingly detailed resolutions (e.g., individual river reaches). Nevertheless, management decisions still must be made at large scales because land and stream managers typically lack sufficient resources to manage on an individual reach basis. Managers thus require a method for identifying stream management units that are ecologically similar and that can be expected to respond similarly to management decisions. We have developed a spatially-constrained clustering algorithm that can merge neighboring river reaches with similar ecological characteristics into larger management units. The clustering algorithm is based on the Cluster Affinity Search Technique (CAST), which was developed for clustering gene expression data. Inputs to the clustering algorithm are the neighbor relationships of the reaches that comprise the digital river network, the ecological attributes of the reaches, and an affinity value, which identifies the minimum similarity for merging river reaches. In this presentation, we describe the clustering algorithm in greater detail and contrast its use with other methods (expert opinion, classification approach, regular clustering) for identifying management units using several Michigan watersheds as a backdrop.

  19. Robottens Anatomi

    DEFF Research Database (Denmark)

    Antabi, Mimo

    Rapport der beskriver de samlede erfaringer fra arbejdet med produktionen af teaterforestillingen Robottens Anatomi. Indehoder bl.a. interviews med medvirkende, bidrag fra instruktør, synopsis, beskrivelse af scenografi mv.......Rapport der beskriver de samlede erfaringer fra arbejdet med produktionen af teaterforestillingen Robottens Anatomi. Indehoder bl.a. interviews med medvirkende, bidrag fra instruktør, synopsis, beskrivelse af scenografi mv....

  20. Algorithm Research of Fingerprint Image Segmentation%指纹图像分割算法的研究

    Institute of Scientific and Technical Information of China (English)

    张伟

    2011-01-01

    Fingerprint image segmentation as an important pan of fingerprint recognition, is the right basis of fingerprint recognition, and only select the appropriate fingerprint segmentation, effective separation of the fingerprint image from the foreground and background in order to follow-up treatment, can realize the effective fingerprint recognition; otherwise will increase the number of false features, affect the final match of the fingerprint can not be valid identification. In this paper, fingerprint image segmentation, the analysis of variance and consistency of orientation fingerprint problem, design a smooth contour with the fingerprint segmentation algorithm, simulation results show that the algorithm can accurately extract the background from the fingerprint image, and can be removed irregular interruption of the edge endpoints, to ensure effective fingerprint areas are intact%指纹图像分割作为指纹识别的重要部分,是正确进行指纹识别的的基础,只有选择合适的指纹分割方法,有效地分离出指纹图像的前景和背景两部分,才能进行后续的处理,才能对指纹进行有效的识别;否则由于背景区域对前景区域影响会增加许多虚假特征,影响最终匹配,不能有效地对指纹进行识别;在指纹图像分割方面,分析了指纹的方差和方向一致性问题,设计了一种具有光滑轮廓线的指纹分割算法,仿真结果表明,该算法能够从指纹背景中准确提取指纹图像,并且能够除去边缘非正常中断端点,保证有效指纹区得到完整保留.

  1. An image segmentation method based on accelerated Dijkstra algorithm%一种基于加速Dijkstra算法的图像分割技术

    Institute of Scientific and Technical Information of China (English)

    戴虹

    2011-01-01

    An optimal path searching algorithm called " Dijkstra Algorithm" is used for image segmentation. An accelerated Dijkstra Algorithm is presented to reduce the calculation work of the classical Dijkstra algorithm and to accelerate its operating speed. Live-Wire image segmentation method based on the accelerated Dijkstra algorithm is presented to sketch the object' s contour of interest in an image and area filling method is used to segment the object. The experimental results show that the algorithm can run image segmentation successfully and has good anti-noise ability, in addition, the algorithm has less interactive times than that of the manual segmentation method and run faster than the original live-Wire algorithm.%利用最短路径搜索算法中的Dijkstra算法进行图像分割.提出一种加速Dijkstra算法减小经典Dijkstra算法的运算量,以加快其运行速度.提出基于加速Dijkstra算法的Live-Wire图像分割方法勾画出一幅图像中感兴趣目标的轮廓并采用边界填充分割该目标.实验结果表明该算法能正确地进行图像分割,抗噪声性能好,与手工分割法相比交互次数较少,与原Live-Wire分割算法相比运行时间较短.

  2. Image Based Hair Segmentation Algorithm for the Application of Automatic Facial Caricature Synthesis

    OpenAIRE

    2014-01-01

    Hair is a salient feature in human face region and are one of the important cues for face analysis. Accurate detection and presentation of hair region is one of the key components for automatic synthesis of human facial caricature. In this paper, an automatic hair detection algorithm for the application of automatic synthesis of facial caricature based on a single image is proposed. Firstly, hair regions in training images are labeled manually and then the hair position prior distributions an...

  3. Aerosol Plume Detection Algorithm Based on Image Segmentation of Scanning Atmospheric Lidar Data

    Energy Technology Data Exchange (ETDEWEB)

    Weekley, R. Andrew; Goodrich, R. Kent; Cornman, Larry B.

    2016-04-01

    An image-processing algorithm has been developed to identify aerosol plumes in scanning lidar backscatter data. The images in this case consist of lidar data in a polar coordinate system. Each full lidar scan is taken as a fixed image in time, and sequences of such scans are considered functions of time. The data are analyzed in both the original backscatter polar coordinate system and a lagged coordinate system. The lagged coordinate system is a scatterplot of two datasets, such as subregions taken from the same lidar scan (spatial delay), or two sequential scans in time (time delay). The lagged coordinate system processing allows for finding and classifying clusters of data. The classification step is important in determining which clusters are valid aerosol plumes and which are from artifacts such as noise, hard targets, or background fields. These cluster classification techniques have skill since both local and global properties are used. Furthermore, more information is available since both the original data and the lag data are used. Performance statistics are presented for a limited set of data processed by the algorithm, where results from the algorithm were compared to subjective truth data identified by a human.

  4. Study of system for segmentation of images and elaboration of algorithms for three dimensional scene reconstruction

    International Nuclear Information System (INIS)

    The aim of this paper is the presentation of a series of methodologies to recognize and to obtain a three-dimensional reconstruction of an inner architectural scene, using a gray level image obtained using a TV camera. In the first part of the work, a series of methods used to find the edges in an effective way are critically compared, obtaining a binary image, and then the application of the Hough transform to such binary image to find the straight lines in the original image are discussed. In the second part, an algorithm is shown in order to find the vanishing points in such image

  5. A novel method for retinal exudate segmentation using signal separation algorithm.

    Science.gov (United States)

    Imani, Elaheh; Pourreza, Hamid-Reza

    2016-09-01

    Diabetic retinopathy is one of the major causes of blindness in the world. Early diagnosis of this disease is vital to the prevention of visual loss. The analysis of retinal lesions such as exudates, microaneurysms and hemorrhages is a prerequisite to detect diabetic disorders such as diabetic retinopathy and macular edema in fundus images. This paper presents an automatic method for the detection of retinal exudates. The novelty of this method lies in the use of Morphological Component Analysis (MCA) algorithm to separate lesions from normal retinal structures to facilitate the detection process. In the first stage, vessels are separated from lesions using the MCA algorithm with appropriate dictionaries. Then, the lesion part of retinal image is prepared for the detection of exudate regions. The final exudate map is created using dynamic thresholding and mathematical morphologies. Performance of the proposed method is measured on the three publicly available DiaretDB, HEI-MED and e-ophtha datasets. Accordingly, the AUC of 0.961 and 0.948 and 0.937 is achieved respectively, which are greater than most of the state-of-the-art methods. PMID:27393810

  6. Liver Tumor Segmentation from MR Images Using 3D Fast Marching Algorithm and Single Hidden Layer Feedforward Neural Network

    Directory of Open Access Journals (Sweden)

    Trong-Ngoc Le

    2016-01-01

    Full Text Available Objective. Our objective is to develop a computerized scheme for liver tumor segmentation in MR images. Materials and Methods. Our proposed scheme consists of four main stages. Firstly, the region of interest (ROI image which contains the liver tumor region in the T1-weighted MR image series was extracted by using seed points. The noise in this ROI image was reduced and the boundaries were enhanced. A 3D fast marching algorithm was applied to generate the initial labeled regions which are considered as teacher regions. A single hidden layer feedforward neural network (SLFN, which was trained by a noniterative algorithm, was employed to classify the unlabeled voxels. Finally, the postprocessing stage was applied to extract and refine the liver tumor boundaries. The liver tumors determined by our scheme were compared with those manually traced by a radiologist, used as the “ground truth.” Results. The study was evaluated on two datasets of 25 tumors from 16 patients. The proposed scheme obtained the mean volumetric overlap error of 27.43% and the mean percentage volume error of 15.73%. The mean of the average surface distance, the root mean square surface distance, and the maximal surface distance were 0.58 mm, 1.20 mm, and 6.29 mm, respectively.

  7. The application of genetic algorithm in medical image-segmentation problems%遗传算法在医学图像分割中的应用

    Institute of Scientific and Technical Information of China (English)

    刘月明; 易东

    2001-01-01

    Image segmentation is a key step of image processing,and it is a hard work too. The experts of this field have tried to find a suitable algorithm for image segmentation for a long term,however,there is not a algorithm is generally accepted till now. J. Holland created genetic algorithm(abbreviation :GA) in 1973. This algorithm has been used in many fields successfully ,and has been introduced to image segmentation field by exports. The principles of image segmentation and algorithm are stated in this article. The author mainly expounded the application of GA in medical image segmentation field in recently years.%图像分割(lmage Segmentation)是图像处理中的主要问题,同时又是一个学术难题,长期以来人们在努力寻找进行图像分割的算法,到目前为止还没有一个普遍认可的算法。1973年,美国教授J.Holland提出了遗传算法(Genetic Algo-rithm,GA),在很多领域获得进展,并在90年代被学者引入图像分割领域。本文简要介绍了图像分割及遗传算法的基本原理,着重探讨了近年来遗传算法在图像分割一个重要的应用领域——医学图像分割领域中的应用。

  8. Fruit image segmentation based on evolutionary algorithm%基于演化算法的水果图像分割

    Institute of Scientific and Technical Information of China (English)

    彭红星; 邹湘军; 陈琰; 杨磊; 熊俊涛; 陈燕

    2014-01-01

    An improved evolutionary algorithm based on queen mating combined with elite and truncated choices by stages was proposed for fruit image segmentation, which was appropriate for the demand of the picking robot for real-time image and adaptive processing algorithms. The 8 bit binary code was used to correspond with the gray value of the fruit image in the improved evolutionary algorithm. The number of the initial population was set to 12 in the phase of the population initialized and the corresponding individual values, which ranged between 0 and 255, were generated by the random function. The twelve random numbers were the initial values of the evolutionary algorithm. Then an improved Otsu algorithm formula was selected as the fitness function. In the selection phase, the iterative process was divided into before stage, middle stage, and after stage, which were respectively used by queen mating algorithm, elitist choices strategy, and truncated choices strategy to select the fitness value. In the first stage, the individuals were produced by a random function and then the best individual (queen) of the evolutionary algorithm was hybridized with the rest of the individuals (including the randomly generated individuals) to generate new individuals. Finally, the individuals with the smallest fitness values were replaced by the new individuals. In the second stage, the elitist choices strategy was used and the individual with the smallest fitness value in the current generation was replaced by the individual with the highest fitness value in the previous generation. In the third stage, the truncated choices strategy was used and the last half of the individuals with the smallest fitness value in the current generation was replaced by the same number of individuals with the highest fitness value in the previous generation. This not only ensures the diversity of the population, but also overcomes the disadvantage of local optimized and too fast a convergence of the

  9. Stedets Anatomi

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel

    Titlen på denne ph.d.-afhandling, Stedets Anatomi – en teoretisk undersøgelse af stedets og rumlighedens betydning for leg, computerspil og læring, skitserer ikke kun afhandlingens teoretiske dimensionering, men også dens analytiske bliks tematik i forbindelse med undersøgelsen af fænomenerne leg...

  10. Regulatory Anatomy

    DEFF Research Database (Denmark)

    Hoeyer, Klaus

    2015-01-01

    This article proposes the term “safety logics” to understand attempts within the European Union (EU) to harmonize member state legislation to ensure a safe and stable supply of human biological material for transplants and transfusions. With safety logics, I refer to assemblages of discourses, le...... they arise. In short, I expose the regulatory anatomy of the policy landscape....

  11. An Algorithm of Multiscale Segmentation for Documen Image%一种文档图像多尺度分割算法

    Institute of Scientific and Technical Information of China (English)

    朱庆生; 舒润震; 朱征宇

    2003-01-01

    Segmenting a document image into text and picture areas is very important for compressing efficiently document images. This paper introduces an algorithm of multiscale image segmentation for document image compression,which uses of wavelet-domain hidden Markov tree model in order to directly calculate the parameter of model based on original image to be segmented,and to obtain multiscale classification and segmentation of image. The idea of the method is to combine several new technologies such as multilevel wavelet transform,multiscale decision,across-scale dependencies and joint probability density function. The paper describes in detail the concept of the dyadic block,the correspondency between wavelets and dyadic blocks based on quad-tree,the hidden Markov model and multiscale likelihood computation.

  12. 对中文分词歧义消除算法的研究%Research on the Algorithm of Eliminating Word Segmentation Ambiguity

    Institute of Scientific and Technical Information of China (English)

    谷瑞

    2015-01-01

    介绍中文分词算法的理论知识,通过介绍歧义存在的种类,分析分词结果出现歧义的必然性.提出改进"退一字组合法",实现歧义消除.在保持切分速度的前提下,提高切分的精度.为搜索引擎建立索引奠定良好的基础.%Having introduced the theory of Chinese word segmentation algorithm,this paper proposes to improve"the back one word combination"by analyzing the categories of word segmentation ambiguity and its inevitability in order to eliminate it and enhance the precision of segmentation while maintaining the segmentation rate. As a result, it lays solid foundation for search engines to establish indexes.

  13. Adaptive thresholding algorithm based on SAR images and wind data to segment oil spills along the northwest coast of the Iberian Peninsula

    International Nuclear Information System (INIS)

    Highlights: ► We present an adaptive thresholding algorithm to segment oil spills. ► The segmentation algorithm is based on SAR images and wind field estimations. ► A Database of oil spill confirmations was used for the development of the algorithm. ► Wind field estimations have demonstrated to be useful for filtering look-alikes. ► Parallel programming has been successfully used to minimize processing time. - Abstract: Satellite Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillage on the ocean’s surface. Several surveillance applications have been developed based on this technology. Environmental variables such as wind speed should be taken into account for better SAR image segmentation. This paper presents an adaptive thresholding algorithm for detecting oil spills based on SAR data and a wind field estimation as well as its implementation as a part of a functional prototype. The algorithm was adapted to an important shipping route off the Galician coast (northwest Iberian Peninsula) and was developed on the basis of confirmed oil spills. Image testing revealed 99.93% pixel labelling accuracy. By taking advantage of multi-core processor architecture, the prototype was optimized to get a nearly 30% improvement in processing time.

  14. Segmentation algorithm for non-stationary compound Poisson processes. With an application to inventory time series of market members in a financial market

    Science.gov (United States)

    Tóth, B.; Lillo, F.; Farmer, J. D.

    2010-11-01

    We introduce an algorithm for the segmentation of a class of regime switching processes. The segmentation algorithm is a non parametric statistical method able to identify the regimes (patches) of a time series. The process is composed of consecutive patches of variable length. In each patch the process is described by a stationary compound Poisson process, i.e. a Poisson process where each count is associated with a fluctuating signal. The parameters of the process are different in each patch and therefore the time series is non-stationary. Our method is a generalization of the algorithm introduced by Bernaola-Galván, et al. [Phys. Rev. Lett. 87, 168105 (2001)]. We show that the new algorithm outperforms the original one for regime switching models of compound Poisson processes. As an application we use the algorithm to segment the time series of the inventory of market members of the London Stock Exchange and we observe that our method finds almost three times more patches than the original one.

  15. The Anatomy of Learning Anatomy

    Science.gov (United States)

    Wilhelmsson, Niklas; Dahlgren, Lars Owe; Hult, Hakan; Scheja, Max; Lonka, Kirsti; Josephson, Anna

    2010-01-01

    The experience of clinical teachers as well as research results about senior medical students' understanding of basic science concepts has much been debated. To gain a better understanding about how this knowledge-transformation is managed by medical students, this work aims at investigating their ways of setting about learning anatomy.…

  16. MEDICAL IMAGE SEGMENTATION FOR ANATOMICAL KNOWLEDGE EXTRACTION

    Directory of Open Access Journals (Sweden)

    Ms Maya Eapen

    2014-01-01

    Full Text Available Computed Tomography-Angiography (CTA images of the abdomen, followed by precise segmentation and subsequent computation of shape based features of liver play an important role in hepatic surgery, patient/donor diagnosis during liver transplantation and at various treatment stages. Nevertheless, the issues like intensity similarity and Partial Volume Effect (PVE between the neighboring organs; left the task of liver segmentation critical. The accurate segmentation of liver helps the surgeons to perfectly classify the patients based on their liver anatomy which in turn helps them in the treatment decision phase. In this study, we propose an effective Advanced Region Growing (ARG algorithm for segmentation of liver from CTA images. The performance of the proposed technique was tested with several CTA images acquired across a wide range of patients. The proposed ARG algorithm identifies the liver regions on the images based on the statistical features (intensity distribution and orientation value. The proposed technique addressed the aforementioned issues and been evaluated both quantitatively and qualitatively. For quantitative analysis proposed method was compared with manual segmentation (gold standard. The method was also compared with standard region growing.

  17. A modified Seeded Region Growing algorithm for vessel segmentation in breast MRI images for investigating the nature of potential lesions

    Science.gov (United States)

    Glotsos, D.; Vassiou, K.; Kostopoulos, S.; Lavdas, El; Kalatzis, I.; Asvestas, P.; Arvanitis, D. L.; Fezoulidis, I. V.; Cavouras, D.

    2014-03-01

    The role of Magnetic Resonance Imaging (MRI) as an alternative protocol for screening of breast cancer has been intensively investigated during the past decade. Preliminary research results have indicated that gadolinium-agent administrative MRI scans may reveal the nature of breast lesions by analyzing the contrast-agent's uptake time. In this study, we attempt to deduce the same conclusion, however, from a different perspective by investigating, using image processing, the vascular network of the breast at two different time intervals following the administration of gadolinium. Twenty cases obtained from a 3.0-T MRI system (SIGNA HDx; GE Healthcare) were included in the study. A new modification of the Seeded Region Growing (SRG) algorithm was used to segment vessels from surrounding background. Delineated vessels were investigated by means of their topology, morphology and texture. Results have shown that it is possible to estimate the nature of the lesions with approximately 94.4% accuracy, thus, it may be claimed that the breast vascular network does encodes useful, patterned, information, which can be used for characterizing breast lesions.

  18. Feasibility of a semi-automated contrast-oriented algorithm for tumor segmentation in retrospectively gated PET images: phantom and clinical validation

    Science.gov (United States)

    Carles, Montserrat; Fechter, Tobias; Nemer, Ursula; Nanko, Norbert; Mix, Michael; Nestle, Ursula; Schaefer, Andrea

    2015-12-01

    PET/CT plays an important role in radiotherapy planning for lung tumors. Several segmentation algorithms have been proposed for PET tumor segmentation. However, most of them do not take into account respiratory motion and are not well validated. The aim of this work was to evaluate a semi-automated contrast-oriented algorithm (COA) for PET tumor segmentation adapted to retrospectively gated (4D) images. The evaluation involved a wide set of 4D-PET/CT acquisitions of dynamic experimental phantoms and lung cancer patients. In addition, segmentation accuracy of 4D-COA was compared with four other state-of-the-art algorithms. In phantom evaluation, the physical properties of the objects defined the gold standard. In clinical evaluation, the ground truth was estimated by the STAPLE (Simultaneous Truth and Performance Level Estimation) consensus of three manual PET contours by experts. Algorithm evaluation with phantoms resulted in: (i) no statistically significant diameter differences for different targets and movements (Δ φ =0.3+/- 1.6 mm); (ii) reproducibility for heterogeneous and irregular targets independent of user initial interaction and (iii) good segmentation agreement for irregular targets compared to manual CT delineation in terms of Dice Similarity Coefficient (DSC  =  0.66+/- 0.04 ), Positive Predictive Value (PPV  =  0.81+/- 0.06 ) and Sensitivity (Sen.  =  0.49+/- 0.05 ). In clinical evaluation, the segmented volume was in reasonable agreement with the consensus volume (difference in volume (%Vol)  =  40+/- 30 , DSC  =  0.71+/- 0.07 and PPV  =  0.90+/- 0.13 ). High accuracy in target tracking position (Δ ME) was obtained for experimental and clinical data (Δ ME{{}\\text{exp}}=0+/- 3 mm; Δ ME{{}\\text{clin}}=0.3+/- 1.4 mm). In the comparison with other lung segmentation methods, 4D-COA has shown the highest volume accuracy in both experimental and clinical data. In conclusion, the accuracy in volume

  19. Initial Center Optimization of Tourism Customer Segmentation K-means Algorithm%旅游客户细分K-means算法的初始中心优化

    Institute of Scientific and Technical Information of China (English)

    王丹竹; 杨昌勇

    2016-01-01

    以标准K-means算法在旅游客户细分的应用中存在的聚类效果不佳等缺陷为着眼点,本文设计了一种以初始化中心优化K-means算法为基础的旅游客户细分模型,首先优化该算法中相似度的计算中的距离度量,之后再以K-means算法聚类效果对初始质心严重依赖和对数据输入顺序敏感等缺点为着眼点,提出寻找较为准确的K个聚类中心的方法。结果表明,通过改进K-means算法得到的客户划分,类别明确,类别之间的界限清晰,说明通过对客户的划分定义明确,划分效果较好。%According to the defects of the standard K-means algorithm such as poor clustering effect in tourism customer segmentation, a tourism customer segmentation model is designed based on optimized K-means algorithm by initializing the center. First, the distance metric in the calculation of the algorithm similarity is optimized, and then according to the defects of K-means algorithm clustering effect such as over relies on the initial centroid and sensitive to data input order, put forward to find a more accurate method of K clustering centers. Results show that the obtained customers’segmentation by improving the K-means algorithm has clear category, and clear boundaries between categories, and show through clearly defined the customers’segmentation, it is better divided.

  20. Microsurgical anatomy related to craniocervical junction segment of the vertebral artery in far lateral approach%寰枢段椎动脉在远外侧入路中的应用显微解剖研究

    Institute of Scientific and Technical Information of China (English)

    贾旺; 毕智勇; 鲁润春; 于春江

    2013-01-01

    Objective Microsurgical anatomy of craniocervical junction (CCJ) segment of the vertebral artery (VA) were studied to provide an applied anatomic basis for the far lateral approach.Methods Simulated operation of far lateral approach was performed on 10 cadaveric heads specimens and 10 dry skulls for measurment of the osseous relationships in the region.Results Craniocervical junction segment of the vertebral artery has five curvatures in most of the specimens,and compensatory vascular expansion in the curvatures was found.The average diameter is (4.3 ± 0.5) mm with changeful direction.The average half length of posterior arch of atlas is (19.3 ±4.7) mm,also the safe extent for exposing vertebral artery.Conclusions The key points to successfully preserve vertebral artery in far lateral approach are familiarity with the microanatomical relationship of craniocervical junction segment of the vertebral artery,especially the five curvatures.%目的 为颅颈交界区手术入路提供解剖学参数,帮助神经外科医生安全、准确地暴露手术靶区.方法 应用10%甲醛固定的汉族成人尸头标本10例20侧;漂白干颅骨及寰枢椎10例20侧.模拟手术入路逐层解剖,并对解剖结构进行精确测量和拍照.结果 寰枢段椎动脉在颅颈交界区形成比较恒定的五个生理弯曲,平均直径(4.3±0.5) mm,角度多变.寰椎后弓外侧半距(19.3±4.7)mm.结论 熟悉寰枢段椎动脉五个生理弯曲的定位方法,有助于提高颅颈交界区手术入路的安全性.

  1. Spinal angiography. Anatomy, technique and indications

    International Nuclear Information System (INIS)

    Spinal angiography is a diagnostic modality requiring detailed knowledge of spinal vascular anatomy. The cervical spinal cord is supplied by the vertebral arteries while segmental arteries which are preserved from fetal anatomy, supply the thoracic and lumbar regions. As spinal angiography carries the risk of paraplegia the indications have to be considered very carefully. Nevertheless, spinal angiography should be performed if there is reason to suspect a spinal vascular malformation from magnetic resonance imaging (MRI). (orig.)

  2. Normal Female Reproductive Anatomy

    Science.gov (United States)

    ... historical Searches are case-insensitive Reproductive System, Female, Anatomy Add to My Pictures View /Download : Small: 720x756 ... Large: 3000x3150 View Download Title: Reproductive System, Female, Anatomy Description: Anatomy of the female reproductive system; drawing ...

  3. Thymus Gland Anatomy

    Science.gov (United States)

    ... historical Searches are case-insensitive Thymus Gland, Adult, Anatomy Add to My Pictures View /Download : Small: 720x576 ... Large: 3000x2400 View Download Title: Thymus Gland, Adult, Anatomy Description: Anatomy of the thymus gland; drawing shows ...

  4. Normal Pancreas Anatomy

    Science.gov (United States)

    ... hyphen, e.g. -historical Searches are case-insensitive Pancreas Anatomy Add to My Pictures View /Download : Small: ... 1586x1534 View Download Large: 3172x3068 View Download Title: Pancreas Anatomy Description: Anatomy of the pancreas; drawing shows ...

  5. 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.

  6. A new method for image segmentation based on Fuzzy C-means algorithm on pixonal images formed by bilateral filtering

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan; Sharifzadeh, Sara

    2013-01-01

    segmentation could be avoided. Indeed, the bilateral filtering, as a preprocessing step, eliminates the unnecessary details of the image and results in a few numbers of pixons, faster performance and more robustness against unwanted environmental noises. Then, the obtained pixonal image is segmented using...

  7. Segmentation algorithm of muskmelon fruit with complex background%复杂背景下甜瓜果实分割算法

    Institute of Scientific and Technical Information of China (English)

    王玉德; 张学志

    2014-01-01

    为解决复杂背景下甜瓜果实与背景图像分割的问题,该文提出了一种融合颜色特征和纹理特征的图像分割算法。首先,把采集到的甜瓜果实图像从RGB色彩空间分别转换到CIELAB和HSV色彩空间,应用a*b*分量建立角度模型,根据甜瓜果实的颜色特点选取阈值并对图像作二值化处理;为降低光照分布不均匀对图像分割的影响,采用HSV空间的HS颜色分量对果实图像进行阈值分割。在以上2种色彩空间分割的基础上,融合角度模型分割和 HS 阈值分割的结果,得到基于颜色特征的分割结果。然后,再按照图像的纹理特征对图像进行分割处理,融合按照颜色特征和纹理特征的分割结果。最后,为解决分割结果中的分割误差和边缘毛刺问题,以颜色特征分割的果实区域为限定条件,对按照融合特征分割的果实区域进行约束性区域生长,得到最终的图像分割结果。为了对该文提出算法的分割效果进行检验,采用超绿阈值分割算法和归一化差异指数算法(NDI)对试验图像进行分割,3种算法的平均检出率分别为83.24%、43.12%、99.09%。对比3种分割算法的检出率和误检率,可以看出,该文提出的算法试验结果明显优于超绿阈值分割算法和归一化差异指数(NDI)分割算法。%In order to solve the problem of muskmelon fruit image segmentation under a complex background, an algorithm of image segmentation based on fusing color feature and texture feature was proposed in this paper. First, the collected muskmelon fruit images were transformed from RGB color space to CIELAB color space and HSV space respectively. According to the color characteristics of muskmelon fruit, the collected images were binarized using the threshold of angle model that was set up in using a*b*components in CIELAB color space. To reduce the influence of the uneven illumination distribution of

  8. 一种生物在体荧光成像的自适应分割算法%Adaptive Segmentation Algorithm of Bioluminescent Image

    Institute of Scientific and Technical Information of China (English)

    常志军; 杨鑫

    2011-01-01

    Bioluminescence imaging is regarded as an imaging modality with a high performance, low cost and good prospect in molecular imaging technique. This paper proposes a new adaptive segmentation algorithm, which is based on the characteristics and the application requirements of the bioluminescent images. The adaptive segmentation is realized by performing the normalized processing, connectivity operation and the interested regions distinguishing on bioluminescent images. Experimental results show that this algorithm can get better segmentation results in the ease of weak signal, low signal-to-noise ratio and multiple light sources, so it is a kind of effective segmentation algorithm of bioluminescent images.%生物在体荧光成像是新兴分子影像技术中性能高、费用低、前景好的一种成像模态.针对生物在体荧光图像的特点和应用需求,提出一种全新的自适应图像分割算法.通过对荧光图像的归一化处理、连通性操作、感兴趣区域区分实现自适应分割.实验结果表明,该算法能够在弱信号、低信噪比、多光源的情况下得到较理想的分割结果,是一种有效的荧光图像分割算法.

  9. Binarization of MRI with Intensity Inhomogeneity Using K-Means Clustering for Segmenting Hippocampus

    Directory of Open Access Journals (Sweden)

    T.Genish

    2013-03-01

    Full Text Available Medical image segmentation plays a crucial role in identifying the shape and structure of human anatomy.The most widely used image segmentation algorithms are edge-based and typically rely on the intensityinhomogeneity of the image at the edges, which often fail to provide accurate segmentation results. Thispaper proposes a boundary detection technique for segmenting the hippocampus (the subcortical structurein medial temporal lobe from MRI with intensity inhomogeneity without ruining its boundary andstructure. The image is pre-processed using a noise filter and morphology based operations. An optimalintensity threshold is then computed using K-means clustering technique. Our method has been validatedon human brain axial MRI and found to give satisfactory performance in the presence of intensityinhomogeneity. The proposed method works well even for weak edge. Our method can be used to detectboundary for accurate segmentation of hippocampus.

  10. Binarization of MRI with Intensity Inhomogeneity using K- Means Clustering for Segmenting Hippocampus

    Directory of Open Access Journals (Sweden)

    K. Somasundaram

    2013-02-01

    Full Text Available Medical image segmentation plays a crucial role in identifying the shape and structure of human anatomy. The most widely used image segmentation algorithms are edge-based and typically rely on the intensity inhomogeneity of the image at the edges, which often fail to provide accurate segmentation results. This paper proposes a boundary detection technique for segmenting the hippocampus (the subcortical structure in medial temporal lobe from MRI with intensity inhomogeneity without ruining its boundary and structure. The image is pre-processed using a noise filter and morphology based operations. An optimal intensity threshold is then computed using K-means clustering technique. Our method has been validated on human brain axial MRI and found to give satisfactory performance in the presence of intensity inhomogeneity. The proposed method works well even for weak edge. Our method can be used to detect boundary for accurate segmentation of hippocampus.

  11. Pituitary Adenoma Segmentation

    CERN Document Server

    Egger, Jan; Kuhnt, Daniela; Freisleben, Bernd; Nimsky, Christopher

    2011-01-01

    Sellar tumors are approximately 10-15% among all intracranial neoplasms. The most common sellar lesion is the pituitary adenoma. Manual segmentation is a time-consuming process that can be shortened by using adequate algorithms. In this contribution, we present a segmentation method for pituitary adenoma. The method is based on an algorithm we developed recently in previous work where the novel segmentation scheme was successfully used for segmentation of glioblastoma multiforme and provided an average Dice Similarity Coefficient (DSC) of 77%. This scheme is used for automatic adenoma segmentation. In our experimental evaluation, neurosurgeons with strong experiences in the treatment of pituitary adenoma performed manual slice-by-slice segmentation of 10 magnetic resonance imaging (MRI) cases. Afterwards, the segmentations were compared with the segmentation results of the proposed method via the DSC. The average DSC for all data sets was 77.49% +/- 4.52%. Compared with a manual segmentation that took, on the...

  12. Investigation of Exact Truncated Data Image Reconstruction Algorithm on Parallel PI-Line Segments in Fan-Beam Scans

    Institute of Scientific and Technical Information of China (English)

    LI Liang; CHEN Zhiqiang; KANG Kejun; ZHANG Li

    2007-01-01

    Some novel reconstruction algorithms have recently been proposed to solve the problem of reconstruction from transverse truncated projections of fan-beam scans. This paper introduced and reformulated the exact backprojection-filtration (BPF)-type reconstruction algorithm for fan-beam scans based on Zou and Pan's work. Subsequently, a legible and implementary BPF algorithm for region-of-interest (ROI)reconstruction is presented using projection data truncated not only in angle-scanning but also in the transverse direction. The algorithm can be widely used for fan-beam full-scans, short-scans, or super-short-scans.The algorithm uses less projection data than the preceding super-short-scan. The algorithm is implemented using the Shepp-Logan phantom and some primary results are presented. Some new discoveries and implications of ROI reconstruction from truncated data are discussed, which suggests that the BPF algorithm can be used in the ROI reconstruction from truncated projections.

  13. Lettuce image target clustering segmentation based on MFICSC algorithm%基于MFICSC 算法的生菜图像目标聚类分割

    Institute of Scientific and Technical Information of China (English)

    孙俊; 武小红; 张晓东; 王艳; 高洪燕

    2012-01-01

    生菜图像目标分割是基于图像处理的生菜生理信息无损检测的前提.为了解决因生菜富含水分使得图像采集镜头反光而导致生菜叶片图像灰度分布不均的问题,该文采用一种修正的图像灰度均衡算法对生菜图像进行灰度均衡处理,应用混合模糊类间分离聚类算法(MFICSC)进行生菜图像目标分割,使总体类间距离最大化,能够同时生成模糊隶属度和典型值,对处理噪声数据和克服一致性聚类问题均表现良好.分别采用MFICSC算法和Otsu算法进行了生菜图像目标分割对比试验,结果表明MFICSC算法具有较好的聚类准确度,效果优于传统Otsu分割算法.%Lettuce image target segmentation is the premise of the nondestructive detection of lettuce physiological information based on image processing. Because lettuce contains more water, the camera len is likely to occur reflex, leading to uneven gray distribution of lettuce leaf image. A modified image equalization algorithm is used to equalize the image gray. In this paper, the mixed fuzzy inter-cluster separation clustering(MFICSC) is applied in lettuce image target segmentation, which can make the distance between classes be maximum on the whole and can produce the fuzzy memberships and possibilities simultaneously. MFICSC can overcome the noise sensitivity and the coincident clusters problem. In the test, the MFICSC algorithm and Otsu algorithm were applied to lettuce image target segmentation respectively. The test results show that the MFICSC algorithm has better clustering accuracy, and its segmentation effect is superior to the one of traditional Otsu algorithm.

  14. 基于交点和区域特征的线段裁剪算法%A Segment Clipping Algorithm Based on the Intersection and Region Features

    Institute of Scientific and Technical Information of China (English)

    陈定钰; 丁有和

    2014-01-01

    Proposes a new algorithm of straight-line segment clipping against rectangular window based on the thought of Weiler-Atherton and Co-hen-Sutherland algorithm. In this algorithm, divides the rectangular window into three regions by the horizontal and vertical direction each other. To reserve the straight-line directionality, every line endpoint in a region code is assigned a different value of-1, 0 or 1, and it can easily determine the "whole out" situation by code operations. To reduce the number of intersection computed, it takes full advan-tage of the properties that the line segment has only "in" and "out" point and exist in pairs. As a result, the application proves that this algorithm has the strong stability and high clipping efficiency.%由Weiler-Atherton和Cohen-Sutherland算法思想,提出一种基于交点和区域特征的线段裁剪算法。算法将矩形窗口按水平方向和竖直方向各划分成三个区域,并从线段的有向性出发,根据起点和终点的不同给出-1、0和1的编码值,从而简化了“弃之”情况的判断。在求交中,为了避免直线段与裁剪边的多次求交,充分利用直线段“入点”和“出点”的唯一性和成对存在的性质,使得该算法具有较强的稳定性和较高的裁剪效率。

  15. 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

    analysis, IQS was improved in most segments (9/14). Conclusion: The SSF algorithm can provide acceptable diagnostic image quality in coronary CTA for patients with intermediate HR.

  16. 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

    International Nuclear Information System (INIS)

    analysis, IQS was improved in most segments (9/14). Conclusion: The SSF algorithm can provide acceptable diagnostic image quality in coronary CTA for patients with intermediate HR

  17. Algorithm for localized adaptive diffuse optical tomography and its application in bioluminescence tomography

    Science.gov (United States)

    Naser, Mohamed A.; Patterson, Michael S.; Wong, John W.

    2014-04-01

    A reconstruction algorithm for diffuse optical tomography based on diffusion theory and finite element method is described. The algorithm reconstructs the optical properties in a permissible domain or region-of-interest to reduce the number of unknowns. The algorithm can be used to reconstruct optical properties for a segmented object (where a CT-scan or MRI is available) or a non-segmented object. For the latter, an adaptive segmentation algorithm merges contiguous regions with similar optical properties thereby reducing the number of unknowns. In calculating the Jacobian matrix the algorithm uses an efficient direct method so the required time is comparable to that needed for a single forward calculation. The reconstructed optical properties using segmented, non-segmented, and adaptively segmented 3D mouse anatomy (MOBY) are used to perform bioluminescence tomography (BLT) for two simulated internal sources. The BLT results suggest that the accuracy of reconstruction of total source power obtained without the segmentation provided by an auxiliary imaging method such as x-ray CT is comparable to that obtained when using perfect segmentation.

  18. Algorithm for localized adaptive diffuse optical tomography and its application in bioluminescence tomography

    International Nuclear Information System (INIS)

    A reconstruction algorithm for diffuse optical tomography based on diffusion theory and finite element method is described. The algorithm reconstructs the optical properties in a permissible domain or region-of-interest to reduce the number of unknowns. The algorithm can be used to reconstruct optical properties for a segmented object (where a CT-scan or MRI is available) or a non-segmented object. For the latter, an adaptive segmentation algorithm merges contiguous regions with similar optical properties thereby reducing the number of unknowns. In calculating the Jacobian matrix the algorithm uses an efficient direct method so the required time is comparable to that needed for a single forward calculation. The reconstructed optical properties using segmented, non-segmented, and adaptively segmented 3D mouse anatomy (MOBY) are used to perform bioluminescence tomography (BLT) for two simulated internal sources. The BLT results suggest that the accuracy of reconstruction of total source power obtained without the segmentation provided by an auxiliary imaging method such as x-ray CT is comparable to that obtained when using perfect segmentation. (paper)

  19. Segmentation of Color Images Based on Different Segmentation Techniques

    OpenAIRE

    Purnashti Bhosale; Aniket Gokhale

    2013-01-01

    In this paper, we propose an Color image segmentation algorithm based on different segmentation techniques. We recognize the background objects such as the sky, ground, and trees etc based on the color and texture information using various methods of segmentation. The study of segmentation techniques by using different threshold methods such as global and local techniques and they are compared with one another so as to choose the best technique for threshold segmentation. Further segmentation...

  20. Thread Pool Size Adaptive Adjusting Algorithm Based on Segmentation%基于分段的线程池尺寸自适应调整算法

    Institute of Scientific and Technical Information of China (English)

    孙旭东; 韩江洪; 刘征宇; 解新胜

    2011-01-01

    提出一种基于分段的线程池尺寸自适应调整算法.该算法将用户请求量分为上升段、平衡段和下降段3段,根据当前用户请求数、线程数自适应调整线程池尺寸,从而满足用户需求.实验结果表明,相比基于平均数的调整算法,该算法能更好地处理并发的用户请求,响应时间更短.%This paper presents a thread pool size adaptive adjusting algorithm based on segmentation. User request quantity is divided into rising balancing and dropping section. This algorithm changes the size of the thread pool based on present request and thread in order to meet need of user requirement. Experimental results show that this algorithm can effectively process multiple concurrent requests, its response time is shorter compared with adjusting algorithm based average value.

  1. Anatomy of the Eye

    Science.gov (United States)

    ... Conditions Frequently Asked Questions Español Condiciones Chinese Conditions Anatomy of the Eye En Español Read in Chinese External (Extraocular) Anatomy Extraocular Muscles: There are six muscles that are ...

  2. Segmentation Algorithm for Oil Spill SAR Images Based on Hierarchical Agglomerative Clustering%基于HAC的溢油SAR图像分割算法

    Institute of Scientific and Technical Information of China (English)

    苏腾飞; 孟俊敏; 张晰

    2013-01-01

    图像分割是SAR溢油检测中的关键步骤,但由于SAR影像中存在斑点噪声,使得一般的图像分割算法难以收到理想的效果,严重影响溢油检测的精度.发展一种基于凝聚层次聚类(Hierarchical Agglomerative Clustering,HAC)的溢油SAR图像分割算法.该算法利用多尺度分割的思想,能够有效保持SAR影像中溢油斑块的形状特征,并能减少细碎斑块的产生.利用2010年墨西哥湾的Envisat ASAR影像开展了溢油SAR图像分割实验,并将该算法和Canny边缘检测、OTSU阈值分割、FCM分割、水平集分割等方法进行了对比.结果显示,HAC方法可以有效减少细碎斑块的产生,有助于提高SAR溢油检测的精度.%Image segmentation is a crucial stage in the SAR oil spill detection.However,the common image segmentation algorithms can hardly achieve satisfactory results due to speckle noise in the SAR images,thus affecting seriously the accuracy of oil spill detection.For this reason,an image segmentation algorithm which is based on HAC (Hierarchical Agglomerative Clustering) is developed for the oil spill SAR images.This method takes advantage of multi-resolution segmentation to maintain effectively the shape property of oil spill patches,and can reduce the formation of small patches.By using Envisat ASAR images of the Gulf of Mexico obtained in 2010,an experiment of SAR oil spill image segmentation has been conducted.Comparing with other approaches such as Canny,OTSU,FCM and Levelset,the results show that HAC can effectively reduce the producing of small patches,which is helpful to improve the accuracy of SAR oil spill detection.

  3. Automated condition-invariable neurite segmentation and synapse classification using textural analysis-based machine-learning algorithms

    OpenAIRE

    Kandaswamy, Umasankar; Rotman, Ziv; Watt, Dana; Schillebeeckx, Ian; Cavalli, Valeria; Klyachko, Vitaly

    2012-01-01

    High-resolution live-cell imaging studies of neuronal structure and function are characterized by large variability in image acquisition conditions due to background and sample variations as well as low signal-to-noise ratio. The lack of automated image analysis tools that can be generalized for varying image acquisition conditions represents one of the main challenges in the field of biomedical image analysis. Specifically, segmentation of the axonal/dendritic arborizations in brightfield or...

  4. GPU-based relative fuzzy connectedness image segmentation

    Energy Technology Data Exchange (ETDEWEB)

    Zhuge Ying; Ciesielski, Krzysztof C.; Udupa, Jayaram K.; Miller, Robert W. [Radiation Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892 (United States); Department of Mathematics, West Virginia University, Morgantown, West Virginia 26506 (United States) and Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 (United States); Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 (United States); Radiation Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892 (United States)

    2013-01-15

    Purpose:Recently, clinical radiological research and practice are becoming increasingly quantitative. Further, images continue to increase in size and volume. For quantitative radiology to become practical, it is crucial that image segmentation algorithms and their implementations are rapid and yield practical run time on very large data sets. The purpose of this paper is to present a parallel version of an algorithm that belongs to the family of fuzzy connectedness (FC) algorithms, to achieve an interactive speed for segmenting large medical image data sets. Methods: The most common FC segmentations, optimizing an Script-Small-L {sub {infinity}}-based energy, are known as relative fuzzy connectedness (RFC) and iterative relative fuzzy connectedness (IRFC). Both RFC and IRFC objects (of which IRFC contains RFC) can be found via linear time algorithms, linear with respect to the image size. The new algorithm, P-ORFC (for parallel optimal RFC), which is implemented by using NVIDIA's Compute Unified Device Architecture (CUDA) platform, considerably improves the computational speed of the above mentioned CPU based IRFC algorithm. Results: Experiments based on four data sets of small, medium, large, and super data size, achieved speedup factors of 32.8 Multiplication-Sign , 22.9 Multiplication-Sign , 20.9 Multiplication-Sign , and 17.5 Multiplication-Sign , correspondingly, on the NVIDIA Tesla C1060 platform. Although the output of P-ORFC need not precisely match that of IRFC output, it is very close to it and, as the authors prove, always lies between the RFC and IRFC objects. Conclusions: A parallel version of a top-of-the-line algorithm in the family of FC has been developed on the NVIDIA GPUs. An interactive speed of segmentation has been achieved, even for the largest medical image data set. Such GPU implementations may play a crucial role in automatic anatomy recognition in clinical radiology.

  5. ADAPTACIÓN DEL ALGORITMO MARACAS PARA SEGMENTACIÓN DE LA ARTERIA CARÓTIDA Y CUANTIFICACIÓN DE ESTENOSIS EN IMÁGENES TAC Adaptation of the MARACAS Algorithm for Carotid Artery Segmentation and Stenosis Quantification on CT Images

    Directory of Open Access Journals (Sweden)

    MARIA A ZULUAGA

    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 segmentations, and the mean stenosis quantification error was 14.4%.

  6. Application of Cuckoo Search Algorithm in Multi-threshold Image Segmentation%布谷鸟搜索算法在多阈值图像分割中的应用

    Institute of Scientific and Technical Information of China (English)

    柳新妮; 马苗

    2013-01-01

    穷举式搜索在寻找多个分割阈值时,计算较为复杂.为解决该问题,提出一种基于布谷鸟搜索算法的多阈值图像分割算法.以Otsu法设计适应度函数,利用布谷鸟搜索算法的并行寻优性能寻找待分割图像的最优阈值.实验结果表明,与细菌觅食算法和人工蜂群算法相比,该算法的寻优速度更快,找到的阈值质量更高.%Aiming at the problem of searching multiple thresholds by exhaustive search,a new image multi-threshold segmentation algorithm based on Cuckoo Search(CS) algorithm is proposed in this paper.This algorithm employs Otsu method as the fitness function,and uses the favorable parallel searching performance of CS algorithm to quickly and accurately find the optimal thresholds of the image to be segmented.Experimental results show that CS algorithm outforms Bacterial Foraging(BF) algorithm and Artificial Bee Colony(ABC)algorithm in terms of segmentation speed and segmentation thresholds.

  7. A Segmentation Algorithm of OCT Image for Macula Edema%一种眼底黄斑水肿OCT图像分割方法

    Institute of Scientific and Technical Information of China (English)

    杨平; 彭清; 刘维平; 杨新

    2011-01-01

    According to the characteristics of OCT images for macula edema, we studied a method for segmentation of the macula edema. Based on the Chan-Vese model, we proposed an improved level-set algorithm. With defining the integer-valued signed function directly, the curve could evolute outward or inward by changing the inside neighboring rid points and outside neighboring grid points into each other. We realized image segmentation which is much faster than the method of Chan-Vese model and smoothness regularization. We segmented 45 images and extracted the macula edema of each image. After achieving good segmentation results, we estimated the volume of the macular edema. The method provides quantitative analytic tools for clinical diagnosis and therapy.%基于眼底黄斑部相干光断层扫描(OCT)图像提出了分割黄斑水肿的方法.根据Chan-Vese模型,采用了一种改进的水平集算法,直接定义整数值的符号函数,曲线的外扩和内缩.通过内外轮廓线上点的相互转化实现,实现了快速分割和曲线平滑.本文用该方法对眼底黄斑水肿45张断层图像进行了分割,提取了黄斑水肿区域轮廓,取得了良好的分割效果,并估算了眼底黄斑水肿的体积,为临床诊断和治疗提供了定量分析的工具.

  8. Adaptive algorithm for printed Uighur character segmentation%印刷体维吾尔文字符切分自适应算法

    Institute of Scientific and Technical Information of China (English)

    张振东; 哈力旦·阿布都热依木; 赵永霄

    2014-01-01

    To research and develop the webcam taking and translating Uighur word system and to solve the difficulties of Uighur word letter segmentation in the system ,a new algorithm based on the adaptive threshold was proposed .Aiming at the features of the Uighur word pictures taken by the webcam ,the word was exacted accurately first .Then the main part of the word was used to make the projection histogram of pixels ,the threshold of segmentation was extracted automatically .The threshold was used in segmentation at last .Experiments verify the segmentation accuracy rate of this method reaches over 96% .At the same time ,it has better adaptability for different images ,and it can promote the study of Uighur word camera translation system .%为研究开发维吾尔文摄像头取词翻译系统,解决其中维吾尔文字单词图像切分难题,提出一种印刷体维吾尔文字符自适应切分算法。针对摄像头取词图像特点,准确提取目标单词;利用维吾尔文单词基线以上的主体部分做像素积分投影,从投影结果中自动提取切分阈值;利用该阈值完成字符切分,达到自适应的效果。经过实验验证,该方法切分正确率达到了96%以上,针对不同图像具有较好的适应性,对维吾尔文摄像头取词翻译系统的研究具有促进作用。

  9. Babel Tower, Paris and Brisbane: a tour around their influences on hepatic segmentation terminology.

    OpenAIRE

    Oscar Claudio Andriani

    2010-01-01

    Liver anatomy has always been the same. However, its interpretation has changed during time according to the development of imaging and surgery. Cantlie introduced a new concept on liver anatomy using the term ―lobe‖ in a different way. Segmental anatomy, introduced in the middle of the XXth Century has a cornerstone in Couinaud’s studies. The fact that anglosaxons followed Cantlie’s concept about right and left lobes even in segmental anatomy after the description by Goldsmith & Woodburne, w...

  10. Customer Segmentation Strategy Based on Hybrid Clustering Algorithm%基于混合聚类算法的客户细分策略研究

    Institute of Scientific and Technical Information of China (English)

    王虹; 孙红

    2016-01-01

    针对层次聚类法和K-means 聚类法的缺陷和不足, 提出将二者相结合的改进算法, 既解决了层次聚类法伸缩性差的问题, 又解决了 K-means聚类法对初始聚类中心敏感的问题. 通过对改进算法的计算复杂度分析并利用UCI数据库的测试数据对改进算法进行测试. 结果表明, 混合聚类算法使样本聚类的准确率提高到94%, 并有更高的执行效率和更好地实用性. 此外, 将此算法应用到汽车销售公司的客户细分管理中, 得出了差别化明显的客户细分类别, 表明此改进算法具有更强的客户细分能力以及客户行为特征的解释能力.%An improved algorithm is put forward to fuse the hierarchical clustering method and the K -means clustering method to solve both the poor scalability of the former and the sensitivity to the initial clustering center of the latter.The computing complexity analysis of the improved algorithm and the test data of UCI database testing re -sults show that the hybrid clustering algorithm increases the sample clustering accuracy to 94%with a higher efficien-cy and better practicability .In addition , this algorithm is applied to the car sales company in the management of customer segmentation , where the differential is obtained obviously of customer segmentation categories , showing that the improved algorithm has higher detection rate and stronger interpretation ability on customer behaviors .

  11. Algorithm of Web Hot Data Mining Based on Structured Segmentation%基于半结构化分割的Web热点数据挖掘算法

    Institute of Scientific and Technical Information of China (English)

    阮梦黎

    2015-01-01

    随着大数据信息技术的发展,数据在线监测和数据挖掘成为计算机信息领域研究的热点。通过对Web热点数据分割挖掘,提高信息热点追踪和Web数据分类能力。传统算法采用非结构化数据挖掘算法,无法有效对Web热点数据进行准确定位和分层挖掘。提出一种基于半结构化分割的Web热点数据挖掘算法。采用半结构化数据进行特征分割,基于优秀基因位进行差分进化,使寻优曲线不断趋于平缓,在多个节点上并行的运行比较脚本,采用半结构化分割,使得Web热点特征挖掘实现自适应寻优,得到Web热点数据的分配因子,提高了挖掘性能。仿真结果表明,该算法获得了良好的效率和精度,提高了Web热点数据挖掘的自适应寻优能力。%With the development of big data information technology, online monitoring data and data mining has become a hot research field of computer information. The segmentation of Web hot data mining, improve the classification ability of information focus and Web data. Using the traditional algorithm of unstructured data mining algorithms, it is not valid for Web hot data for accurate positioning and layered mining. The paper proposed a mining algorithm Web hot data structured based on segmentation, feature segmentation using semi structured data, excellent genes are based on differential evolution, make the optimization curve tends to be gentle, parallel on multiple nodes running script, through the code makes the un⁃structured data mapped to the data block, make the data stored in the database relational data model, to get the distribution factor Web hot data, improve the mining performance.The simulation results show that the high efficiency and accuracy, it improved adaptive Web hotspot of data mining optimization ability.

  12. Algorithm of Web Hot Data Mining Based on Structured Segmentation%基于半结构化分割的Web热点数据挖掘算法

    Institute of Scientific and Technical Information of China (English)

    阮梦黎

    2015-01-01

    With the development of big data information technology, online monitoring data and data mining has become a hot research field of computer information. The segmentation of Web hot data mining, improve the classification ability of information focus and Web data. Using the traditional algorithm of unstructured data mining algorithms, it is not valid for Web hot data for accurate positioning and layered mining. The paper proposed a mining algorithm Web hot data structured based on segmentation, feature segmentation using semi structured data, excellent genes are based on differential evolution, make the optimization curve tends to be gentle, parallel on multiple nodes running script, through the code makes the un⁃structured data mapped to the data block, make the data stored in the database relational data model, to get the distribution factor Web hot data, improve the mining performance.The simulation results show that the high efficiency and accuracy, it improved adaptive Web hotspot of data mining optimization ability.%随着大数据信息技术的发展,数据在线监测和数据挖掘成为计算机信息领域研究的热点。通过对Web热点数据分割挖掘,提高信息热点追踪和Web数据分类能力。传统算法采用非结构化数据挖掘算法,无法有效对Web热点数据进行准确定位和分层挖掘。提出一种基于半结构化分割的Web热点数据挖掘算法。采用半结构化数据进行特征分割,基于优秀基因位进行差分进化,使寻优曲线不断趋于平缓,在多个节点上并行的运行比较脚本,采用半结构化分割,使得Web热点特征挖掘实现自适应寻优,得到Web热点数据的分配因子,提高了挖掘性能。仿真结果表明,该算法获得了良好的效率和精度,提高了Web热点数据挖掘的自适应寻优能力。

  13. Segmentation of the whole breast from low-dose chest CT images

    Science.gov (United States)

    Liu, Shuang; Salvatore, Mary; Yankelevitz, David F.; Henschke, Claudia I.; Reeves, Anthony P.

    2015-03-01

    The segmentation of whole breast serves as the first step towards automated breast lesion detection. It is also necessary for automatically assessing the breast density, which is considered to be an important risk factor for breast cancer. In this paper we present a fully automated algorithm to segment the whole breast in low-dose chest CT images (LDCT), which has been recommended as an annual lung cancer screening test. The automated whole breast segmentation and potential breast density readings as well as lesion detection in LDCT will provide useful information for women who have received LDCT screening, especially the ones who have not undergone mammographic screening, by providing them additional risk indicators for breast cancer with no additional radiation exposure. The two main challenges to be addressed are significant range of variations in terms of the shape and location of the breast in LDCT and the separation of pectoral muscles from the glandular tissues. The presented algorithm achieves robust whole breast segmentation using an anatomy directed rule-based method. The evaluation is performed on 20 LDCT scans by comparing the segmentation with ground truth manually annotated by a radiologist on one axial slice and two sagittal slices for each scan. The resulting average Dice coefficient is 0.880 with a standard deviation of 0.058, demonstrating that the automated segmentation algorithm achieves results consistent with manual annotations of a radiologist.

  14. A Survey of Semantic Segmentation

    OpenAIRE

    Thoma, Martin

    2016-01-01

    This survey gives an overview over different techniques used for pixel-level semantic segmentation. Metrics and datasets for the evaluation of segmentation algorithms and traditional approaches for segmentation such as unsupervised methods, Decision Forests and SVMs are described and pointers to the relevant papers are given. Recently published approaches with convolutional neural networks are mentioned and typical problematic situations for segmentation algorithms are examined. A taxonomy of...

  15. An Information Hiding Algorithm Based on Double Text Segments%基于双文本段的信息隐藏算法

    Institute of Scientific and Technical Information of China (English)

    陈志立; 黄刘生; 余振山; 杨威; 陈国良

    2009-01-01

    信息隐藏是一种在传输或存储过程中将隐秘信息隐藏在特定载体中,以保证隐秘信息安全性的技术.常用的载体有图像、音频、视频、文本等类型文档.由于文本文档特别是纯文本文档中的冗余信息非常少,基于纯文本文档的信息隐藏具有很大的挑战性.现存的基于纯文本文档的算法都是基于单文本段的,在安全性方面还存在许多难以克服的缺陷.该文提出了一种新的基于双文本段的信息隐藏算法,通过在多种隐藏形式中选择适当的隐藏形式和信息分散存储,大大地提高信息隐藏的隐蔽性、安全性.另外,算法具有很高的灵活度,可以根据具体的应用情景进行适当的变形或调整,以便更好地适用于实际需求.%Information hiding is a technique that hides secret messages in some carrier during transmission or storage. Carriers in common use include image, audio, video, text documents and so on. Since there is little redundancy in text documents, particularly in plain text documents, information hiding based on plain text documents is much more challenging. Previous algorithms based on plain text documents are all based on a single plain text segment. Therefore, there are many inherent limitations in security of them. In this paper, a novel information hiding algorithm based on double text segments is proposed. The algorithm can enhance the concealment and security of information hiding greatly by choosing a proper hiding form out of many ones and scattering information to places. In addition, the algorithm is so flexible that it can be modified or adjusted according to the certain application scene to fit the practical requirements better.

  16. Segmentation algorithm of medical images based on improved Self-Organizing Feature Maps network%改进自组织特征网络的医学图像分割算法

    Institute of Scientific and Technical Information of China (English)

    黄建灯

    2015-01-01

    为了提高医学图像分割精度,提出一种改进自组织特征网络的医学图像分割算法。首先采用小波包分解提取医学图像的特征,然后改进自组织特征网络建立医学图像分类器,实现医学图像分割,最后采用仿真实验测试算法的性能。仿真结果表明,本文算法不仅解决了传统医学图像分割算法存在的缺陷,提高医学图像分割的精度,具有较好的实际应用价值。%In order to improve the segmentation accuracy of medical image segmentation algorithm, a medical im-age segmentation algorithm is proposed based on improved self organizing feature mapping network for medical image. Firstly, wavelet packet decomposition is used to extract features of medical images, and then the improved self organi-zing feature network algorithm is used to establish medical image classifier to segment medical image, finally the simu-lation experiment is carried out to test the performance of algorithm. The simulation results show that the proposed algo-rithm not only solves the defects existing in traditional segmentation algorithms for medical image, improve the segmen-tation accuracy of medical image, and has good practical value.

  17. Computerized segmentation algorithm with personalized atlases of murine MRIs in a SV40 large T-antigen mouse mammary cancer model

    Science.gov (United States)

    Sibley, Adam R.; Markiewicz, Erica; Mustafi, Devkumar; Fan, Xiaobing; Conzen, Suzanne; Karczmar, Greg; Giger, Maryellen L.

    2016-03-01

    Quantities of MRI data, much larger than can be objectively and efficiently analyzed manually, are routinely generated in preclinical research. We aim to develop an automated image segmentation and registration pipeline to aid in analysis of image data from our high-throughput 9.4 Tesla small animal MRI imaging center. T2-weighted, fat-suppressed MRIs were acquired over 4 life-cycle time-points [up to 12 to 18 weeks] of twelve C3(1) SV40 Large T-antigen mice for a total of 46 T2-weighted MRI volumes; each with a matrix size of 192 x 256, 62 slices, in plane resolution 0.1 mm, and slice thickness 0.5 mm. These image sets were acquired with the goal of tracking and quantifying progression of mammary intraepithelial neoplasia (MIN) to invasive cancer in mice, believed to be similar to ductal carcinoma in situ (DCIS) in humans. Our segmentation algorithm takes 2D seed-points drawn by the user at the center of the 4 co-registered volumes associated with each mouse. The level set then evolves in 3D from these 2D seeds. The contour evolution incorporates texture information, edge information, and a statistical shape model in a two-step process. Volumetric DICE coefficients comparing the automatic with manual segmentations were computed and ranged between 0.75 and 0.58 for averages over the 4 life-cycle time points of the mice. Incorporation of these personalized atlases with intra and inter mouse registration is expected to enable locally and globally tracking of the morphological and textural changes in the mammary tissue and associated lesions of these mice.

  18. Multi-atlas segmentation for abdominal organs with Gaussian mixture models

    Science.gov (United States)

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

    2015-03-01

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

  19. 基于Mean Shift和随机游走的图像分割算法%Image Segmentation Algorithm Based on Mean Shift and Random Walk

    Institute of Scientific and Technical Information of China (English)

    穆克; 程伟; 褚俊霞

    2012-01-01

    An improved random walk algorithm was proposed herein.First,Mean Shift algorithm was adopted to preprocess the image,which was partitioned into a series of homogeneous areas,so that the homogeneous areas were taken as nodes to walk at random,with noise inhibited while reducing the number of nodes.Second,PMD was used to define the weight between regions.Thirdly,seeds were improved to have added the auxiliary seeds,and the auxiliary and signed seeds were used to walk random,with region merging realized.The final image segmentation was reached.Experimental results expatiates that the proposed method highlights the segmentation accuracy.%提出了一种改进的随机游走算法。首先,采用Mean Shift算法对图像进行预处理,将图像划分成一些同质区域,用同质区域作为节点进行随机游走,在降低节点数的同时也抑制了噪声对分割的影响;其次,利用马氏距离定义区域之间的权值;对种子点进行了改进,增加了辅助种子点,利用辅助种子点和用户标记的种子点进行随机游走,实现同质区域的合并,实现图像的最终分割。实验结果表明,该算法提高了图像分割的精度。

  20. AN ANTI-COLLISION ALGORITHM FOR RFID TAGS USING SEGMENTED EXTRACTION%一种分段抽取RFID标签防碰撞算法

    Institute of Scientific and Technical Information of China (English)

    王明斐; 于琨

    2014-01-01

    RFID technology gains attention from various industries,because it has low implementation cost and can effectively simplify the identification process of goods.RFID needs to rapidly and accurately obtain tag information from a great deal of tags.Limited by the scanning time cost and tags cost,the collision of multiple tag information cannot be avoid in scanning process.Deterministic anti-collision algorithms represented by tree-based query series algorithm are widely used due to high reliability.However,these algorithms have long tag recognition time and also have a large amount of traffic for information exchange.An anti-collision algorithm with segmented extraction is proposed in this paper.Theoretical analysis and simulation show that the proposed algorithm has a lower tag recognition time and a fewer total traffic compared with existing typical deterministic algorithms.%无线识别技术由于实现成本较低且能够有效简化货物的识别过程而受到各行业的关注。无线识别技术需要从大量的标签中迅速、准确地获取标签信息。由于扫描时间成本和标签成本的限制,无法避免扫描过程中多个标签信息碰撞的发生。以基于树的查询系列算法为代表的确定性防碰撞算法因可靠性高而获得大量应用。但是,这些算法的标签识别时间较长同时识别的总通信量较大。提出一种分段抽取的防碰撞算法。理论分析与仿真表明,该算法与已有典型确定性算法相比,具有更低的标签识别时间和更少的总通信量。

  1. Improving the robustness of interventional 4D ultrasound segmentation through the use of personalized prior shape models

    Science.gov (United States)

    Barbosa, Daniel; Queirós, Sandro; Morais, Pedro; Baptista, Maria J.; Monaghan, Mark; Rodrigues, Nuno F.; D'hooge, Jan; Vilaça, João. L.

    2015-03-01

    While fluoroscopy is still the most widely used imaging modality to guide cardiac interventions, the fusion of pre-operative Magnetic Resonance Imaging (MRI) with real-time intra-operative ultrasound (US) is rapidly gaining clinical acceptance as a viable, radiation-free alternative. In order to improve the detection of the left ventricular (LV) surface in 4D ultrasound, we propose to take advantage of the pre-operative MRI scans to extract a realistic geometrical model representing the patients cardiac anatomy. This could serve as prior information in the interventional setting, allowing to increase the accuracy of the anatomy extraction step in US data. We have made use of a real-time 3D segmentation framework used in the recent past to solve the LV segmentation problem in MR and US data independently and we take advantage of this common link to introduce the prior information as a soft penalty term in the ultrasound segmentation algorithm. We tested the proposed algorithm in a clinical dataset of 38 patients undergoing both MR and US scans. The introduction of the personalized shape prior improves the accuracy and robustness of the LV segmentation, as supported by the error reduction when compared to core lab manual segmentation of the same US sequences.

  2. Color image segmentation based on normalized cut and fish swarm optimization algorithm%基于鱼群算法优化normalized cut的彩色图像分割方法

    Institute of Scientific and Technical Information of China (English)

    周逊; 郭敏; 马苗

    2013-01-01

    为了克服传统的谱聚类算法求解normalized cut彩色图像分割时,分割效果差、算法复杂度高的缺点,提出了一种基于鱼群算法优化normalized cut的彩色图像分割方法.先对图像进行模糊C-均值聚类预处理,然后用鱼群优化算法替代谱聚类算法求解Ncut的最小值,最后通过最优个体鱼得到分割结果.实验表明,该方法耗时少,且分割效果好.%Traditional spectral clustering algorithm minimizing normalized cut criterion has an inaccurate result and a high algorithm complexity in color image segmentation. In order to improve these disadvantages, this paper proposed a color image segmentation method based on normalized cut and fish swarm optimization algorithm. It firstly used fuzzy C-means dealing with color image, then employed fish swarm optimization algorithm instead of spectral clustering algorithm to minimize normalized cut, finally got segmentation result by the optimal individual fish. Experimental results show that the method achieves consumes less time, and achieves a precise segmentation result.

  3. AnatomiQuiz

    DEFF Research Database (Denmark)

    Brent, Mikkel Bo; Kristoffersen, Thomas

    2015-01-01

    AnatomiQuiz er en quiz-app udviklet til bevægeapparatets anatomi. Den består af mere end 2300 spørgsmål og over 1000 anatomiske billeder. Alle spørgsmål tager udgangspunkt i lærebogen Bevægeapparatets anatomi af Finn Bojsen-Møller m.fl.......AnatomiQuiz er en quiz-app udviklet til bevægeapparatets anatomi. Den består af mere end 2300 spørgsmål og over 1000 anatomiske billeder. Alle spørgsmål tager udgangspunkt i lærebogen Bevægeapparatets anatomi af Finn Bojsen-Møller m.fl....

  4. Application of SVM Algorithm for Particle Swarm Optimization in Apple Image Segmentation%基于粒子群优化SVM的苹果图像分割

    Institute of Scientific and Technical Information of China (English)

    黄奇瑞

    2015-01-01

    苹果图像分割是苹果采摘机器人视觉系统中识别和定位的关键技术。针对目前苹果采摘机器人对果实识别误差大、处理时间长等问题,结合粒子群算法在求解组合优化问题时具有的全局搜索特性,提出了一种基于粒子群参数优化的 SVM 分割算法。试验结果表明:该算法能很好地实现苹果果实与图像背景的分离,后续利用数学形态学中的闭运算对分割后的图像进行处理,能够较好地保存苹果轮廓信息、消除孔洞现象,为完善苹果采摘机器视觉系统的识别和定位提供技术支持。%The apple image segmentation is the key technology of identification and location in the apple-picking machine vision system. On account of huge errors in the process of discriminating fruits by apple-picking robots at present and the long-time processing, the SVM theory in fingerprint image segmentation method is conducted. Combined with the global search ability of particle swarm optimization in solving combinational optimization problems, the SVM partitioning algorithm, which is based on the parameter optimization of particle swarm, is put forward. The results show that this algorithm makes the separation of apple fruits and the image background come true. It also preserves the outline of apples, then polishes the image after segmentation by the close operation in mathematical morphology, which eliminates the pore phenomenon effectively and provides convenience for the further apple-picking and apple-discriminating.

  5. Computer-aided measurement of liver volumes in CT by means of geodesic active contour segmentation coupled with level-set algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Suzuki, Kenji; Kohlbrenner, Ryan; Epstein, Mark L.; Obajuluwa, Ademola M.; Xu Jianwu; Hori, Masatoshi [Department of Radiology, University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637 (United States)

    2010-05-15

    Purpose: Computerized liver extraction from hepatic CT images is challenging because the liver often abuts other organs of a similar density. The purpose of this study was to develop a computer-aided measurement of liver volumes in hepatic CT. Methods: The authors developed a computerized liver extraction scheme based on geodesic active contour segmentation coupled with level-set contour evolution. First, an anisotropic diffusion filter was applied to portal-venous-phase CT images for noise reduction while preserving the liver structure, followed by a scale-specific gradient magnitude filter to enhance the liver boundaries. Then, a nonlinear grayscale converter enhanced the contrast of the liver parenchyma. By using the liver-parenchyma-enhanced image as a speed function, a fast-marching level-set algorithm generated an initial contour that roughly estimated the liver shape. A geodesic active contour segmentation algorithm coupled with level-set contour evolution refined the initial contour to define the liver boundaries more precisely. The liver volume was then calculated using these refined boundaries. Hepatic CT scans of 15 prospective liver donors were obtained under a liver transplant protocol with a multidetector CT system. The liver volumes extracted by the computerized scheme were compared to those traced manually by a radiologist, used as ''gold standard.''Results: The mean liver volume obtained with our scheme was 1504 cc, whereas the mean gold standard manual volume was 1457 cc, resulting in a mean absolute difference of 105 cc (7.2%). The computer-estimated liver volumetrics agreed excellently with the gold-standard manual volumetrics (intraclass correlation coefficient was 0.95) with no statistically significant difference (F=0.77; p(F{<=}f)=0.32). The average accuracy, sensitivity, specificity, and percent volume error were 98.4%, 91.1%, 99.1%, and 7.2%, respectively. Computerized CT liver volumetry would require substantially less

  6. Robust optic nerve segmentation on clinically acquired CT

    Science.gov (United States)

    Panda, Swetasudha; Asman, Andrew J.; DeLisi, Michael P.; Mawn, Louise A.; Galloway, Robert L.; Landman, Bennett A.

    2014-03-01

    The optic nerve is a sensitive central nervous system structure, which plays a critical role in many devastating pathological conditions. Several methods have been proposed in recent years to segment the optic nerve automatically, but progress toward full automation has been limited. Multi-atlas methods have been successful for brain segmentation, but their application to smaller anatomies remains relatively unexplored. Herein we evaluate a framework for robust and fully automated segmentation of the optic nerves, eye globes and muscles. We employ a robust registration procedure for accurate registrations, variable voxel resolution and image fieldof- view. We demonstrate the efficacy of an optimal combination of SyN registration and a recently proposed label fusion algorithm (Non-local Spatial STAPLE) that accounts for small-scale errors in registration correspondence. On a dataset containing 30 highly varying computed tomography (CT) images of the human brain, the optimal registration and label fusion pipeline resulted in a median Dice similarity coefficient of 0.77, symmetric mean surface distance error of 0.55 mm, symmetric Hausdorff distance error of 3.33 mm for the optic nerves. Simultaneously, we demonstrate the robustness of the optimal algorithm by segmenting the optic nerve structure in 316 CT scans obtained from 182 subjects from a thyroid eye disease (TED) patient population.

  7. Anatomy of the lymphatics.

    Science.gov (United States)

    Skandalakis, John E; Skandalakis, Lee J; Skandalakis, Panagiotis N

    2007-01-01

    The lymphatic system is perhaps the most complicated system of Homo sapiens. An introduction to the anatomy, embryology, and anomalies of the lymphatics is presented. The overall anatomy and drainage of the lymphatic vessels in outlined. The topographic anatomy, relations, and variations of the principle vessels of the lymphatic system (the right lymphatic duct, the thoracic duct, and the cisterna chyli) are presented in detail.

  8. Application of Kernel DBSCAN Algorithm in Civil Aviation Customer Segmentation%核DBSCAN算法在民航客户细分中的应用

    Institute of Scientific and Technical Information of China (English)

    潘玲玲; 张育平; 徐涛

    2012-01-01

    This paper proposes a kernel-based DBSCAN algorithm which is aiming at the complexity of the civil aviation passenger behavior. The algorithm uses the DBSCAN clustering technology, combines with the nuclear mapping mechanism, and realizes civil aviation customer segmentation. Experimental results show that the method can highlight the differences between samples, and also can reduce the confusion of the clustering results and the cluster purity is improved by nearly 30%.%针对民航客户行为数据的复杂性,运用数据挖掘中的DBSCAN聚类技术,结合核映射机理,提出一种基于核的DBSCAN算法,用于实现民航客户的细分.实验结果表明,该方法能突出客户之间的行为特征差异,降低聚类结果的混乱性,且其聚类纯度比原DBSCAN算法约提升30%.

  9. FUZZY CLUSTERING ALGORITHMS FOR WEB PAGES AND CUSTOMER SEGMENTS%Web页面和客户群体的模糊聚类算法

    Institute of Scientific and Technical Information of China (English)

    宋擒豹; 沈钧毅

    2001-01-01

    Web log mining is broadly used in E-commerce and personalizationof the Web. In this paper, the fuzzy clustering algorithms for Web pages and customers is presented. First, the fuzzy sets of Web page and customer are setup separately according to the hitting information of customers. Second, the fuzzy similarity matrices ave constructed on the basis of the fuzzy sets and the Max-Min similarity measure scheme. Finally, Web page clusters and tustomer segments are abstracted directly from the corresponding fuzzy similarity matrix. Experiments show the effectiveness of the algorithm.%web日志挖掘在电子商务和个性化web等方面有着广泛的应用.文章介绍了一种web页面和客户群体的模糊聚类算法.在该算法中,首先根据客户对Web站点的浏览情况分别建立Web页面和客户的模糊集,在此基础上根据Max—Min模糊相似性度量规则构造相应的模糊相似矩阵,然后根据模糊相似矩阵直接进行聚类.实验结果表明该算法是有效的.

  10. A segmentation algorithm of cerebral cortex based on dual edge detections and regional growing%基于双重边缘检测和区域生长的大脑皮层分割算法

    Institute of Scientific and Technical Information of China (English)

    刘宁; 罗洪艳; 谭立文; 李敏; 文丽丽

    2012-01-01

    目的 设计一种数字人脑切片图像自动分割算法,以实现对大脑皮层的准确分割.方法 采用RGB空间彩色边缘检测与Canny算子边缘检测,联合种子点自动选择的区域生长算法,提取并分割大脑皮层,并与手工分割结果进行对比分析.结果 自动分割的大脑皮层边缘完整、清晰、平滑,与手工分割结果的吻合度较高.结论采用该方法可较为准确地分割数字人脑切片图像中的大脑皮层.%Objective To design a automatic segmentation algorithm for digital cross-section slice images of human brain, in order to segment the cerebral cortex accurately. Methods Cerebral cortex was obtained and extracted from gray matter using RGB space edge detection, Canny operator detection and regional growing algorithm. A comparative analysis between the segmentation results of automatic algorithm and manual method was performed. Results Highly coincident to that segmented by manual method, cerebral cortex segmented by automatic algorithm was characterized by complete, clear and smooth edge. Conclusion This algorithm is suitable for the segmentation of cerebral cortex in digital cross-section slice images.

  11. FPGA Implementation of Gaussian Mixture Model Algorithm for 47 fps Segmentation of 1080p Video

    Directory of Open Access Journals (Sweden)

    Mariangela Genovese

    2013-01-01

    Full Text Available Circuits and systems able to process high quality video in real time are fundamental in nowadays imaging systems. The circuit proposed in the paper, aimed at the robust identification of the background in video streams, implements the improved formulation of the Gaussian Mixture Model (GMM algorithm that is included in the OpenCV library. An innovative, hardware oriented, formulation of the GMM equations, the use of truncated binary multipliers, and ROM compression techniques allow reduced hardware complexity and increased processing capability. The proposed circuit has been designed having commercial FPGA devices as target and provides speed and logic resources occupation that overcome previously proposed implementations. The circuit, when implemented on Virtex6 or StratixIV, processes more than 45 frame per second in 1080p format and uses few percent of FPGA logic resources.

  12. 基于混合单纯形算法的模糊均值图像分割%Fuzzy Means Image Segmentation Based on Hybridized Nelder-Mead Simplex Algorithm

    Institute of Scientific and Technical Information of China (English)

    李艳灵; 刘婷

    2012-01-01

    针对模糊C均值算法用于图像分割时对初始值敏感、容易陷入局部极值的问题,提出基于混合单纯形算法的模糊均值图像分割算法.算法利用Nelder-Mead单纯形算法计算量小、搜索速度快和粒子群算法自适应能力强、具有较好的全局搜索能力的特点,将混合单纯形算法的结果作为模糊C均值算法的输入,并将其用于图像分割.实验结果表明:基于混合单纯形算法的模糊均值图像分割算法在改善图像分割质量的同时,提高了算法的运行速度.%Standard fuzzy C-means algorithm is sensitive to initial data, and gets in the local optimization easily. For this reason, fuzzy means image segmentation based on hybridized Nelder-Mead simplex algorithm is proposed in this paper. Nelder-Mead simplex algorithm has the virtues of rapid searching and less calculation. The virtues of particle swarm operation algorithm is strong adaptability and better global search capability. In the new algorithm, the virtues of Nelder-Mead simplex algorithm and particle swarm operation algorithm are used and the result of hybridized Nelder-Mead simplex algorithm is regarded as the input of fuzzy C-means algorithm for image segmentation. Experimental results show that new algorithm not only has higher convergence speed, but also can achieve more robust segmentation results.

  13. 基于改进K-means算法的RFAT客户细分研究%RFAT customer segmentation based on improved K-means algorithm

    Institute of Scientific and Technical Information of China (English)

    刘芝怡; 陈功

    2014-01-01

    The traditional K-means algorithm has sensitivity to the initial cluster centers,meanwhile it is difficult for users to determine the optimal number of clusters in advance. In order to solve these problems,a new improved K-means algorithm is proposed here. The algorithm can optimize the initial center points through computing the maximum distance of objects. At the same time,it can find the optimal number of clusters by using a new evaluation function. The results can reduce the dependence on the parameters. When the improved algorithm is used to analyze customers of a firm, the RFAT customer classification model is proposed. The new model has four segmentation variables to assess the customer’s value:Recency, Frequency, Average Monetary and Trend. The customers RFAT-value is analyzed by using clustering. The business strategy for different customer groups is also pointed out. The application results show that the RFAT model and the improved K-means algorithm proposed here can classify customers effectively. It also can fully reflect the customer’s current value and appreciation potential.%为了解决传统K-means算法对初始聚类中心敏感和聚类数目事先难以确定的问题,提出了一种改进的K-means算法。改进算法利用最大距离等分策略来选取初始聚类中心,并利用一种评价函数来自动确定聚类数,减少了算法结果对参数的依赖。将改进算法应用到某企业客户分类中时,为提高分类结果的表征性,提出了以客户最近购买时间( Recency )、购买频次(Frequency)、平均购买额(Average Monetary)和购买倾向(Trend)作为客户价值细分变量的RFAT( Recency,frequency,average monetary and trend)模型,对客户RFAT值进行了聚类分析,并提供了针对不同客户群的营销策略。实证研究表明,该文所提出的改进算法和模型可以有效地对企业客户进行分类,能充分反映客户的当前价值和增值潜能。

  14. 基于小波变换和改进的FCM算法的医学 CT图像分割法%Medical CT Image Segmentation Based on Wavelet Transform and Improved FCM Algorithm

    Institute of Scientific and Technical Information of China (English)

    马春

    2016-01-01

    为提高计算机辅助诊断的准确性,提出一种基于小波变换和改进的模糊C均值( Fuzzy C-Means, FCM)算法的医学CT图像分割方法。以FCM算法为基础,首先利用小波变换对医学图像进行分解,用分解后低频图像的像素点作为FCM算法的样本点;其次,利用马氏距离来进一步修正 FCM_S( FCM_Spatial)算法,修正后的 FCM 算法能更加精确地反映医学图像的信息。实验结果表明,算法的效率得到较大提高。%In order to enhance the accuracy of computer auxiliary diagnosis, a medical CT image segmentation algorithm based on wavelet transform and improved FCM algorithm is proposed .Because the traditional FCM algorithm usually run on all im-age pixels, which makes the efficiency of the algorithm reduced.On the basis of FCM algorithm, firstly this algorithm processes the image using wavelet transform, and the low frequency images by wavelet transform are inputted into FCM algorithm to obtain seg-mentation results.It not only greatly reduces the time complexity of the algorithm but also effectively suppresses image noise .Sec-ondly, the algorithm introduces the Mahalanobis distance to improve FCM_S algorithm, and the improved FCM algorithm can be more accurate to obtain medical image information .The experiments show that this algorithm significantly improves the segmenta-tion’s efficiency.

  15. A Novel Method for the Detection of Microcalcifications Based on Multi-scale Morphological Gradient Watershed Segmentation Algorithm

    Directory of Open Access Journals (Sweden)

    S. Vijaya Kumar

    2010-07-01

    Full Text Available This paper presents an automated system for detecting masses in mammogram images. Breast cancer is one of the leading causes of women mortality in the world. Since the causes are unknown, breast cancer cannot be prevented. It is difficult for radiologists to provide both accurate and uniform evaluation over the enormous number of ammograms generated in widespread screening. Microcalcifications (calcium deposits and masses are the earliest signs of breast carcinomas and their detection is one of the key issues for breast cancer control. Computer-aided detection of Microcalcifications and masses is an important and challenging task in breast cancer control. This paper presents a novel approach for detecting microcalcification clusters. First digitized mammogram has been taken from Mammography Image Analysis Society (MIAS database. The Mammogram is preprocessed using Adaptive median filtered. Next, the microcalcification clusters are identified by using the marker extractions of the gradient images obtained by multiscale morphological reconstruction and avoids Oversegmentation vivid in Watershed algorithm. Experimental result show that the microcalcification can be accurately and efficiently detected using the proposed approach.

  16. Anatomy: Spotlight on Africa

    Science.gov (United States)

    Kramer, Beverley; Pather, Nalini; Ihunwo, Amadi O.

    2008-01-01

    Anatomy departments across Africa were surveyed regarding the type of curriculum and method of delivery of their medical courses. While the response rate was low, African anatomy departments appear to be in line with the rest of the world in that many have introduced problem based learning, have hours that are within the range of western medical…

  17. Anatomy Comic Strips

    Science.gov (United States)

    Park, Jin Seo; Kim, Dae Hyun; Chung, Min Suk

    2011-01-01

    Comics are powerful visual messages that convey immediate visceral meaning in ways that conventional texts often cannot. This article's authors created comic strips to teach anatomy more interestingly and effectively. Four-frame comic strips were conceptualized from a set of anatomy-related humorous stories gathered from the authors' collective…

  18. Side scan sonar imagery segmentation algorithm by BEMD-improved multilayer level set model%BEMD-分层水平集侧扫声纳图像快速分割算法

    Institute of Scientific and Technical Information of China (English)

    叶秀芬; 王雷; 王天

    2012-01-01

    针对侧扫声纳图像不同区域的像素分布特点,提出了一种改进的BEMD(二维经验模态分解)-分层水平集分割算法.介绍了CV(Chan和Vese)水平集模型和分层水平集模型,利用分层水平集模型进行三类分割.为了提高分割精度,利用BEMD重新描述模型的能量函数.通过BEMD的加权参数,在不影响分割精度的前提下提高模型的抗噪性能.分析了c-均值算法与水平集算法的联系,利用改进的c-均值算法初始化水平集演化曲线,以减少迭代次数.对水平集能量函数添加惩罚项,以提高水平集演化速度.利用改进的BEMD-分层水平集分割算法进行无监督的图像分割实验并与其他算法比较,验证了该算法的抗噪性、分割的准确性和快速性.%Characteristics of different regions in side scan sonar imagery are analyzed. A kind of improved BE-MD-multilayer level set segmentation algorithm is proposed to segment sonar imagery into three categories of region. In order to improve the accuracy of segmentation and the convergence rate of the level set model, BEMD (Two-dimensional Empirical Mode Decomposition) is used to describe the model's energy function. Through BEMD weighted parameters, the anti-noise performance of the model is improved without losing the accuracy of segmentation. After analysis of the contact of the c-means algorithm and the level set algorithm, an improved c-means algorithm is used to initialize the level set evolution curve. What's more, a penalty term in the energy of level set is added to improve the evolution speed. Unsupervised sonar image segmentation experiments are done by using improved BEMD-hierarchical level set segmentation algorithm. Compared with other algorithms, the noise immunity, the segmentation accuracy and rapidity of the proposed algorithm are validated.

  19. Anatomy comic strips.

    Science.gov (United States)

    Park, Jin Seo; Kim, Dae Hyun; Chung, Min Suk

    2011-01-01

    Comics are powerful visual messages that convey immediate visceral meaning in ways that conventional texts often cannot. This article's authors created comic strips to teach anatomy more interestingly and effectively. Four-frame comic strips were conceptualized from a set of anatomy-related humorous stories gathered from the authors' collective imagination. The comics were drawn on paper and then recreated with digital graphics software. More than 500 comic strips have been drawn and labeled in Korean language, and some of them have been translated into English. All comic strips can be viewed on the Department of Anatomy homepage at the Ajou University School of Medicine, Suwon, Republic of Korea. The comic strips were written and drawn by experienced anatomists, and responses from viewers have generally been favorable. These anatomy comic strips, designed to help students learn the complexities of anatomy in a straightforward and humorous way, are expected to be improved further by the authors and other interested anatomists. PMID:21634024

  20. A Research on Improving Image Segmentation Algorithm Based on Curve Evolution%曲线演化的图像分割算法改进研究

    Institute of Scientific and Technical Information of China (English)

    曾金发; 曹功坤

    2011-01-01

    This essay has made a research on improving the auto-detection effect for images based on curve evolution.Since the image recognition and accuracy are low, the traditional Chan-vese active contour model (C-V model) can not detect the edge far away from the active contour lines and different from the average gray value.By using the gray weighted average of object and background out of image of evolution curves of level collection and adjusting the weights, the image segmentation algorithm can converge the evolution curve accurately and quickly to the image edge far away from the average gray intensity.The algorithm has the ability of topology changes.It can split fast, overcome the defects that C-V model can not detect the edge, accelerate the convergence speed of image segmentation and improve the sesmentafion effect.%研究提高曲线演化的图像自动检测效果问题.由于图像识别度低、准确度低,传统 Chan-vese 活动轮廓模型(C-V 模型)不能检测到远离活动轮廓线且与平均灰度值相差大的边缘.图像分割算法采用水平集演化曲线外图像的目标和背景的灰度加权平均值,通过调节权重值,使演化曲线能准确快速收敛于远离平均灰度强度的图像边缘上.该算法具备拓扑变化能力,分割速度快,能克服原 C-V 模型不能检测到边缘缺陷,加速图像分割的收敛速度,提高分割效果.

  1. Auxiliary anatomical labels for joint segmentation and atlas registration

    Science.gov (United States)

    Gass, Tobias; Szekely, Gabor; Goksel, Orcun

    2014-03-01

    This paper studies improving joint segmentation and registration by introducing auxiliary labels for anatomy that has similar appearance to the target anatomy while not being part of that target. Such auxiliary labels help avoid false positive labelling of non-target anatomy by resolving ambiguity. A known registration of a segmented atlas can help identify where a target segmentation should lie. Conversely, segmentations of anatomy in two images can help them be better registered. Joint segmentation and registration is then a method that can leverage information from both registration and segmentation to help one another. It has received increasing attention recently in the literature. Often, merely a single organ of interest is labelled in the atlas. In the presense of other anatomical structures with similar appearance, this leads to ambiguity in intensity based segmentation; for example, when segmenting individual bones in CT images where other bones share the same intensity profile. To alleviate this problem, we introduce automatic generation of additional labels in atlas segmentations, by marking similar-appearance non-target anatomy with an auxiliary label. Information from the auxiliary-labeled atlas segmentation is then incorporated by using a novel coherence potential, which penalizes differences between the deformed atlas segmentation and the target segmentation estimate. We validated this on a joint segmentation-registration approach that iteratively alternates between registering an atlas and segmenting the target image to find a final anatomical segmentation. The results show that automatic auxiliary labelling outperforms the same approach using a single label atlasses, for both mandibular bone segmentation in 3D-CT and corpus callosum segmentation in 2D-MRI.

  2. Segmentation of radiographic images under topological constraints: application to the femur

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-09-15

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

  3. 基于Gabor小波和SVM的人脸表情识别算法%Facial Expression Recognition Algorithm Based on Gabor Wavelet Automatic Segmentation and SVM

    Institute of Scientific and Technical Information of China (English)

    陈亚雄

    2011-01-01

    针对包含表情信息的静态图像,提出基于Gabor小波和SVM的人脸表情识别算法.根据先验知识,并使用形态学和积分投影相结合定位眉毛眼睛区域,采用模板内计算均值定位嘴巴区域,自动分割出表情子区域.对分割出的表情子区域进行Gabor小波特征提取,在利用Fisher线性判别对特征进行降维,去除冗余和相关.利用支持向量机对人脸表情进行分类.用该算法在日本表情数据库上进行测试,获得了较高的识别准确率.证明了该算法的有效性.%A facial recognition algorithm based on Gabor wavelet and SVM is proposed in allusion to static image containing expression Information. The mathematical morphology combined with projection is adopted to locate the brow and eye region < and the calculating mean value in template is employed to locate the mouth region, which can segment the expression sub-regions automatically. The features of the expression sub-regions are extracted by Gabor wavelet transformation and then effective Gabor expression features are selected by Fisher linear discriminate (FLD) to deduce the dimension and redundancy of the features. The features are sent to support vector machine (SVM) to classify the different expressions. The algorithm was tested in Japanese female expression database. It can get a high precision of recognition. The feasibility of this method was verified by experiments.

  4. 基于竞选算法的图像多阈值分割技术%Multilevel Thresholding Segmentation Technique Based on Election Campaign Optimization Algorithm

    Institute of Scientific and Technical Information of China (English)

    涂叙安; 吕文阁

    2016-01-01

    This paper presents a method to get the optimal threshold based on gray-level histogram transform, using the election campaign algorithm as the basis of rapid search the global optimal threshold algorithm. First,select multiple grey value for a group divided gray-level histogram into several parts, this histograms synthesized normal distribution function and multiplied by their weights, add them as a new distribution function. after that,the new function and the original histogram are normalized respectively and in the solution space solving the absolute value of difference between them,the smallest set of grey value as the image segmentation thresholds.%提出了一种基于灰度直方图变换求解最佳阈值的方法,采用竞选算法作为快速搜索全局最优阈值的基础算法。首先,选取多个灰度值为一组,将整个灰度直方图分割成几部分,分别对这些直方图拟合成正态分布函数后加权相加合成一个新的分布函数,然后,将优化分布函数与原直方图分别归一化处理,在解空间内求解它们差值的绝对值的和,取和值最小的那组灰度值作为图像的分割阈值。

  5. K-means聚类算法在民航客户细分中的应用%Application of K-means algorithm to civil aviation customer segmentation

    Institute of Scientific and Technical Information of China (English)

    杨倩倩; 生佳根; 赵海田

    2015-01-01

    This paper aims at studying the problem of customer value in customer relationship management according to current airline data warehouse. The K-means clustering algorithm is used to build an aviation customer segmentation model which makes the customers classified into three types, and the relative marketing strategies were put forward accordingly. Experimental results show that the method can highlight the differences between samples, calculating the customer value more properly, and the customer value is improved by nearly 30%.%针对客户关系管理中客户价值这一问题,通过对航空公司现有数据仓库中客户信息的分析,采用数据挖掘技术中的K-means聚类算法建立民航客户细分模型,并通过实验将民航客户细分为3类,提出了对这3类航空客户的相关营销策略。实验结果表明该方法能突出客户之间的行为特征差异,更加准确地划分客户类型,进而使得客户价值约提高30%。

  6. 层次聚类算法在气象客户细分中的应用%Application of Hierarchical Clustering Algorithm in Meteorological Customer Segmentation

    Institute of Scientific and Technical Information of China (English)

    巨晓璇; 邹小斌; 屈直; 刘春敏

    2015-01-01

    本文以陕西省专业气象服务客户群为研究对象,结合2008-2013年陕西省气象局专业气象客户类别、贡献、合作年限等客户数据,以SPSS统计分析软件为工具,选用层次聚类算法对陕西省专业气象服务的客户进行细分,同时提出相应的营销策略.%This paper, taking Shaanxi Province professional meteorological service customersas the research objects, combined with 2008--2013 Shaanxi Provincial Meteorological Bureau specialized meteorological customer category, contribution, cooperation experience and other customer data,with SPSS statistical analysis software as the tool, used hierarchical clustering algorithm to segment the customers ofShaanxi professional meteorological service, and pro?posed corresponding marketing strategies.

  7. Image segmentation and registration algorithm to collect thoracic skeleton semilandmarks for characterization of age and sex-based thoracic morphology variation.

    Science.gov (United States)

    Weaver, Ashley A; Nguyen, Callistus M; Schoell, Samantha L; Maldjian, Joseph A; Stitzel, Joel D

    2015-12-01

    Thoracic anthropometry variations with age and sex have been reported and likely relate to thoracic injury risk and outcome. The objective of this study was to collect a large volume of homologous semilandmark data from the thoracic skeleton for the purpose of quantifying thoracic morphology variations for males and females of ages 0-100 years. A semi-automated image segmentation and registration algorithm was applied to collect homologous thoracic skeleton semilandmarks from 343 normal computed tomography (CT) scans. Rigid, affine, and symmetric diffeomorphic transformations were used to register semilandmarks from an atlas to homologous locations in the subject-specific coordinate system. Homologous semilandmarks were successfully collected from 92% (7077) of the ribs and 100% (187) of the sternums included in the study. Between 2700 and 11,000 semilandmarks were collected from each rib and sternum and over 55 million total semilandmarks were collected from all subjects. The extensive landmark data collected more fully characterizes thoracic skeleton morphology across ages and sexes. Characterization of thoracic morphology with age and sex may help explain variations in thoracic injury risk and has important implications for vulnerable populations such as pediatrics and the elderly. PMID:26496701

  8. On Customer Segmentation Based on K-means Clustering Algorithm%基于K-means聚类算法的客户细分探讨

    Institute of Scientific and Technical Information of China (English)

    缪兵

    2012-01-01

    The paper focuses on importance of K-means clustering algorithm among clustering analyses in the analysis of customer value and provides customer segmentation through analysis of the customer's current and potential values.On this basis,enterprises may identify characteristics of various types of customers in conjunction with industrial features and implement differentiated service strategies and offer better resources and services to the most valuable customers,so as to achieve the goal of profitability as well as customer satisfaction.%重点讨论了聚类分析方法中K-means聚类算法在客户价值分析中的作用,通过对客户的现有价值和潜在价值进行分析,对客户进行细分。在此基础上,企业可结合行业的特征找出各类客户的特点,实行差异化服务策略,让更好的资源和服务提供给最有价值客户,从而达到顾客满意、企业盈利的目的。

  9. Skull Base Anatomy.

    Science.gov (United States)

    Patel, Chirag R; Fernandez-Miranda, Juan C; Wang, Wei-Hsin; Wang, Eric W

    2016-02-01

    The anatomy of the skull base is complex with multiple neurovascular structures in a small space. Understanding all of the intricate relationships begins with understanding the anatomy of the sphenoid bone. The cavernous sinus contains the carotid artery and some of its branches; cranial nerves III, IV, VI, and V1; and transmits venous blood from multiple sources. The anterior skull base extends to the frontal sinus and is important to understand for sinus surgery and sinonasal malignancies. The clivus protects the brainstem and posterior cranial fossa. A thorough appreciation of the anatomy of these various areas allows for endoscopic endonasal approaches to the skull base.

  10. Anatomy of Sarcocaulon

    Directory of Open Access Journals (Sweden)

    R. L. Verhoeven

    1983-12-01

    Full Text Available The anatomy of the leaf blade, petiole, stem and root of the genus Sarcocaulon (DC. Sweet is discussed. On the basis of the leaf anatomy, the four sections recognized by Moffett (1979 can be identified: section Denticulati (dorsiventral leaves, section Multifidi (isobilateral leaves and adaxial and abaxial palisade continuous at midvein, section Crenati (isobilateral leaves, short curved trichomes and glandular hairs, section Sarcocaulon (isobilateral leaves and glandular hairs only. The anatomy of the stem is typically that of a herbaceous dicotyledon with a thick periderm. The root structure shows that the function of the root is not food storage.

  11. 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.

  12. Comparison of a Gross Anatomy Laboratory to Online Anatomy Software for Teaching Anatomy

    Science.gov (United States)

    Mathiowetz, Virgil; Yu, Chih-Huang; Quake-Rapp, Cindee

    2016-01-01

    This study was designed to assess the grades, self-perceived learning, and satisfaction between occupational therapy students who used a gross anatomy laboratory versus online anatomy software (AnatomyTV) as tools to learn anatomy at a large public university and a satellite campus in the mid-western United States. The goal was to determine if…

  13. Segmentation of Noisy Discrete Surfaces

    OpenAIRE

    Provot, Laurent; Debled-Rennesson, Isabelle

    2008-01-01

    International audience We propose in this paper a segmentation process that can deal with noisy discrete objects. A flexible approach considering arithmetic discrete planes with a variable width is used to avoid the over-segmentation that might happen when classical segmentation algorithms based on regular discrete planes are used to decompose the surface of the object. A method to choose a seed and different segmentation strategies according to the shape of the surface are also proposed.

  14. 基于同态滤波和K均值聚类算法的杨梅图像分割%Bayberry image segmentation based on homomorphic filtering and K-means clustering algorithm

    Institute of Scientific and Technical Information of China (English)

    徐黎明; 吕继东

    2015-01-01

    For harvesting robot, fruit identification is the key step for accurate fruit positioning and successful picking. The primary task of fruit identification and picking is to separate fruit from complicated background of branches, trunk and sky by image segmentation. It is hard to accurately segment colorized bayberry image because there are fruits with low brightness or uneven illumination in nature scenes. In this study, RGB (red, green and blue) color space was transformed into HSV (hue, saturation and value) space. After that, the luminance component of image was strengthened by dynamic Butterworth homomorphism filter transfer function. Then, it was restored to RGB color space for colorized image illumination compensation and shadow removal. The bayberry image after shadow removal included red bayberry, green leave and white sky. Each pixel of colorized bayberry image to be segmented was considered as one point of data set X. These pixels were classified into red, green and white. According to the characteristics of the componentsa andb in Lab color space, RGB color space was transformed into CIELAB space. The K-means clustering algorithm was used for image segmentation, and the parameterK was selected as 3. In order to verify the effectiveness of the proposed algorithm, 15 bayberry images were selected from 100 images affected by different degrees of shadow under different growth conditions and uneven illumination conditions. Firstly,in order to prove effectiveness of illumination compensation, theK-means clustering algorithm was used to conduct image segmentation experiments before and after illumination compensation to shadow removal. Secondly, in order to validate segmentation effectiveness of images after illumination compensation based on different methods, this study applied adaptive 2*R-G-B grey threshold andK-means clustering segmentation algorithms to compare their effects of shadow removal. Thirdly, homomorphism filter algorithm was compared with

  15. Polarimetric Segmentation Using Wishart Test Statistic

    DEFF Research Database (Denmark)

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

    2002-01-01

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

  16. MEDICAL IMAGE SEGMENTATION

    Directory of Open Access Journals (Sweden)

    Madhavi Latha

    2010-07-01

    Full Text Available Image segmentation is an essential but critical component in low level vision image analysis, pattern recognition, and in robotic systems. It is one of the most difficult and challenging tasks in image processing which determines the quality of the final result of the image analysis. Image segmentation is the process of dividing an image into different regions such that each region is homogeneous. Various image segmentation algorithms are discussed. Some examples in different image formats are presented and overall results discussed and compared considering different parameters.

  17. An interactive segmentation method based on superpixel

    DEFF Research Database (Denmark)

    Yang, Shu; Zhu, Yaping; Wu, Xiaoyu

    2015-01-01

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

  18. LAPAROSCOPIC ANATOMY OF THE EXTRAHEPATIC BILIARY TRACT

    Directory of Open Access Journals (Sweden)

    E. Târcoveanu

    2005-01-01

    Full Text Available Development of mini-invasive surgery determinates a rapid improvement in laparoscopic regional anatomy. As laparoscopy is becoming common in most surgical departments, basic laparoscopic anatomy is mandatory for all residents in general surgery. Successful general surgery starts in the anatomy laboratory. Successfully minim invasive surgery starts in the operative theatre with laparoscopic exploration. The initial laparoscopic view of the right upper quadrant demonstrates primarily the subphrenic spaces, abdominal surface of the diaphragm and diaphragmatic surface of the liver. The falciform ligament is a prominent dividing point between the left subphrenic space and the right subphrenic space. The ligamentum teres hepatis is seen in the free edge of the falciform. Upward traction on the gallbladder exposes the structures of Calot’s triangle and the hepatoduodenal ligament. The liver is divided into anatomic segments based on internal anatomy that is invisible to the laparoscopist. Surface landmarks include the falciform ligament and the gallbladder fossa. The surgical procedures performed laparoscopically currently include liver biopsy, wedge resection, fenestration of hepatic cysts, laparoscopic approach of the hidatid hepatic cyst, and atypical hepatectomy. We present the laparoscopic anatomy of extrahepatic biliary tract. Once the gallbladder is elevated, inspection reveals Hartmann’s pouch and the cystic duct. The typical angular junction of the cystic duct on the common duct actually occurs in a minority of patients and the length and course of the cystic duct are highly variable. The boundaries of Calot’s triangle are often not well seen. The cystic artery is often visible under the peritoneum as it runs along the surface of the gallbladder. The variations of the structures of the hepatoduodenal ligament may occur to injuries during laparoscopic cholecystectomy. Cholangiography increases the safety of dissection of biliary tract by

  19. Variation in root wood anatomy

    NARCIS (Netherlands)

    Cutler, D.F.

    1976-01-01

    Variability in the anatomy of root wood of selected specimens particularly Fraxinus excelsior L. and Acer pseudoplatanus L. in the Kew reference microscope slide collection is discussed in relation to generalised statements in the literature on root wood anatomy.

  20. Anatomy relevant to conservative mastectomy

    OpenAIRE

    O’Connell, Rachel L.; Rusby, Jennifer E

    2015-01-01

    Knowledge of the anatomy of the nipple and breast skin is fundamental to any surgeon practicing conservative mastectomies. In this paper, the relevant clinical anatomy will be described, mainly focusing on the anatomy of the “oncoplastic plane”, the ducts and the vasculature. We will also cover more briefly the nerve supply and the arrangement of smooth muscle of the nipple. Finally the lymphatic drainage of the nipple and areola will be described. An appreciation of the relevant anatomy, tog...

  1. A Heuristic Image Search Algorithm for Active Shape Model Segmentation of the Caudate Nucleus and Hippocampus in Brain MR Images of Children with FASD

    Directory of Open Access Journals (Sweden)

    A A Eicher

    2012-09-01

    Full Text Available Magnetic Resonance Imaging provides a non-invasive means to study the neural correlates of Fetal Alcohol Spectrum Disorder (FASD - the most common form of preventable mental retardation worldwide. One approach aims to detect brain abnormalities through an assessment of volume and shape of two sub-cortical structures, the caudate nucleus and hippocampus. We present a method for automatically segmenting these structures from high-resolution MR images captured as part of an ongoing study into the neural correlates of FASD. Our method incorporates an Active Shape Model, which is used to learn shape variation from manually segmented training data. A modified discrete Geometrically Deformable Model is used to generate point correspondence between training models. An ASM is then created from the landmark points. Experiments were conducted on the image search phase of ASM segmentation, in order to find the technique best suited to segmentation of the hippocampus and caudate nucleus. Various popular image search techniques were tested, including an edge detection method and a method based on grey profile Mahalanobis distance measurement. A novel heuristic image search method was also developed and tested. This heuristic method improves image segmentation by taking advantage of characteristics specific to the target data, such as a relatively homogeneous tissue colour in target structures. Results show that ASMs that use the heuristic image search technique produce the most accurate segmentations. An ASM constructed using this technique will enable researchers to quickly, reliably, and automatically segment test data for use in the FASD study.

  2. 基于模糊ABC算法的空间域SAR图像阈值分割%SAR image threshold segmentation in spatial domain based on fuzzy artificial bee colony algorithm

    Institute of Scientific and Technical Information of China (English)

    柳新妮; 马苗

    2012-01-01

    In order to increase the speed of SAR image segmentation based on fuzzy Artificial Bee Colony algorithm, a method of SAR image in spatial threshold segmentation is proposed. In this method, gray morphology operations are employed to reduce the inherent image noise, and the searching range is reduced on the basis of the histogram feature of the denoised image. Simultaneously, a fuzzy function is introduced in order to refine the motion of bees, and fast search the optimal threshold. Experimental results show that the proposed method is not only robust to the speckle noise in SAR images, but also superior to the segmentation methods based on Genetic algorithm or Artificial Fish Swarm algorithm in terms of segmenting speed and quality.%为提高SAR(合成孔径雷达)图像分割速度,提出一种基于模糊ABC(人工蜂群)算法的空间域SAR图像闽值分割方法.该方法利用灰度形态学算子抑制图像噪声,根据抑噪图像的直方图特征缩小阈值范围,同时引入模糊隶属度函数优化蜂的运动轨迹,快速搜索最优分割阂值.实验结果显示,该方法不仅能有效抑制可见光图像和真实SAR图像中的斑点噪声,而且分割速度与分割质量明显优于基于遗传算法和人工鱼群算法的分割方法.

  3. OpenCV分水岭算法的改进及其在细胞分割中的应用%Improvement on watershed algorithm of OpenCV and its application in cell image segmentation

    Institute of Scientific and Technical Information of China (English)

    张羽; 徐端全

    2012-01-01

    分水岭算法是一种基于形态学的图像分割算法,能快速准确地确定连通区域的边界.将基于标记的分水岭算法用于细胞图像的分割,较好地解决了粘连细胞的分割问题.在该细胞分割算法的实现过程中,发现了OpenCV分水岭算法实现的缺陷,通过对相关代码的分析,发现该缺陷存在的原因是算法流程中对相邻像素相对关系的描述存在问题.将OpenCV分水岭算法中对相邻像素取差的绝对值,改为对相邻像素取差值,对该算法进行了改进.实验证明,改进后的OpenCV分水岭算法对细胞图像的分割效果明显好于直接使用OpenCV分水岭算法得到的结果.该方法在不影响分割速度的情况下,提高了OpenCV分水岭算法分割的准确度.%Watershed is an image segmentation algorithm based on morphology, which can determine the boundary of connected section efficiently and effectively. Application of marker watershed algorithm in cell image segmentation leads to the solution of adhesion cell segmentation. When implementing this algorithm, a flaw of the watershed algorithm in OpenCV has been found. The cause of this bug is the wrong description of the difference between two adjacent pixels. An improvement of OpenCV watershed was proposed by replacing the absolute difference between adjacent pixels with the difference between them. The experiment shows that the improved OpenCV watershed algorithm has a better segmentation performance than that of original algorithm with same processing speed.

  4. Learning Anatomy Enhances Spatial Ability

    Science.gov (United States)

    Vorstenbosch, Marc A. T. M.; Klaassen, Tim P. F. M.; Donders, A. R. T.; Kooloos, Jan G. M.; Bolhuis, Sanneke M.; Laan, Roland F. J. M.

    2013-01-01

    Spatial ability is an important factor in learning anatomy. Students with high scores on a mental rotation test (MRT) systematically score higher on anatomy examinations. This study aims to investigate if learning anatomy also oppositely improves the MRT-score. Five hundred first year students of medicine ("n" = 242, intervention) and…

  5. Improved container code segmentation algorithm based on mathematical morphology.%基于数学形态学的集装箱箱号分割改进算法

    Institute of Scientific and Technical Information of China (English)

    谭伟; 方超; 杜建洪

    2011-01-01

    This paper has advanced an improved algorithm based on mathematical morphology and histogram projection. In the locating section, an improved algorithm based on edge detection and mathematical morphology is used to connect the container code area into a whole connecting region,which can fix the size of the morphologic structure adaptively and solve the problem of vertical array of the container characters.In the segmentation section, mathematical morphology is employed to remove noise, and histogram projection is used to segment each character horizontally and vertically. The exit resuits indicate that this algorithm is easy and available with little prior information and the overall segmentation accuracy can achieve 93.33%,which proves the validity of the algorithm.%提出了基于数学形态学和直方图投影的集装箱箱号分割改进算法.在箱号定位阶段,运用基于边缘检测和数学形态学的改进算法,能自适应确定形态学结构元素的大小,将箱号区域连通成一个区域,并能解决集装箱文字纵向排列的问题.字符分割阶段用数学形态学方法消除干扰边缘和噪声,通过投影直方图法完成行与列分割.实验表明,该算法简单可行,只需较少的集装箱先验信息,并且整箱分割正确率达到93.33%,证明了算法的有效性.

  6. 基于蛙跳算法与Otsu法的图像多阈值分割技术%Multilevel thresholding segmentation based on shuffled frog leaping algorithm and Otsu method

    Institute of Scientific and Technical Information of China (English)

    康杰红; 马苗

    2012-01-01

    为了快速准确地确定多阈值图像分割中的最佳阈值,提出了一种基于蛙跳算法与Otsu法相结合的多阈值图像分割方法.该方法将多阈值求解看作一种多变量的组合求解优化问题,利用多阈值Otsu法设计分割目标函数,将新兴的仿生学优化求解算法——蛙跳算法引入到图像分割技术中,通过蛙跳算法中全局搜索和局部搜索相结合的搜索机制并行求解多个阈值.实验结果表明,该方法与基于人工鱼群算法的图像多阈值分割方法相比,明显提高了图像分割速度和分割质量.%In order to obtain a group of satisfying thresholds in image segmentation quickly and accurately, this paper proposed a method based on shuffled frog leaping (SFL) algorithm and Otsu method for multilevel thresholding image segmentation. The method regarded the group of thresholds as a group of potential solutions to a certain objective function, and employed the extended Otsu method to be the fitness function for SFL algorithm. And then, the powerful searching ability of SFL algorithm was used to locate the thresholds in parallel, which combines the global search in the whole swarm and local searches in subswarms. Experimental results showed that compared with the method based on artificial fish swarm (AFS) algorithm, the suggested method obviously im- proved the performance of image segmentation in speed and quality.

  7. An automated three-dimensional detection and segmentation method for touching cells by integrating concave points clustering and random walker algorithm.

    Directory of Open Access Journals (Sweden)

    Yong He

    Full Text Available Characterizing cytoarchitecture is crucial for understanding brain functions and neural diseases. In neuroanatomy, it is an important task to accurately extract cell populations' centroids and contours. Recent advances have permitted imaging at single cell resolution for an entire mouse brain using the Nissl staining method. However, it is difficult to precisely segment numerous cells, especially those cells touching each other. As presented herein, we have developed an automated three-dimensional detection and segmentation method applied to the Nissl staining data, with the following two key steps: 1 concave points clustering to determine the seed points of touching cells; and 2 random walker segmentation to obtain cell contours. Also, we have evaluated the performance of our proposed method with several mouse brain datasets, which were captured with the micro-optical sectioning tomography imaging system, and the datasets include closely touching cells. Comparing with traditional detection and segmentation methods, our approach shows promising detection accuracy and high robustness.

  8. 基于模糊速度函数的活动轮廓模型的肺结节分割%A Segmentation Algorithm of Pulmonary Nodules Using Active Contour Model Based on Fuzzy Speed Function

    Institute of Scientific and Technical Information of China (English)

    陈侃; 李彬; 田联房

    2013-01-01

    Pulmonary nodules are potential manifestation of lung cancer.In order to detect juxta-vascular pulmonary nodules and ground glass opacity pulmonary nodules in computer-aided diagnosis (CAD) system,the above two types of pulmonary nodules need to be accurately segmented.At present,the segmentation algorithm of pulmonary nodules using traditional active contour model may cause boundary leakage.In order to avoid this phenomenon,a new segmentation algorithm of pulmonary nodules using active contour model based on fuzzy speed function is proposed in this paper.First,the fuzzy membership degree in fuzzy speed function is calculated by using the fuzzy clustering algorithm,which uses gray feature and local shape index.Second,a fuzzy speed function is incorporated into the active contour model.At the boundary of pulmonary nodules,tbe fuzzy speed function equals zero and the evolution of the contour curve stops,so that the accurate segmentation of pulmonary nodules is completed.Experimental results show that the proposed algorithm can achieve accurate segmentation of juxta-vascular pulmonary nodules and ground glass opacity pulmonary nodules.%肺结节是肺癌在早期阶段的表现形式.利用计算机辅助诊断(Computer-aided diagnosis,CAD)技术对血管粘连型肺结节和磨玻璃型肺结节进行检测,需要对这两类肺结节进行准确的分割.目前基于传统活动轮廓模型的肺结节分割算法,存在边界泄露现象.对此,本文提出一种基于模糊速度函数的活动轮廓模型的肺结节分割算法.首先,采用结合灰度特征和局部形态特征的模糊聚类算法,计算模糊速度函数中的模糊隶属度;其次,将模糊速度函数引入到活动轮廓模型中,在肺结节的边界处,该速度函数为零,轮廓曲线停止演变,从而完成肺结节的分割.实验结果表明,本文提出的算法可以精确地分割血管粘连肺结节和磨玻璃型肺结节.

  9. Plugin procedure in segmentation and application to hyperspectral image segmentation

    OpenAIRE

    Girard, R

    2010-01-01

    In this article we give our contribution to the problem of segmentation with plug-in procedures. We give general sufficient conditions under which plug in procedure are efficient. We also give an algorithm that satisfy these conditions. We give an application of the used algorithm to hyperspectral images segmentation. Hyperspectral images are images that have both spatial and spectral coherence with thousands of spectral bands on each pixel. In the proposed procedure we combine a reduction di...

  10. Anatomy for Biomedical Engineers

    Science.gov (United States)

    Carmichael, Stephen W.; Robb, Richard A.

    2008-01-01

    There is a perceived need for anatomy instruction for graduate students enrolled in a biomedical engineering program. This appeared especially important for students interested in and using medical images. These students typically did not have a strong background in biology. The authors arranged for students to dissect regions of the body that…

  11. The Anatomy Puzzle Book.

    Science.gov (United States)

    Jacob, Willis H.; Carter, Robert, III

    This document features review questions, crossword puzzles, and word search puzzles on human anatomy. Topics include: (1) Anatomical Terminology; (2) The Skeletal System and Joints; (3) The Muscular System; (4) The Nervous System; (5) The Eye and Ear; (6) The Circulatory System and Blood; (7) The Respiratory System; (8) The Urinary System; (9) The…

  12. Leaf anatomy and photosynthesis

    NARCIS (Netherlands)

    Berghuijs, H.N.C.

    2016-01-01

    Keywords: CO2 diffusion, C3 photosynthesis, mesophyll conductance, mesophyll resistance, re-assimilation, photorespiration, respiration, tomato Herman Nicolaas Cornelis Berghuijs (2016). Leaf anatomy and photosynthesis; unravelling the CO2 diffusion pathway in C3 leaves. PhD thesis. Wageningen Unive

  13. 基于图像区域分割和置信传播的立体匹配算法%Stereo Matching Algorithm Based on Image Region Segmentation and Belief Propagation

    Institute of Scientific and Technical Information of China (English)

    张惊雷; 王艳姣

    2013-01-01

    As the high error matching rates of the traditional pixel-based matching algorithm,a stereo matching algorithm based on image region segmentation and Belief Propagation(BP) is proposed.The mean shift algorithm is applied to segment the reference image into regions with homogeneous color,and the initial disparity of each pixel is calculated by means of the adaptive weights approaches.The disparity plane parameters are collected by plane model fitting on each segmented region.The ultimate disparity map is acquired by calculated the regional optimal disparity plane,which uses the improved region-based belief propagation algorithm.Compared with the pixel-based global optimization algorithms such as classical BP and Graph Cut(GC) algorithm,this algorithm can greatly reduce the error matching rates especially in textureless regions and occluded regions.%传统基于像素的立体匹配算法误匹配率较高.为解决该问题,提出一种基于图像区域分割和置信传播的匹配算法.采用均值偏移对参考图像进行区域分割,通过自适应权值匹配计算初始视差图,对各分割区域的初始视差用平面模型拟合得到视差平面参数,使用基于区域的改进置信传播算法求得各区域的最优视差平面,从而得到最终视差图.与全局优化的经典置信传播算法和图割算法的对比实验结果表明,该算法能降低低纹理区域和遮挡区域的误匹配率.

  14. Bayesian Parameter Estimation and Segmentation in the Multi-Atlas Random Orbit Model.

    Directory of Open Access Journals (Sweden)

    Xiaoying Tang

    Full Text Available This paper examines the multiple atlas random diffeomorphic orbit model in Computational Anatomy (CA for parameter estimation and segmentation of subcortical and ventricular neuroanatomy in magnetic resonance imagery. We assume that there exist multiple magnetic resonance image (MRI atlases, each atlas containing a collection of locally-defined charts in the brain generated via manual delineation of the structures of interest. We focus on maximum a posteriori estimation of high dimensional segmentations of MR within the class of generative models representing the observed MRI as a conditionally Gaussian random field, conditioned on the atlas charts and the diffeomorphic change of coordinates of each chart that generates it. The charts and their diffeomorphic correspondences are unknown and viewed as latent or hidden variables. We demonstrate that the expectation-maximization (EM algorithm arises naturally, yielding the likelihood-fusion equation which the a posteriori estimator of the segmentation labels maximizes. The likelihoods being fused are modeled as conditionally Gaussian random fields with mean fields a function of each atlas chart under its diffeomorphic change of coordinates onto the target. The conditional-mean in the EM algorithm specifies the convex weights with which the chart-specific likelihoods are fused. The multiple atlases with the associated convex weights imply that the posterior distribution is a multi-modal representation of the measured MRI. Segmentation results for subcortical and ventricular structures of subjects, within populations of demented subjects, are demonstrated, including the use of multiple atlases across multiple diseased groups.

  15. Segmentation of anatomical branching structures based on texture features and conditional random field

    Science.gov (United States)

    Nuzhnaya, Tatyana; Bakic, Predrag; Kontos, Despina; Megalooikonomou, Vasileios; Ling, Haibin

    2012-02-01

    This work is a part of our ongoing study aimed at understanding a relation between the topology of anatomical branching structures with the underlying image texture. Morphological variability of the breast ductal network is associated with subsequent development of abnormalities in patients with nipple discharge such as papilloma, breast cancer and atypia. In this work, we investigate complex dependence among ductal components to perform segmentation, the first step for analyzing topology of ductal lobes. Our automated framework is based on incorporating a conditional random field with texture descriptors of skewness, coarseness, contrast, energy and fractal dimension. These features are selected to capture the architectural variability of the enhanced ducts by encoding spatial variations between pixel patches in galactographic image. The segmentation algorithm was applied to a dataset of 20 x-ray galactograms obtained at the Hospital of the University of Pennsylvania. We compared the performance of the proposed approach with fully and semi automated segmentation algorithms based on neural network classification, fuzzy-connectedness, vesselness filter and graph cuts. Global consistency error and confusion matrix analysis were used as accuracy measurements. For the proposed approach, the true positive rate was higher and the false negative rate was significantly lower compared to other fully automated methods. This indicates that segmentation based on CRF incorporated with texture descriptors has potential to efficiently support the analysis of complex topology of the ducts and aid in development of realistic breast anatomy phantoms.

  16. 室内惯性/视觉组合导航地面图像分割算法%Floor segmentation algorithm for indoor vision/inertial integrated navigation

    Institute of Scientific and Technical Information of China (English)

    汪剑鸣; 王曦; 王胜蓓; 李士心; 冷宇

    2011-01-01

    Navigation is a key technology for autonomous robots, which makes them movable in an unknown environment. To tackle the difficulty of building indoor navigation map for inertial navigation systems, a new map building method for inertial/visual navigation is proposed. By limiting robot's movement within the floor areas, the global navigation map is generated from a bird-view image. An algorithm of automatic floor segmentation is proposed, which employs principal component analysis to implement dimension reduction for local color features and adopts clustering analysis to realize floor segmentation automatically. Finally, an indoor bird-view image database is built to evaluate the algorithm. The algorithm gets the worst performance, 75% averaged accurate segmentation rate, on the fourth group images because illumination reflection is found in the images. Average accurate segmentation rates on other groups are around 85%. Thus, the preprocessing algorithms, such as illumination refection detection, can help to improve the performance of the algorithm.%导航技术是机器人实现自主移动的关键技术之一.针对惯性导航创建全局导航地图困难等问题,提出一种新的惯性/视觉组合导航室内全局地图创建方法.规定机器人只能在地面区域中移动,并利用室内俯视图像建立全局地图,提出一种俯视图像地面区域的自动分割算法.首先,利用主元分析算法对图像的局部颜色特征进行降维;其次,利用聚类算法对地面区域进行自动分割;最后,建立了室内俯视图像数据库并对算法的性能进行了验证.由于第四组图像中包含反光区域,算法的分割结果较差,平均正确分辨率为75%.算法在其他各组的平均正确分割率为85%左右.为提高算法的性能,可在应用本算法前利用反光区域检测算法对图像进行预处理.

  17. The Automatic Image Segmentation Method Based on Fast FCM and Random Walk Algorithm%基于快速FCM与随机游走算法的图像自动分割方法

    Institute of Scientific and Technical Information of China (English)

    许健才; 张良均; 余燕团

    2016-01-01

    在图像分割中,针对 FCM 算法存在聚类数目需要预先给定、收敛速度慢等缺点,本文把快速模糊 C 均值聚类算法和随机游走算法相结合,具体方法为先采用快速模糊 C 均值聚类算法对图像进行预分割,以便获得聚类中心的位置,然后将该中心作为随机游走的种子点,再进行图像分割,实验结果得到了较为满意的预期效果,证明该方法是可行的。本文的研究为快速 FCM 实现自适应性和开发图形图像预处理系统提供了技术支持与理论依据。%As far as image segmentation, the defeat of the number of clusters for FCM algorithm is reeded to be improued. In this paper, the fast fuzzy C-means clustering and random walk algorithm are combined to solve the problem of image segmentation. Firstly, the fast FCM for image pre-segmentation to obtain the number of clusters and cluster central location as the seed points of random walk firstly. Then, for image segmentation, experimental results show that this method is feasible, and get a more satisfactory desired purpose. Results of this study achieve self-adaptive and fast FCM develop graphical image preprocessing system provides technical support and theoretical basis.

  18. Effect of blood vessel segmentation on the outcome of electroporation-based treatments of liver tumors.

    Directory of Open Access Journals (Sweden)

    Marija Marčan

    Full Text Available Electroporation-based treatments rely on increasing the permeability of the cell membrane by high voltage electric pulses applied to tissue via electrodes. To ensure that the whole tumor is covered with sufficiently high electric field, accurate numerical models are built based on individual patient anatomy. Extraction of patient's anatomy through segmentation of medical images inevitably produces some errors. In order to ensure the robustness of treatment planning, it is necessary to evaluate the potential effect of such errors on the electric field distribution. In this work we focus on determining the effect of errors in automatic segmentation of hepatic vessels on the electric field distribution in electroporation-based treatments in the liver. First, a numerical analysis was performed on a simple 'sphere and cylinder' model for tumors and vessels of different sizes and relative positions. Second, an analysis of two models extracted from medical images of real patients in which we introduced variations of an error of the automatic vessel segmentation method was performed. The results obtained from a simple model indicate that ignoring the vessels when calculating the electric field distribution can cause insufficient coverage of the tumor with electric fields. Results of this study indicate that this effect happens for small (10 mm and medium-sized (30 mm tumors, especially in the absence of a central electrode inserted in the tumor. The results obtained from the real-case models also show higher negative impact of automatic vessel segmentation errors on the electric field distribution when the central electrode is absent. However, the average error of the automatic vessel segmentation did not have an impact on the electric field distribution if the central electrode was present. This suggests the algorithm is robust enough to be used in creating a model for treatment parameter optimization, but with a central electrode.

  19. 一种关于眼底渗血区检测的双标记双分割算法%A Testing Double-marked Double Segmentation Algorithm for Fundus Oozing Area

    Institute of Scientific and Technical Information of China (English)

    何金娇; 李巧倩; 赖永森; 詹宇艺; 徐文华

    2014-01-01

    Subhyaloid hemorrhage detection in the diagnosis of diseases is important,fundus image processing can reduce the computer doctor of duplication. But due to retinal image quality,detection algorithms,as well as the diversity and complexity of the bleed area and other factors,the current detection methods have kinds of rough and low rate of detection. It presents a new segmentation of fundus oculi lesion detection algorithm,including two segmentation and two marked extraction. Division for the first time is the simple segmentation of maximum cluster variance for image,mainly removing most of the background,extracting image segmentation tags. The second division, mainly to connect tag,the processed image is morphology for segmenting type,in order to obtain more detailed bleeding lesion area. Ex-perimental results show the effectiveness of the algorithm.%眼底出血区检测在疾病诊断中具有重要意义,计算机处理眼底图像可以减少医生的重复劳动。但由于受到眼底图像质量、检测算法,以及出血区的多样性和复杂性等因素的影响,目前的检测方法存在检测种类粗糙和检出率低的问题。文中提出一种新的眼底病灶检测分割算法,算法包括两次分割和两次标记提取。第一次分割是对图像进行简单的最大类间方差分割,主要是去除大部分的背景,提取分割得到的图像粗标记;第二次分割,主要是对形态学处理后的图像进行连通标记,进行类聚分割,以获得更细致的病变渗血区域。实验结果表明该算法是有效的。

  20. The anatomy workbook

    International Nuclear Information System (INIS)

    This is an atlas of human anatomy presented in the form of line drawings, many of which correspond to imaging planes used in ultrasound (US), computed tomography (CT), and magnetic resonance (MR). The book is organized into 17 sections, each covering a specific structure or organ system. Large, uncluttered drawings are labeled for identification of structures of interest. Many illustrations include captions consisting of comments explaining major divisions within organs, specific anatomic relationships and landmarks, and pertinent vascular anatomy. Most organs are first depicted in isolation or in relation to important adjacent organs or blood vessels and are rendered as if viewed from anterior, posterior, inferior, or superior perspectives. The organs are demonstrated again in serial transverse, saggital, and coronal sections, each accompanied by a drawing of a body in anatomic position denoting the plane of the section

  1. Efficient segmentation by sparse pixel classification

    DEFF Research Database (Denmark)

    Dam, Erik B; Loog, Marco

    2008-01-01

    Segmentation methods based on pixel classification are powerful but often slow. We introduce two general algorithms, based on sparse classification, for optimizing the computation while still obtaining accurate segmentations. The computational costs of the algorithms are derived, and they are dem......, and they are demonstrated on real 3-D magnetic resonance imaging and 2-D radiograph data. We show that each algorithm is optimal for specific tasks, and that both algorithms allow a speedup of one or more orders of magnitude on typical segmentation tasks.......Segmentation methods based on pixel classification are powerful but often slow. We introduce two general algorithms, based on sparse classification, for optimizing the computation while still obtaining accurate segmentations. The computational costs of the algorithms are derived...

  2. 股骨近端相关影像解剖学测量研究%The research of relevant image anatomy measurements of the proximal segment of femur

    Institute of Scientific and Technical Information of China (English)

    吴炳华; 尹生江; 戴闽; 徐聪

    2015-01-01

    Objective To obtain the morphological parameters of the proximal segment of the femur in Chinese healthy senior population through three-dimensional reconstruction of CT images of the femur in order to provide the anatomical basis for the design of the proximal femoral internal fixation system. Method The CT scan data of the proximal segment of the femur of 60 Chinese healthy senior personswas obtained and the three-dimensional reconstruction of the femur was performed using the system’s default software. The bony landmarks were determined on the three-dimensional images of the normal femur. Measurement included the anatomic indexes of the lesser trochanter, neck shaft, angle, femoral offset and femoral canal, etc. Results There was no statistically significant difference of all measurement parameters between the left side and the right side (P>0.05), and length of the vertical axis of the lesser trochanter was (26.80 ± 2.53) mm and its the transverse diameter was(16.09±1.72) mm;The height and the volume of the lesser trochanter was (8.41± 1.50) mm and (727.15 ± 165.18) mm3, respectively. The minimum length of the screw used to fix the lesser trochanter of the femur was (46.77 ± 2.70) mm, and the up-dip angle was (16.83 ± 2.06)° , the neck-shaft angle was(131.42 ± 8.03)° , the range of femoral offset was(37.85 ± 7.02)mm. Conclusion It is feasible to accurately identify the anatomical landmarks on the three-dimensional reconstruction of the femur. The measurement data was beneficial to treatment of the elderly patients with intertrochanteric fractures and design of the proximal femoral internal fixation system for fixation of the lesser trochanter.%目的:目的通过CT三维重建测量正常国人老年股骨近端的相关形态参数,为设计股骨近端内固定系统提供解剖学依据。方法对60位老年国人的股骨近端进行CT扫描,利用自带的医学图像处理软件进行三维重建,标定相关解剖标志,测量指

  3. Penile Embryology and Anatomy

    OpenAIRE

    Yiee, Jenny H.; Baskin, Laurence S

    2010-01-01

    Knowledge of penile embryology and anatomy is essential to any pediatric urologist in order to fully understand and treat congenital anomalies. Sex differentiation of the external genitalia occurs between the 7thand 17th weeks of gestation. The Y chromosome initiates male differentiation through the SRY gene, which triggers testicular development. Under the influence of androgens produced by the testes, external genitalia then develop into the penis and scrotum. Dorsal nerves supply penile sk...

  4. Segmental neurofibromatosis

    OpenAIRE

    Galhotra, Virat; Sheikh, Soheyl; Jindal, Sanjeev; Singla, Anshu

    2014-01-01

    Segmental neurofibromatosis is a rare disorder, characterized by neurofibromas or cafι-au-lait macules limited to one region of the body. Its occurrence on the face is extremely rare and only few cases of segmental neurofibromatosis over the face have been described so far. We present a case of segmental neurofibromatosis involving the buccal mucosa, tongue, cheek, ear, and neck on the right side of the face.

  5. Executions and scientific anatomy.

    Science.gov (United States)

    Dolezal, Antonín; Jelen, Karel; Stajnrtova, Olga

    2015-12-01

    The very word "anatomy" tells us about this branch's connection with dissection. Studies of anatomy have taken place for approximately 2.300 years already. Anatomy's birthplace lies in Greece and Egypt. Knowledge in this specific field of science was necessary during surgical procedures in ophthalmology and obstetrics. Embalming took place without public disapproval just like autopsies and manipulation with relics. Thus, anatomical dissection became part of later forensic sciences. Anatomical studies on humans themselves, which needed to be compared with the knowledge gained through studying procedures performed on animals, elicited public disapprobation and prohibition. When faced with a shortage of cadavers, anatomists resorted to obtaining bodies of the executed and suicide victims - since torture, public display of the mutilated body, (including anatomical autopsy), were perceived as an intensification of the death penalty. Decapitation and hanging were the main execution methods meted out for death sentences. Anatomists preferred intact bodies for dissection; hence, convicts could thus avoid torture. This paper lists examples of how this process was resolved. It concerns the manners of killing, vivisection on people in the antiquity and middle-ages, experiments before the execution and after, vivifying from seeming death, experiments with galvanizing electricity on fresh cadavers, evaluating of sensibility after guillotine execution, and making perfect anatomical preparations and publications during Nazism from fresh bodies of the executed. PMID:26859596

  6. Algorithmes pour la segmentation et l'amélioration de la qualité des images et des vidéos

    OpenAIRE

    Bertolino, Pascal

    2012-01-01

    Travaux sur la segmentation des images et des vidéos en vue de leur codage, indexation et interprétation ainsi que sur l'amélioration de la qualité de la restitution de ces images sur les écrans plats.

  7. 对数似然图像分割的快速主动轮廓跟踪算法%Fast active contour tracking algorithm based on log-likelihood image segmentation

    Institute of Scientific and Technical Information of China (English)

    杨华; 陈善静; 曾凯; 张红

    2012-01-01

    针对跟踪目标尺度变化问题,提出了基于灰度对数似然图像分割的快速主动轮廓跟踪算法.改进的主动轮廓跟踪算法将根据以目标与背景的颜色差异而建立的对数似然图对图像进行阈值分割和数学形态学处理,再将Kalman滤波器结合到主动轮廓跟踪算法进行目标跟踪.改进的主动轮廓跟踪算法对目标分割准确,轮廓特征显著,跟踪效果稳定,算法能很好地适应跟踪目标尺度变化.通过Kalman滤波器对目标位置点的预测减少了主动轮廓跟踪算法收敛的迭代次数,使算法的运算效率提高了33%左右.%A fast active contour tracking(ACT) algorithm based on log-likelihood image segmentation has been proposed to solve the scale change problem in the process of target tracking. The algorithm adopts the log-likelihood image segmentation method, which segments images according to their log-likelihood images built based on the color difference between target and background, and the mathematical morphology method, and tracks the target with conventional ACT algorithm combined with Kalman filter. It tracks the target precisely with distinct contour features and stable tracking performance, and can well adapt to the target scale change. The Kalman filter adopted reduces the number of iterations for algorithm convergence through its forecast of the target position, and thus the fast ACT algorithm is about 33% more efficient than the conventional one.

  8. Image Segmentation with Multi-Threshold of Gray-Level & Gradient-Magnitude Entropy Based on Genetic Algorithm%基于遗传算法的灰度-梯度熵多阈值图像分割

    Institute of Scientific and Technical Information of China (English)

    贺建峰; 符增; 易三莉; 相艳; 崔锐

    2015-01-01

    Due to considering the gray level spatial distribution information, some image segmentation technologies based on entropy threshold can enhance the thresholding segmentation performance. However, they still cannot dis-tinguish image edges and noise well. Even though GLGM (gray-level&gradient-magnitude) entropy can effectively solve the problem, it cannot segment effectively multi-objective and complex image. So, this paper proposes image segmentation with multi-threshold of GLGM entropy based on genetic algorithm. In the proposed method, integral figure is introduced in order to make threshold searching dimension from original O(9 ´ L) to O(L) , and the single threshold segmentation of GLGM entropy is further extended to multi-threshold segmentation. Lastly, the real-code-GA is used to search the best thresholds. The simulation results show that this method can be effectively applied for the multi-threshold segmentation of complex images.%一些基于熵的阈值图像分割技术考虑了空间信息,从而能够提高阈值分割的性能,但是仍然不能较好地区分边缘和噪声。尽管灰度-梯度(gray-level & gradient-magnitude,GLGM)熵算法能有效地解决以上问题,但是针对多目标和复杂图像却不能有效地分割。为此,提出了一种基于遗传算法(genetic algorithm,GA)的GLGM熵多阈值快速分割方法。该方法应用积分图思想将GLGM熵算法阈值搜索空间从O(9´ L)降到O(L),并将GLGM熵算法从单阈值拓展到多阈值。最后应用基于实数编码的遗传算法搜索GLGM熵多阈值的最佳阈值。仿真结果表明,该方法能够实现图像的快速多阈值分割,适合复杂图像分割。

  9. 用于中文分词的组合型歧义消解算法%COMBINATORIAL WORD SENSES DISAMBIGUATION ALGORITHM FOR CHINESE WORD SEGMENTATION

    Institute of Scientific and Technical Information of China (English)

    袁鼎荣; 李新友; 邵延振

    2011-01-01

    自动分词技术的瓶颈是切分歧义,切分歧义可分为交集型切分歧义和组合型切分歧义.以组合型歧义字段所在句子为研究对象,考察歧义字段不同切分方式所得结果与其前后搭配所得词在全文中的支持度,构造从合或从分切分支持度度量因子,依据该因子消除组合型歧义.通过样例说明和实验验证该方法可行并优于现有技术.%The bottleneck of automatic word segmentation is to segment the ambiguity of word senses, which can be divided into crossing ambiguity and combinational ambiguity of the word senses. In this paper, we took the sentence including word section with combinational ambiguity as our research object, examined the support degree of the words composed of the segmented results of ambiguous word section derived from different segmentation methods and their co-occurrence words in the text, constructed the metric factor of support degree of segmentations either in compliance to composition or to separation, the combinational ambiguity of word senses is cleared up according to the factor. The feasibility of the method and its predominance over present techniques have been illustrated by the exemplar and attested by the experiment.

  10. Neuro-Fuzzy Phasing of Segmented Mirrors

    Science.gov (United States)

    Olivier, Philip D.

    1999-01-01

    A new phasing algorithm for segmented mirrors based on neuro-fuzzy techniques is described. A unique feature of this algorithm is the introduction of an observer bank. Its effectiveness is tested in a very simple model with remarkable success. The new algorithm requires much less computational effort than existing algorithms and therefore promises to be quite useful when implemented on more complex models.

  11. Segmental Neurofibromatosis

    Directory of Open Access Journals (Sweden)

    Yesudian Devakar

    1997-01-01

    Full Text Available Segmental neurofibromatosis is a rare variant of neurofibromatosis in which the lesions are confined to one segment or dermatome of the body. They resemble classical neurofibromas in their morphology, histopathology and electron microscopy. However, systemic associations are usually absent. We report one such case with these classical features.

  12. 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...... 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...... their evaluation of fish - for example by focusing on quality. Therefore, taking heterogeneity between segments into account makes a lot of difference, quantitatively as well as qualitatively....

  13. A Method of Compressed Domain Video Shot Segmentation Based on DCE Algorithm%基于DCE算法的压缩域视频镜头分割方法

    Institute of Scientific and Technical Information of China (English)

    黄永锋; 熊泽东; 王绍宇

    2012-01-01

    Shot segmentation is structural base for video retrieval. An efficient video shot segmentation method is proposed. Firstly, the features are extracted from I frame of video stream in the compressed domain, and the curve of feature information is drawn. Then, the discrete curve evolution (DCE) algorithm is used to evolved the curve. Finally, video shots are segmented and key frames are extracted by the key points of the curve. The experimental results show that the method is efficient and robust, because it takes fully into account the timing features of video encoding.%镜头分割是视频检索的结构化基础,为此提出一种高效的视频镜头分割方法.首先,在压缩域中提取视频流中Ⅰ帧携带的特征信息,并生成帧间特征分布曲线;然后,利用离散曲线演化(DCE)算法对预处理过的曲线进行分析与演进;最后,分割出视频镜头并提取关键帧,试验结果表明:该方法充分考虑了视频编码的时序特点,具有较好的分割效果,鲁棒性强.

  14. Research on Chinese Word Segmentation Based on Bi- Direction Marching Method and Feature Selection Algorithm%基于双向匹配法和特征选择算法的中文分词技术研究

    Institute of Scientific and Technical Information of China (English)

    麦范金; 李东普; 岳晓光

    2011-01-01

    Bi-direction marching method is a traditional algorithm, which can find ambiguity but can not solve the ambiguity problem. In order to find a better solution, this paper proposes a combination method based on bidirection marching method and feature selection algorithm. Through the accumulation of corpus, a Chinese word segmentation system is designed. Experimental results show that the new Chinese word segmentation method is better than traditional methods.%传统的双向匹配算法虽然能够发现歧义现象,但是却不能解决歧义问题.为了更好地进行歧义消解,提出了一种基于双向匹配法和特征选择算法的中文分词技术,通过积累的语料库,设计并实现了一个基于两种方法的分词系统.该系统的实验结果表明,基于双向匹配法和特征选择算法的中文分词技术比传统方法的效果要好.

  15. 基于 C4.5算法的民航客户价值细分研究%Customer Value Segmentation Based on C4 .5 Algorithm in Aviation Market

    Institute of Scientific and Technical Information of China (English)

    张劲松; 江波

    2014-01-01

    With the development of the air-passenger transport market ,customer segmentation plays an in-creasingly important role in the marketing of airlines .In view of the airport passenger behavior data ,this paper uses C4 .5 decision tree of data mining for market segmentation and obtains the decision tree of cus-tomer value .In addition ,it also analyzes the characteristics of value customers for airlines based on the e-valuation to classification results of decision tree .At last ,this paper contrastively analyzes the frequently used classification algorithm with C4 .5 and indicates that C4 .5 algorithm can produce the excellent effect in airline customer value segmentation .%随着民航旅客运输的发展,客户细分在航空公司市场营销中发挥着越来越重要的作用。针对调研的机场候机旅客行为数据,采用数据挖掘中的决策树C4.5算法对民航客户进行价值细分。在生成的旅客价值细分决策树的基础上,对决策树分类结果进行了评价,并分析了航空公司价值旅客的主要特征。通过与常用的数据分类算法的综合对比分析,表明C4.5算法在民航客户价值细分中具有相对良好的分类效果。

  16. Cerebellar anatomy as applied to cerebellar microsurgical resections

    Directory of Open Access Journals (Sweden)

    Alejandro Ramos

    2012-06-01

    Full Text Available OBJECTIVE: To define the anatomy of dentate nucleus and cerebellar peduncles, demonstrating the surgical application of anatomic landmarks in cerebellar resections. METHODS: Twenty cerebellar hemispheres were studied. RESULTS: The majority of dentate nucleus and cerebellar peduncles had demonstrated constant relationship to other cerebellar structures, which provided landmarks for surgical approaching. The lateral border is separated from the midline by 19.5 mm in both hemispheres. The posterior border of the cortex is separated 23.3 mm from the posterior segment of the dentate nucleus; the lateral one is separated 26 mm from the lateral border of the nucleus; and the posterior segment of the dentate nucleus is separated 25.4 mm from the posterolateral angle formed by the junction of lateral and posterior borders of cerebellar hemisphere. CONCLUSIONS: Microsurgical anatomy has provided important landmarks that could be applied to cerebellar surgical resections.

  17. Image segmentation algorithm combined PCNN with maximal correlative criterion%PCNN和最大相关准则相结合的图像分割方法

    Institute of Scientific and Technical Information of China (English)

    邓成锦; 聂仁灿; 周冬明; 赵东风

    2011-01-01

    脉冲耦合神经网络(PCNN)是有着生物学背景的新一代人工神经网络,在图像分割方面体现了优异的性能.PCNN模型在参数估计和阈值迭代方面的问题还有待解决.将一维最大相关准则和二维最大相关准则相结合来估计神经元参数,实现了图像分割的自动化并降低了运算的复杂性.仿真结果表明,该方法在分割图效果和运算复杂度方面都得到了提高,具有较好的实用性.%Pulse Coupled Neural Network(PCNN) is a new generation which has a biological background of artificial neural network, reflects excellent performance in the image segmentation. But the problems of PCNN model parameter estimation and threshold iteration are not been resolved. This paper combines one dimension maximal correlative criterion and two dimension maximal correlative criterion to estimate the neuron parameters,achieves the automation of image segmentation and reduces the complexity of computing. Simulation results show that the proposed method results in the segmentation map and computational complexity compared with the related literature have been improved,and has better usability.

  18. Who Is Repeating Anatomy? Trends in an Undergraduate Anatomy Course

    Science.gov (United States)

    Schutte, Audra F.

    2016-01-01

    Anatomy courses frequently serve as prerequisites or requirements for health sciences programs. Due to the challenging nature of anatomy, each semester there are students remediating the course (enrolled in the course for a second time), attempting to earn a grade competitive for admissions into a program of study. In this retrospective study,…

  19. 基于NSCT-Gabor特征和脉冲耦合神经网络的 SAR图像分割%A Segmentation Algorithm for SAR Images Based on NSCT-Gabor Characteristics and PCNN

    Institute of Scientific and Technical Information of China (English)

    吴俊政; 严卫东; 倪维平; 边辉; 张晗

    2015-01-01

    针对SAR图像目标的精确分割问题,利用非下采样轮廓波变换( NSCT )和Gabor滤波器分别提取图像特征,然后采用脉冲耦合神经网络( PCNN)对目标区域进行增强,提出了一种分割算法。分别对图像进行NSCT分解和Ga-bor滤波,对NSCT域的高、低频子带系数构造一个特征图,对Gabor滤波的不同尺度构造对应的特征图,对所获取的各个特征图用PCNN进行目标增强,最后对增强的特征图进行合理合并与分割。利用MSTAR SAR数据库中各种干扰强度下的图像进行了实验,结果表明,相比于模糊C均值、马尔可夫随机场等常见的分割算法,所提出的算法分割结果更为准确,同时受噪声干扰更小。%A segmentation algorithm was proposed by using Nonsubsampled Contourlet Transform ( NSCT ) and Gabor filter to extract characteristics of images respectively and using Pulse Coupled Neural Networks (PCNN) to enhance the target areas.Characteristic figures were constructed for the high and low frequencies of NSCT and corresponding characteristic figures were also constructed for the Gabor filters .All the characteristic figures were enhanced by PCNN .Then,the enhanced figures were integrated and segmented reasonably .Images in MSTAR SAR data library under different jamming intensities were selected for experiment .The results indicated that:Compared with the common algorithms such as FCM and the algorithm based on Markov random field,the proposed algorithm can realize more accurate segmentation for SAR images and has strong immunity from interferences .

  20. [Pandora's box of anatomy].

    Science.gov (United States)

    Weinberg, Uri; Reis, Shmuel

    2008-05-01

    Physicians in Nazi Germany were among the first to join the Nazi party and the SS, and were considered passionate and active supporters of the regime. Their actions included development and implementation of the racial theory thus legitimizing the development of the Nazi genocide plan, leadership and execution of the sterilization and euthanasia programs as well as atrocious human experimentation. Nazi law allowed the use of humans and their remains in research institutions. One of the physicians whose involvement in the Nazi regime was particularly significant was Eduard Pernkopf. He was the head of the Anatomy Institute at the University of Vienna, and later became the president of the university. Pernkopf was a member of the Nazi party, promoted the idea of "racial hygiene", and in 1938, "purified" the university from all Jews. In Pernkopfs atlas of anatomy, the illustrators expressed their sympathy to Nazism by adding Nazi symbols to their illustrations. In light of the demand stated by the "Yad Vashem" Institute, the sources of the atlas were investigated. The report, which was published in 1998, determined that Pernkopfs Anatomy Institute received almost 1400 corpses from the Gestapo's execution chambers. Copies of Pernkopfs atlas, accidentally exposed at the Rappaport School of Medicine in the Technion, led to dilemmas concerning similar works with a common background. The books initiated a wide debate in Israel and abroad, regarding ethical aspects of using information originated in Nazi crimes. Moreover, these findings are evidence of the evil to which science and medicine can give rise, when they are captured as an unshakable authority. PMID:18770971

  1. Segmentation of complex document

    Directory of Open Access Journals (Sweden)

    Souad Oudjemia

    2014-06-01

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

  2. 移动商务中面向客户细分的KSP混合聚类算法%KSP: A Hybrid Clustering Algorithm for Customer Segmentation in Mobile E-commerce

    Institute of Scientific and Technical Information of China (English)

    邓晓懿; 金淳; 樋口良之; 韩庆平

    2011-01-01

    数据挖掘技术中的聚类算法是解决客户细分问题的重要算法之一.为解决传统聚类算法在客户细分问题中分类精度较低、收敛速度较慢的问题,着重对比分析传统聚类算法中K- means、自组织映射网络和粒子群3种算法的不足,提出融合3种算法优点的混合型聚类算法,该算法利用K- means和自组织映射网络对初始聚类中心进行优化,结合粒子群优化和K-means优化聚类迭代过程,并在迭代优化过程中设计避免算法因早熟而停滞的机制.针对移动电子商务环境下的餐饮业客户细分问题,建立移动餐饮业客户细分模型,并利用混合型聚类算法、K - means、层级自组织映射网络和基于粒子群的K- means等4种算法对实际案例进行对比分析.研究结果表明,混合型聚类算法的聚类精度分别比其他3种算法高,同时还具有最快的收敛性能,更适用于客户细分问题.%Clustering algorithms in data mining technology is an important kind of algorithms of soloving customer segmentation problems. To overcome the low accuracy and slow convergence of traditional clustering algorithms in customer segmentation, this paper analyzes deficiencies of traditional cluster algorithms, K-means, SOM and PSO. After that, an improved hybrid clustering algorithm named KSP is proposed, which integrates advantages of K-means, SOM and PSO. The initialization of KSP is optimized by K-means and SOM; the solving process is carried out by the combination of PSO and K-means with a mechanism of restraining premature stagnancy. Then, a customer segmentation model was established to analyze types of customers in catering industry under mobile electronic commerce environment. Also, an actual case was illustrated to verify the efficiency of the KSP algorithm. The results show that the KSP has the highest accuracy and convergence rate. Thus, it is more suitable for customer segmentation.

  3. Normal cranial CT anatomy

    International Nuclear Information System (INIS)

    The human brain consists of well-known anatomical components. Some parts of these components have been shown to be concerned with certain functions. A complete cranial CT examination consists of a series of several slices obtained in a sequence usually from the base to the vertex of the cranial vault, in the axial mode. The ultimate goal of this chapter is to pinpoint those slices that depict a given anatomical structure or several structures that deal with a given function. To achieve this goal, the discussion of CT cranial anatomy is presented in three sections

  4. TEACHING ANATOMY TO UNDERGRADUATE STUDENTS

    Directory of Open Access Journals (Sweden)

    Sharadkumar Pralhad Sawant,

    2015-09-01

    Full Text Available Introduction: Anatomy is the base of medical science in India and is taught practically to all disciplines of undergraduate health sciences in the first year. It is an acknowledged fact that a basic knowledge of Anatomy is a prerequisite to learn any other branch of medicine. All medical professionals must have a basic knowledge of Anatomy so as to ensure safe medical practice. Traditionally Anatomy teaching consists of didactic lectures as well as dissections or prosections as per the requirement of the course. Lecture is defined as an oral discourse on a given subject before an audience for purpose of instruction and leaning. In the traditional method lectures were taken via chalk & board, but nowadays power point presentations are increasingly being used. To make Anatomy learning both pleasant and motivating, new methods of teaching gross anatomy are being assessed as medical colleges endeavour to find time in their curricula for new content without fore-going fundamental anatomical knowledge. This paper examines the other teaching methodologies for teaching gross anatomy. Conclusion: Proper utilization of newer technologies along with the traditional teaching methods will certainly lead to enhanced understanding of gross anatomy and will ultimately improve students’ performance.

  5. 基于图像片马尔科夫随机场的脑MR图像分割算法%Brain MR Image Segmentation Algorithm Based on Markov Random Field with Image Patch

    Institute of Scientific and Technical Information of China (English)

    宋艳涛; 纪则轩; 孙权森

    2014-01-01

    传统的高斯混合模型(Gaussian mixture model, GMM)算法在图像分割中未考虑像素的空间信息,导致其对于噪声十分敏感。马尔科夫随机场(Markov random field, MRF)模型通过像素类别标记的Gibbs 分布先验概率引入了图像的空间信息,能较好地分割含有噪声的图像,然而MRF 模型的分割结果容易出现过平滑现象。为了解决上述缺陷,提出了一种新的基于图像片权重方法的马尔科夫随机场图像分割模型,对邻域内的不同图像片根据相似度赋予不同的权重,使其在克服噪声影响的同时能保持图像细节信息。同时,采用KL 距离引入先验概率与后验概率关于熵的惩罚项,并对该惩罚项进行平滑,得到最终的分割结果。实验结果表明,算法具有较强的自适应性,能够有效克服噪声对于分割结果的影响,并获得较高的分割精度。%Without considering the spatial information between pixels, the traditional Gaussian mixture model (GMM) algorithm is very sensitive to noise during image segmentation. Markov random field (MRF) models provide a powerful way to noisy images through Gibbs joint probability distribution which introduce the spatial information of images. However, they often lead to over-smoothing. To overcome these drawbacks, we propose a new brain MR image segmentation algorithm based on MRF with image patch by assigning each pixel in the neighborhood with a different weight according to the similarity between image patches. The proposed method can overcome the noise and keep the details of topology and corner regions. Meanwhile, by introducing the KL distance into the prior probability and posterior probability as an entropy penalty, the proposed algorithm could get better segmentation results through smoothing this penalty term. Experimental results show that our algorithm can overcome the impact of noise on the segmentation results adaptively and efficiently, and get accurate segmentation

  6. A Segmentation Algorithm Combined with Non-local Information and Graph Cut%结合非局部信息与图割的图像分割算法

    Institute of Scientific and Technical Information of China (English)

    王涛; 纪则轩; 孙权森

    2015-01-01

    The interactive image segmentation algorithm based on graph cut segments a foreground object from its background, which has drawn great interest in image processing and computer vision. In order to further improve the accuracy of the segmentation, this paper presents an interactive segmentation algo-rithm by introducing the non-local information into graph cut framework. To model the non-local informa-tion of the image, we set a fixed-size search window for each pixel, and hence each pixel only needs to con-sider the relationships with the pixels in the search window. Instead of using intensity of each pixel, the im-age patches are utilized to compute the similarity between pixels when considering the similarities between non-local pixels. By introducing the non-local information into the graph cut framework, a new energy term combining the local and non-local information is constructed by merging the local and non-local information in the boundary term of the conventional energy function. A new set of non-local edges is added in the graph to represent the non-local information of the image. The segmentation results can be obtained by solving the mincut/maxflow algorithm. Finally, the experimental results demonstrate the effectiveness and feasibility of the proposed algorithm.%基于图割的交互式图像分割方法从图像背景中分离出前景目标,在图像处理和计算机视觉领域引起了广泛的关注。为了进一步提高分割精度,提出一种结合图像非局部信息和图割的交互式图像分割算法。在建模图像非局部信息时为每个像素点设置一个固定大小的搜索窗口,每个像素点只需考虑与搜索窗口内像素之间的关系;计算非局部像素对之间相似性时采用图像片替代像素,通过图像片之间的相似性替代像素之间的相似性,以表征图像的非局部信息;将图像非局部信息引入到图割框架中,在传统能量函数的边界项将图像的

  7. Towards Perceptually Driven Segmentation Evaluation Metrics

    OpenAIRE

    Drelie Gelasca, E.; Ebrahimi, T.; Farias, M; Carli, M; Mitra, S.

    2004-01-01

    To be reliable, an automatic segmentation evaluation metric has to be validated by subjective tests. In this paper, a formal protocol for subjective tests for segmentation quality assessment is presented. The most common artifacts produced by segmentation algorithms are identified and an extensive analysis of their effects on the perceived quality is performed. A psychophysical experiment was performed to assess the quality of video with segmentation errors. The results show how an objective ...

  8. Statistical Validation of Image Segmentation Quality Based on a Spatial Overlap Index1

    Science.gov (United States)

    Zou, Kelly H.; Warfield, Simon K.; Bharatha, Aditya; Tempany, Clare M.C.; Kaus, Michael R.; Haker, Steven J.; Wells, William M.; Jolesz, Ferenc A.; Kikinis, Ron

    2005-01-01

    Rationale and Objectives To examine a statistical validation method based on the spatial overlap between two sets of segmentations of the same anatomy. Materials and Methods The Dice similarity coefficient (DSC) was used as a statistical validation metric to evaluate the performance of both the reproducibility of manual segmentations and the spatial overlap accuracy of automated probabilistic fractional segmentation of MR images, illustrated on two clinical examples. Example 1: 10 consecutive cases of prostate brachytherapy patients underwent both preoperative 1.5T and intraoperative 0.5T MR imaging. For each case, 5 repeated manual segmentations of the prostate peripheral zone were performed separately on preoperative and on intraoperative images. Example 2: A semi-automated probabilistic fractional segmentation algorithm was applied to MR imaging of 9 cases with 3 types of brain tumors. DSC values were computed and logit-transformed values were compared in the mean with the analysis of variance (ANOVA). Results Example 1: The mean DSCs of 0.883 (range, 0.876–0.893) with 1.5T preoperative MRI and 0.838 (range, 0.819–0.852) with 0.5T intraoperative MRI (P < .001) were within and at the margin of the range of good reproducibility, respectively. Example 2: Wide ranges of DSC were observed in brain tumor segmentations: Meningiomas (0.519–0.893), astrocytomas (0.487–0.972), and other mixed gliomas (0.490–0.899). Conclusion The DSC value is a simple and useful summary measure of spatial overlap, which can be applied to studies of reproducibility and accuracy in image segmentation. We observed generally satisfactory but variable validation results in two clinical applications. This metric may be adapted for similar validation tasks. PMID:14974593

  9. MARKET SEGMENTATION

    OpenAIRE

    Munaga Ramakrishna Mohan Rao

    2015-01-01

    Market segmentation is a marketing strategy that involves dividing a broad target market into subsets of consumers, businesses, or countries who have common needs and priorities, and then designing and implementing strategies to target them. Market segmentation strategies may be used to identify the target customers, and provide supporting data for positioning to achieve a marketing plan objective. Businesses may develop product differentiation strategies, or an undifferentiated approach, inv...

  10. Segmenting anatomy in chest x-rays for tuberculosis screening.

    Science.gov (United States)

    Karargyris, Alexandros; Antani, Sameer; Thoma, George

    2011-01-01

    In this paper we describe the development of a screening system for pulmonary pathologies (i.e. pneumonia, tuberculosis) application in global healthcare settings. As a first step toward this goal, the paper presents a novel approach for detecting lungs and ribs in chest radiographs. The approach is a unified method combining two detection schemes resulting in reduced cost. The novelty of our approach lies on the fact that instead of using pixel-wise techniques exclusively we used region-based features computed as wavelet features that take into consideration the orientation of anatomic structures. Initial results are described. Next steps include classification of non-rib lung regions for radiographic patterns suggesting tuberculosis infection. PMID:22256142

  11. PERFORMANCE ANALYSIS OF CLUSTERING BASED IMAGE SEGMENTATION AND OPTIMIZATION METHODS

    Directory of Open Access Journals (Sweden)

    Jaskirat kaur

    2012-05-01

    Full Text Available Partitioning of an image into several constituent components is called image segmentation. Myriad algorithms using different methods have been proposed for image segmentation. Many clustering algorithms and optimization techniques are also being used for segmentation of images. A major challenge in segmentation evaluation comes from the fundamental conflict between generality and objectivity. As there is a glut of image segmentation techniques available today, customer who is the real user of these techniques may get obfuscated. In this paper to address the above described problem some image segmentation techniques are evaluated based on their consistency in different applications. Based on the parameters used quantification of different clustering algorithms is done.

  12. Segmentation of Indus Texts: A Dynamic Programming Approach.

    Science.gov (United States)

    Siromoney, Gift; Huq, Abdul

    1988-01-01

    Demonstrates how a dynamic programing algorithm can be developed to segment unusually long written inscriptions from the Indus Valley Civilization. Explains the problem of segmentation, discusses the dynamic programing algorithm used, and includes tables which illustrate the segmentation of the inscriptions. (GEA)

  13. Bayesian segmentation of hyperspectral images

    CERN Document Server

    Mohammadpour, Adel; Mohammad-Djafari, Ali

    2007-01-01

    In this paper we consider the problem of joint segmentation of hyperspectral images in the Bayesian framework. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently with common hidden classification label variables which is modeled by a Potts Markov Random Field. We introduce an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results.

  14. Bayesian segmentation of hyperspectral images

    Science.gov (United States)

    Mohammadpour, Adel; Féron, Olivier; Mohammad-Djafari, Ali

    2004-11-01

    In this paper we consider the problem of joint segmentation of hyperspectral images in the Bayesian framework. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently with common hidden classification label variables which is modeled by a Potts Markov Random Field. We introduce an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results.

  15. Research of Parallel Algorithm for Image Segmentation Under Multi-core Environment%多核环境下的图像分割并行算法研究

    Institute of Scientific and Technical Information of China (English)

    刘张桥; 王成良; 焦晓军

    2011-01-01

    对多核环境下的图像分割并行算法进行研究,在基于正交小波分解的多分辨率图像锥中引入模糊C-均值(FCM)算法,采用OpenMP语言设计P-FCM多核并行模型,并给出该模型的算法实现步骤.在对初始图像数据预处理时,采用矩形块数据分割法进行图像分块,将分块后的子图像数据作为并行运算时的输入数据由主线程分给不同的处理器.实验结果表明,在处理较大图像时,该算法效率较高.%This paper studies the parallel algorithm for image segmentation under multi-core environment. It combines the multiresolution image pyramid based on the orthogonal wavelet decomposition with the Fuzzy C-means(FCM) clustering algorithm, and achieves the multi-processor and multi-threaded parallel model of P-FCM with the parallel language of OpenMP. It gives the algorithm implementation of the model. For the original image data preprocessing, the parallel method of rectangular block is used to divide the original image data into sub-rectangular data blocks, which will be used as the input data and assigned to different processor by the mater thread for the parallel computing. Experimental results show that, in dealing with the large size images, this algorithm has high efficiency.

  16. Image segmentation approach based on cuckoo search algorithm and 2-D Fisher criterion%基于杜鹃搜索和二维Fisher准则的图像分割方法

    Institute of Scientific and Technical Information of China (English)

    叶志伟; 王明威; 刘伟; 尹宇洁

    2016-01-01

    Thresholding method is one of the most common methods for image segmentation, however thresholding methods based on 1 -D histogram are easily ruined by the noise. Thresholding based on 2 -D histogram and Fisher criterion function can overcome the shortcoming of 1-D threshold method, which has the better segmentation performance. But due to huge computation is required for 2-D Fisher criterion function its speed is very slow. Commonly used optimization methods to speed up thresholding based on 2-D Fisher criterion function like particle swarm optimization and genetic algorithm are easily to fall into the local optimum. Cuckoo search is a newly proposed meta-heuristic optimization algorithm; testing results on some benchmarks indicate that cuckoo search has better global convergence ability than particle swarm optimization and genetic algorithm. In this paper, by employing cuckoo search algorithm, a segmentation approach was proposed based on 2 -D Fisher criterion function. The experimental results show that the proposed method decreases the seeking time of optimal threshold with the basic 2 -D Fisher criterion based thresholding method, which is a well performing method and is more suitable for real-time image segmentation.%阈值法是图像分割最为常用的方法之一,然而基于一维直方图的阈值方法分割结果容易受噪声的影响.基于二维直方图的二维Fisher准则能够克服一维阈值法缺陷,具有较好的分割性能.但是二维Fisher准则阈值法在求取最优阈值时需要大量的计算,运算速度非常慢.常用的二维Fisher准则阈值优化计算方法如粒子群算法和遗传算法容易陷入局部最优.杜鹃搜索算法是新近提出的一种元启发优化算法,一些经典的函数优化问题测试结果表明杜鹃搜索算法全局寻优能力优于粒子群算法和遗传算法.在介绍杜鹃搜索算法的基础上,提出一种基于杜鹃搜索算法改进的二维Fisher准则阈值分割方法.

  17. [Surgery without anatomy?].

    Science.gov (United States)

    Stelzner, F

    2016-08-01

    Anatomy is the basis of all operative medicine. While this branch of scientific medicine is frequently not explicitly mentioned in surgical publications, it is nonetheless quintessential to medical education. In the era of video sequences and digitized images, surgical methods are frequently communicated in the form of cinematic documentation of surgical procedures; however, this occurs without the help of explanatory drawings or subtexts that would illustrate the underlying anatomical nomenclature, comment on fine functionally important details or even without making any mention of the surgeon. In scientific manuscripts color illustrations frequently appear in such overwhelming quantities that they resemble long arrays of trophies but fail to give detailed explanations that would aid the therapeutic translation of the novel datasets. In a similar fashion, many anatomy textbooks prefer to place emphasis on illustrations and photographs while supplying only a paucity of explanations that would foster the understanding of functional contexts and thus confuse students and practitioners alike. There is great temptation to repeat existing data and facts over and over again, while it is proportionally rare to make reference to truly original scientific discoveries. A number of examples are given in this article to illustrate how discoveries that were made even a long time ago can still contribute to scientific progress in current times. This includes the NO signaling molecules, which were first described in 1775 but were only discovered to have a pivotal role as neurotransmitters in the function of human paradoxical sphincter muscles in 2012 and 2015. Readers of scientific manuscripts often long for explanations by the numerous silent coauthors of a publication who could contribute to the main topic by adding in-depth illustrations (e. g. malignograms, evolution and involution of lymph node structures). PMID:27251482

  18. VISUALIZATION OF REGISTERED SUBSURFACE ANATOMY

    DEFF Research Database (Denmark)

    2010-01-01

    A system and method for visualization of subsurface anatomy includes obtaining a first image from a first camera and a second image from a second camera or a second channel of the first camera, where the first and second images contain shared anatomical structures. The second camera and the second...... channel of the first camera are capable of imaging anatomy beneath the surface in ultra-violet, visual, or infra-red spectrum. A data processor is configured for computing registration of the first image to the second image to provide visualization of subsurface anatomy during surgical procedures...

  19. The anatomy of teaching and the teaching of anatomy.

    Science.gov (United States)

    Peck, David; Skandalakis, John E

    2004-04-01

    Professional education is one of the greatest problems currently confronting the healing professions. The incorporation of basic science departments into colleges of medicine has affected curriculum design, research, admissions criteria, and licensure. Those who are not practicing members of a particular health care profession wield undue influence in medical schools. Ideally, gross anatomy teachers should be health care professionals who use anatomy in their practices. Reorganization of medical education will heal the rift between research and clinical medicine.

  20. 递推人工蜂群的模糊划分熵多阈值分割算法%A Fuzzy Partition Entropy Approach for Multi-Thresholding Segmentation Based on the Recursive Artificial Bee Colony Algorithm

    Institute of Scientific and Technical Information of China (English)

    尹诗白; 赵祥模; 王卫星; 王一斌

    2012-01-01

    针对图像分割中模糊划分熵算法在多阈值选取时存在的效率低、计算重复的问题,提出了一种递推人工蜂群的模糊划分熵多阈值分割算法(RAFPEA).首先选择附加边界条件及灰度权重的隶属函数来构建图像的模糊熵模型,并将该模型中不同变量的组合计算转化为递推过程,进而保存此过程中不重复的瞬间递推值,然后引入人工蜂群算法,利用预存的递推结果来计算蜂群寻优时的个体适应度值,从而减少重复计算,达到快速寻优的目的.实验结果表明:RAFPEA的均一度与精确的穷举模糊划分熵法相同,但运行时间仅为穷举、遗传的模糊划分熵算法的5%;随着阈值数量的增加,运行时间稳定不变,在确保精度的前提下,可高效地对图像进行多阈值分割.%A new recursive artificial bee colony fuzzy partition entropy algorithm (RAFPEA) for multi-thresholding image segmentation is proposed to solve the inefficiency and repeated computation in fuzzy partition entropy approach for selecting the thresholds in the process of image segmentation. The membership functions with attached boundary conditions and gray weights are selected to build the image fuzzy entropy model. The combined computation of different variables in this model is converted to the recursive process and the no-repetitive results of the processing moments are stored. Then the artificial bee colony algorithm (ABCA) uses the stored results to calculate the fitness value of individual species in the ABCA so that the repeated calculations can be reduced and the optimal thresholds can be searched effectively. Experimental results and comparisons with common algorithms indicate that the run time accounts for 5% of ones of the fuzzy partition entropy approaches based on exhaustive algorithm and genetic algorithm. And the uniformity obtained by the proposed scheme is equivalent to the one via exhaustive search. Moreover, as the number of

  1. Template characterization and correlation algorithm created from segmentation for the iris biometric authentication based on analysis of textures implemented on a FPGA

    International Nuclear Information System (INIS)

    Among the most used biometric signals to set personal security permissions, taker increasingly importance biometric iris recognition based on their textures and images of blood vessels due to the rich in these two unique characteristics that are unique to each individual. This paper presents an implementation of an algorithm characterization and correlation of templates created for biometric authentication based on iris texture analysis programmed on a FPGA (Field Programmable Gate Array), authentication is based on processes like characterization methods based on frequency analysis of the sample, and frequency correlation to obtain the expected results of authentication.

  2. Microsurgical anatomy of the posterior circulation

    Directory of Open Access Journals (Sweden)

    Pai Balaji

    2007-01-01

    Full Text Available Context: The microsurgical anatomy of the posterior circulation is very complex and variable. Surgical approaches to this area are considered risky due to the presence of the various important blood vessels and neural structures. Aims: To document the microsurgical anatomy of the posterior circulation along with variations in the Indian population. Materials and Methods: The authors studied 25 cadaveric brain specimens. Microsurgical dissection was carried out from the vertebral arteries to the basilar artery and its branches, the basilar artery bifurcation, posterior cerebral artery and its various branches. Measurements of the outer diameters of the vertebral artery, basilar artery and posterior cerebral artery and their lengths were taken. Results: The mean diameter of the vertebral artery was 3.4 mm on the left and 2.9 mm on the right. The diameter of the basilar artery varied from 3-7 mm (mean of 4.3 mm. The length varied from 24-35 mm (mean of 24.9 mm. The basilar artery gave off paramedian and circumferential perforating arteries. The origin of the anterior inferior cerebellar artery (AICA varied from 0-21 mm (mean 10.0 mm from the vertebrobasilar junction. The diameter of the AICA varied from being hypoplastic i.e., < 0.5 mm to 2 mm (mean 1.0 mm. The superior cerebellar artery (SCA arises very close to the basilar bifurcation, in our series (1-3 mm from the basilar artery bifurcation. The diameter of the SCA varied from 0.5-2.5 mm on both sides. The posterior cerebral artery (PCA is divided into four segments. The PCA gave rise to perforators (thalamoperforators, thalamogeniculate arteries, circumflex arteries and peduncular arteries, medial posterior choroidal artery, lateral posterior choroidal artery and cortical branches. In 39 specimens the P1 segment was found to be larger than the posterior communicating artery, in six specimens it was found to be equal to the diameter of the posterior communicating artery and in five specimens it

  3. OLFACTION: ANATOMY, PHYSIOLOGY AND BEHAVIOR

    Science.gov (United States)

    The anatomy, physiology and function of the olfactory system are reviewed, as are the normal effects of olfactory stimulation. It is speculated that olfaction may have important but unobtrusive effects on human behavior.

  4. Anatomie et identification des bois

    OpenAIRE

    Jourez, Benoît

    2010-01-01

    Anatomie des bois Structure anatomique des résineux et des feuillus Structure de la membrane cellulaire structure submicroscopique Anatomie du bois des essences feuillues tropicales Caractères anatomiques servant à l'identification des essences Reconnaissance microscopique du bois des essences résineuses et feuillues Duramen et duraminisation Formations anormales ( bois de compression et bois de tension) Chimie du bois Composition générale Cellulose, hé...

  5. Spatial positioning fuzzy C- means algorithm in segmentation of range-gated image%距离选通激光成像空间定位模糊C均值聚类分割法

    Institute of Scientific and Technical Information of China (English)

    曹忆南; 王新伟; 周燕

    2013-01-01

    针对距离选通激光成像对比度低、照度不均、图像模糊的特点,提出了一种基于空间定位的模糊C均值聚类方法( SPFCM )对目标进行分割。传统的模糊C均值聚类法存在以下缺点:一是需要预先获得目标分类数量,自适应性较差;二是对空间信息不敏感,导致目标轮廓不完整以及错误分类。针对上述缺陷,文中对传统算法进行了改进,引入了初定位的概念,首先利用最大类间方差法(Otsu法)和数学形态学工具对子目标进行初步定位,再将其形心方位信息和灰度信息融合到聚类过程中,以较短的迭代过程实现不同目标的归类。实验结果证明基于空间定位的模糊C均值聚类法可以完整、有效地对距离选通激光图像进行提取分割,处理时间优于传统FCM。%A fuzzy C- means algorithm based on spatia l positioning was proposed to do the segmentation for range-gated image, which had the feature of low contrast, uneven illumination, and blurring. Object extraction is essential in image processing, providing the basic and necessary information for other methods. Traditional FCM algorithm needs the number of classes to cluster the data, which limits its adaptability. It also lacks in sensitivity of spatial information, resulting in misclassification as well as incomplete extraction of objects. For the above defects, the traditional algorithm was improved by pre-positioning. Firstly, median filter, Otsu method, and mathematical morphology method were applied to do the initial segmentation, obtaining the centroid and grayscale information of all targets, which took very short time. Then both of the centroid and grayscale information were used in clustering process, accomplishing the classification with fewer iterations and less time consuming than traditional FCM. Experiments indicate that the the Spatial Positioning FCM (SPFCM) is effective in segmentation of range-gated image, the

  6. Modified algorithm of bit-plane complexity segmentation steganography based on preprocessing%基于预处理的位平面复杂度分割隐写改进算法

    Institute of Scientific and Technical Information of China (English)

    刘虎; 袁海东

    2012-01-01

    Since Bit-Plane Complexity Segmentation ( BPCS) steganography is vulnerable to complex histogram attack, this paper proposed an improved algorithm based on preprocessing. The steganography derived compensatory rule from distribution of the cover image. Then it used reversed preprocessing in compensation to the change of complexity caused by embedded information. The experimental results show that the proposed algorithm can properly hide information and counteract the attack of complex histogram. The compensation happens before information hiding, so it can maintain the big capacity characteristic of the original algorithm.%位平面复杂度分割(BPCS)隐写易受复杂度直方图攻击,为了弥补这一缺陷,提出了一种基于预处理的改进隐写算法.算法针对载密图像进行统计特征的量化分析,求导出逆向预处理的补偿规则,进而对嵌入信息引起的复杂度变化进行逆向的预处理补偿.实验结果表明,改进的算法在保证隐蔽性的同时具有很好的抗复杂度直方图攻击的能力,由于补偿过程是在隐藏秘密信息之前发生的,算法也较好地保持了BPCS大容量隐写的优点.

  7. Penile Embryology and Anatomy

    Directory of Open Access Journals (Sweden)

    Jenny H. Yiee

    2010-01-01

    Full Text Available Knowledge of penile embryology and anatomy is essential to any pediatric urologist in order to fully understand and treat congenital anomalies. Sex differentiation of the external genitalia occurs between the 7thand 17th weeks of gestation. The Y chromosome initiates male differentiation through the SRY gene, which triggers testicular development. Under the influence of androgens produced by the testes, external genitalia then develop into the penis and scrotum. Dorsal nerves supply penile skin sensation and lie within Buck's fascia. These nerves are notably absent at the 12 o'clock position. Perineal nerves supply skin sensation to the ventral shaft skin and frenulum. Cavernosal nerves lie within the corpora cavernosa and are responsible for sexual function. Paired cavernosal, dorsal, and bulbourethral arteries have extensive anastomotic connections. During erection, the cavernosal artery causes engorgement of the cavernosa, while the deep dorsal artery leads to glans enlargement. The majority of venous drainage occurs through a single, deep dorsal vein into which multiple emissary veins from the corpora and circumflex veins from the spongiosum drain. The corpora cavernosa and spongiosum are all made of spongy erectile tissue. Buck's fascia circumferentially envelops all three structures, splitting into two leaves ventrally at the spongiosum. The male urethra is composed of six parts: bladder neck, prostatic, membranous, bulbous, penile, and fossa navicularis. The urethra receives its blood supply from both proximal and distal directions.

  8. [Dental anatomy of dogs].

    Science.gov (United States)

    Sarkisian, E G

    2014-12-01

    The aim of the research was to investigate dog teeth anatomy as animal model for study of etiopathogenesis of caries disease and physiological tooth wear in human. After examining the dog's dental system, following conclusions were drawn: the dog has 42 permanent teeth, which are distributed over the dental arches not equally, and so the upper dentition consists of 20, and the lower of 22 teeth. The largest are considered upper fourth premolar and lower first molars, which are called discordant teeth. Between discordant teeth and fangs a dog has an open bite, which is limited to the top and bottom conical crown premolar teeth. Thus, in the closed position of the jaws, behind this occlusion is limited by discordant teeth, just in contact are smaller in size two molars. Only large dog's molars in a valid comparison can be likened to human molars, which allows us to use them in an analog comparison between them with further study of the morphological features ensure durability short-crown teeth and their predisposition to caries.

  9. Penile embryology and anatomy.

    Science.gov (United States)

    Yiee, Jenny H; Baskin, Laurence S

    2010-01-01

    Knowledge of penile embryology and anatomy is essential to any pediatric urologist in order to fully understand and treat congenital anomalies. Sex differentiation of the external genitalia occurs between the 7th and 17th weeks of gestation. The Y chromosome initiates male differentiation through the SRY gene, which triggers testicular development. Under the influence of androgens produced by the testes, external genitalia then develop into the penis and scrotum. Dorsal nerves supply penile skin sensation and lie within Buck's fascia. These nerves are notably absent at the 12 o'clock position. Perineal nerves supply skin sensation to the ventral shaft skin and frenulum. Cavernosal nerves lie within the corpora cavernosa and are responsible for sexual function. Paired cavernosal, dorsal, and bulbourethral arteries have extensive anastomotic connections. During erection, the cavernosal artery causes engorgement of the cavernosa, while the deep dorsal artery leads to glans enlargement. The majority of venous drainage occurs through a single, deep dorsal vein into which multiple emissary veins from the corpora and circumflex veins from the spongiosum drain. The corpora cavernosa and spongiosum are all made of spongy erectile tissue. Buck's fascia circumferentially envelops all three structures, splitting into two leaves ventrally at the spongiosum. The male urethra is composed of six parts: bladder neck, prostatic, membranous, bulbous, penile, and fossa navicularis. The urethra receives its blood supply from both proximal and distal directions. PMID:20602076

  10. Leveraging Colour Segmentation for Upper-Body Detection

    OpenAIRE

    Duffner, Stefan; Odobez, Jean-Marc

    2014-01-01

    This paper presents an upper-body detection algorithm that extends classical shape-based detectors through the use of additional semantic colour segmentation cues. More precisely, candidate upper-body image patches produced by a base detector are soft-segmented using a multi-class probabilistic colour segmentation algorithm that leverages spatial as well as colour prior distributions for different semantic object regions (skin, hair, clothing, background). These multi-class soft segmentation ...

  11. FISICO: Fast Image SegmentatIon COrrection

    Science.gov (United States)

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

    2016-01-01

    Background and Purpose In clinical diagnosis, medical image segmentation plays a key role in the analysis of pathological regions. Despite advances in automatic and semi-automatic segmentation techniques, time-effective correction tools are commonly needed to improve segmentation results. Therefore, these tools must provide faster corrections with a lower number of interactions, and a user-independent solution to reduce the time frame between image acquisition and diagnosis. Methods We present a new interactive method for correcting image segmentations. Our method provides 3D shape corrections through 2D interactions. This approach enables an intuitive and natural corrections of 3D segmentation results. The developed method has been implemented into a software tool and has been evaluated for the task of lumbar muscle and knee joint segmentations from MR images. Results Experimental results show that full segmentation corrections could be performed within an average correction time of 5.5±3.3 minutes and an average of 56.5±33.1 user interactions, while maintaining the quality of the final segmentation result within an average Dice coefficient of 0.92±0.02 for both anatomies. In addition, for users with different levels of expertise, our method yields a correction time and number of interaction decrease from 38±19.2 minutes to 6.4±4.3 minutes, and 339±157.1 to 67.7±39.6 interactions, respectively. PMID:27224061

  12. FISICO: Fast Image SegmentatIon COrrection.

    Directory of Open Access Journals (Sweden)

    Waldo Valenzuela

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

  13. Segmental neurofibromatosis

    OpenAIRE

    Yesudian Devakar; Krishnan S. G. S; Jayaraman M; Janaki V R; Yesudian Patrick

    2014-01-01

    Segmental neurofibromatosis or type V neurofibromatosis is a rare genodermatosis characterized by neurofibromas, café-au-lait spots and neurofibromas limited to a circumscribed body region. The disease may be associated with systemic involvement and malignancies. The disorder has not been reported yet in the Polish medical literature. A 63-year-old Caucasian woman presented with a 20-year history of multiple, flesh colored, dome-shaped, soft to firm nodules situated in the right lumbar region...

  14. 考虑展宽段的路段排队长度检测算法%Road Queue Length Detection Algorithm Considering Stretching Segment

    Institute of Scientific and Technical Information of China (English)

    杨雷; 吕鹏

    2012-01-01

    为了实时估计路段车辆排队长度,利用铺设在路段上的检测器,提出了一种车辆排队估计方法,对车辆排队进行实时跟踪.该方法考虑了一般的道路拓扑结构,路段排队的演化过程分为四个阶段:初始排队阶段、排队蔓延阶段、排队上溯阶段和堵塞路段阶段,不同阶段的排队利用不同的信息,通过不同的模型进行推算,通过实地调查验证,可以高效实时追踪路段排队的演化.%In order to estimate real-time queue length and provide information for traffic management, an algorithm was proposed. This method uses detector lay under road surface to track vehicle queue. General road topology was considered. Queue evolution was divided into four stages: initial queue stage, queue propagation stage, queue spillover stage, and fully congested stage. Different information was used to estimate queue length in different stages. The field test proves the effectiveness of the method.

  15. Efficient threshold for volumetric segmentation

    Science.gov (United States)

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

    2015-07-01

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

  16. Automatic Segmentation of Drosophila Neural Compartments Using GAL4 Expression Data Reveals Novel Visual Pathways.

    Science.gov (United States)

    Panser, Karin; Tirian, Laszlo; Schulze, Florian; Villalba, Santiago; Jefferis, Gregory S X E; Bühler, Katja; Straw, Andrew D

    2016-08-01

    Identifying distinct anatomical structures within the brain and developing genetic tools to target them are fundamental steps for understanding brain function. We hypothesize that enhancer expression patterns can be used to automatically identify functional units such as neuropils and fiber tracts. We used two recent, genome-scale Drosophila GAL4 libraries and associated confocal image datasets to segment large brain regions into smaller subvolumes. Our results (available at https://strawlab.org/braincode) support this hypothesis because regions with well-known anatomy, namely the antennal lobes and central complex, were automatically segmented into familiar compartments. The basis for the structural assignment is clustering of voxels based on patterns of enhancer expression. These initial clusters are agglomerated to make hierarchical predictions of structure. We applied the algorithm to central brain regions receiving input from the optic lobes. Based on the automated segmentation and manual validation, we can identify and provide promising driver lines for 11 previously identified and 14 novel types of visual projection neurons and their associated optic glomeruli. The same strategy can be used in other brain regions and likely other species, including vertebrates. PMID:27426516

  17. Multi-contrast submillimetric 3 Tesla hippocampal subfield segmentation protocol and dataset.

    Science.gov (United States)

    Kulaga-Yoskovitz, Jessie; Bernhardt, Boris C; Hong, Seok-Jun; Mansi, Tommaso; Liang, Kevin E; van der Kouwe, Andre J W; Smallwood, Jonathan; Bernasconi, Andrea; Bernasconi, Neda

    2015-01-01

    The hippocampus is composed of distinct anatomical subregions that participate in multiple cognitive processes and are differentially affected in prevalent neurological and psychiatric conditions. Advances in high-field MRI allow for the non-invasive identification of hippocampal substructure. These approaches, however, demand time-consuming manual segmentation that relies heavily on anatomical expertise. Here, we share manual labels and associated high-resolution MRI data (MNI-HISUB25; submillimetric T1- and T2-weighted images, detailed sequence information, and stereotaxic probabilistic anatomical maps) based on 25 healthy subjects. Data were acquired on a widely available 3 Tesla MRI system using a 32 phased-array head coil. The protocol divided the hippocampal formation into three subregions: subicular complex, merged Cornu Ammonis 1, 2 and 3 (CA1-3) subfields, and CA4-dentate gyrus (CA4-DG). Segmentation was guided by consistent intensity and morphology characteristics of the densely myelinated molecular layer together with few geometry-based boundaries flexible to overall mesiotemporal anatomy, and achieved excellent intra-/inter-rater reliability (Dice index ≥90/87%). The dataset can inform neuroimaging assessments of the mesiotemporal lobe and help to develop segmentation algorithms relevant for basic and clinical neurosciences. PMID:26594378

  18. Entangled decision forests and their application for semantic segmentation of CT images.

    Science.gov (United States)

    Montillo, Albert; Shotton, Jamie; Winn, John; Iglesias, Juan Eugenio; Metaxas, Dimitri; Criminisi, Antonio

    2011-01-01

    This work addresses the challenging problem of simultaneously segmenting multiple anatomical structures in highly varied CT scans. We propose the entangled decision forest (EDF) as a new discriminative classifier which augments the state of the art decision forest, resulting in higher prediction accuracy and shortened decision time. Our main contribution is two-fold. First, we propose entangling the binary tests applied at each tree node in the forest, such that the test result can depend on the result of tests applied earlier in the same tree and at image points offset from the voxel to be classified. This is demonstrated to improve accuracy and capture long-range semantic context. Second, during training, we propose injecting randomness in a guided way, in which node feature types and parameters are randomly drawn from a learned (nonuniform) distribution. This further improves classification accuracy. We assess our probabilistic anatomy segmentation technique using a labeled database of CT image volumes of 250 different patients from various scan protocols and scanner vendors. In each volume, 12 anatomical structures have been manually segmented. The database comprises highly varied body shapes and sizes, a wide array of pathologies, scan resolutions, and diverse contrast agents. Quantitative comparisons with state of the art algorithms demonstrate both superior test accuracy and computational efficiency. PMID:21761656

  19. 模糊分段光滑图像分割模型及其快速算法%Fuzzy piecewise smooth image segmentation model and a fast algorithm

    Institute of Scientific and Technical Information of China (English)

    赵在新; 成礼智

    2011-01-01

    灰度分布不均图像是图像分割中一个难点,为此提出一种模糊分段光滑(FPS)图像分割模型.借鉴分段光滑Mumford-Shah(MS)模型与模糊聚类思想,新模型通过两个定义在图像域的光滑函数描述区域特征,并利用模糊隶属度函数代替MS模型中的特征函数.同时,边界检测算子的引入能够有效保护图像中的边界信息.数值求解采用分裂Bregman方法与Gauss-Seidel迭代相结合的快速算法.对合成图像以及真实图像分割实验表明,本文算法能够有效分割灰度分布不均图像,同时具有较高的计算效率.%A fuzzy piecewise smooth (FPS) model is proposed aiming at the intensity- inhomogeneous image segmentation. Motivated by piecewise smooth Munford-Shah (MS) model and fuzzy clustering,two smooth functions were used to represent the region characteristics respectively and a fuzzy membership function was adopted to replace the hard membership function of MS model. An edge detection operator was also incorporated into the minimization ernergy function. The new energy is convex for the membership function,and the final segmentation does not depend on the initial contour. For numerical computation, a fast algorithm based on split Bregman method and Gauss-Seidel iteration was employed. Experimental results for synthetic and real images show desirable performance of the proposed method.

  20. Segmentation of sows in farrowing pens

    DEFF Research Database (Denmark)

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

    2014-01-01

    and illumination changes as well as motionless foreground objects. About 97% of the segmented binary images in the validation data sets can be used to track sow behaviours, such as position, orientation and movement. The experimental results demonstrate that the proposed algorithm is able to provide a basis......The correct segmentation of a foreground object in video recordings is an important task for many surveillance systems. The development of an effective and practical algorithm to segment sows in grayscale video recordings captured under commercial production conditions is described....... The segmentation algorithm combines a modified adaptive Gaussian mixture model for background subtraction with the boundaries of foreground objects, which is obtained by using dyadic wavelet transform. This algorithm can accurately extract the shapes of a sow under complex environments, such as dynamic background...

  1. Unsupervised Multiresolution Image Segmentation Integrating Color and Texture

    Institute of Scientific and Technical Information of China (English)

    XINGQiang; YUANBaozong; TANGXiaofang

    2004-01-01

    Unsupervised segmentation of images is highly useful in various applications including contentbased image retrieval. A novel multiresolution image segmentation algorithm, designed to separate a focused object of interest from background automatically, is described in this paper. According to the principle of human vision system, our algorithm first searches the salient block representing object in global image domain. Then all image blocks are clustered using the feature of color moments and texture in salient block. At last the algorithm classifies the image blocks belonging to object class in high resolution. Experiment shows that our algorithm achieves better segmentation results at higher speed compared with the traditional image segmentation approach using global optimization.

  2. An anatomy precourse enhances student learning in veterinary anatomy.

    Science.gov (United States)

    McNulty, Margaret A; Stevens-Sparks, Cathryn; Taboada, Joseph; Daniel, Annie; Lazarus, Michelle D

    2016-07-01

    Veterinary anatomy is often a source of trepidation for many students. Currently professional veterinary programs, similar to medical curricula, within the United States have no admission requirements for anatomy as a prerequisite course. The purpose of the current study was to evaluate the impact of a week-long precourse in veterinary anatomy on both objective student performance and subjective student perceptions of the precourse educational methods. Incoming first year veterinary students in the Louisiana State University School of Veterinary Medicine professional curriculum were asked to participate in a free precourse before the start of the semester, covering the musculoskeletal structures of the canine thoracic limb. Students learned the material either via dissection only, instructor-led demonstrations only, or a combination of both techniques. Outcome measures included student performance on examinations throughout the first anatomy course of the professional curriculum as compared with those who did not participate in the precourse. This study found that those who participated in the precourse did significantly better on examinations within the professional anatomy course compared with those who did not participate. Notably, this significant improvement was also identified on the examination where both groups were exposed to the material for the first time together, indicating that exposure to a small portion of veterinary anatomy can impact learning of anatomical structures beyond the immediate scope of the material previously learned. Subjective data evaluation indicated that the precourse was well received and students preferred guided learning via demonstrations in addition to dissection as opposed to either method alone. Anat Sci Educ 9: 344-356. © 2015 American Association of Anatomists. PMID:26669269

  3. Market Segmentation Using Bayesian Model Based Clustering

    OpenAIRE

    Van Hattum, P.

    2009-01-01

    This dissertation deals with two basic problems in marketing, that are market segmentation, which is the grouping of persons who share common aspects, and market targeting, which is focusing your marketing efforts on one or more attractive market segments. For the grouping of persons who share common aspects a Bayesian model based clustering approach is proposed such that it can be applied to data sets that are specifically used for market segmentation. The cluster algorithm can handle very l...

  4. Consistent Segmentation using a Rician Classifier

    OpenAIRE

    Roy, Snehashis; Carass, Aaron; Bazin, Pierre-Louis; Resnick, Susan; Prince, Jerry L.

    2011-01-01

    Several popular classification algorithms used to segment magnetic resonance brain images assume that the image intensities, or log-transformed intensities, satisfy a finite Gaussian mixture model. In these methods, the parameters of the mixture model are estimated and the posterior probabilities for each tissue class are used directly as soft segmentations or combined to form a hard segmentation. It is suggested and shown in this paper that a Rician mixture model fits the observed data bette...

  5. Generative models for image segmentation and representation

    OpenAIRE

    González Díaz, Iván

    2011-01-01

    This PhD. Thesis consists of two well differentiated parts, each of them focusing on one particular field of Computer Vision. The first part of the document considers the problem of automatically generating image segmentations in video sequences in the absence of any kind of semantic knowledge or labeled data. To that end, a blind spatio-temporal segmentation algorithm is proposed that fuses motion, color and spatial information to produce robust segmentations. The approach follows an iterati...

  6. A contrario line segment detection

    CERN Document Server

    von Gioi, Rafael Grompone

    2014-01-01

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

  7. Facial expression recognition algorithm based on local Gabor wavelet automatic segmentation%基于自动分割的局部Gabor小波人脸表情识别算法

    Institute of Scientific and Technical Information of China (English)

    刘姗姗; 王玲

    2009-01-01

    针对包含表情信息的静态灰度图像,提出基于自动分割的局部Gabor小波人脸表情识别算法.首先使用数学形态学与积分投影相结合定位眉毛眼睛区域,采用模板内计算均值定位嘴巴区域,自动分割出表情子区域.接着,对分割出的表情子区域进行Gabor小波变换提取表情特征,再利用Fisher线性判别分析进行选择,有效地去除了表情特征的冗余性和相关性.最后利用支持向量机实现对人脸表情的分类.用该算法在日本女性表情数据库上进行测试,实现了自动化且易于实现,结果证明了该方法的有效性.%A local Gabor wavelet facial expression recognition algorithm based on automatic segmentation to the still image containing facial expression information was introduced. Firstly, mathematical morphology combined with projection was used to locate the brow and eye region, and the mouth region was located by calculating template average, which can segment the expression sub-regions automatically. Secondly, features of the expression sub-regions were extracted by Gabor wavelet transformation and then effective Gabor expression features were selected by Fisher Linear Discriminant ( FLD) analysis, removing the redundancy and relevance of expression features. Finally the features were sent to Support Vector Machine (SVM) to classify different expressions. The algorithm was tested on Japanese female facial expression database. It is easy to realize automation. The feasibility of this method has been verified by experiments.

  8. 基于运动目标子块分割的视频零水印算法%VIDEO ZERO-WATERMARKING ALGORITHM BASED ON SEGMENTATION OF SUB-BLOCK OF MOVING OBJECT

    Institute of Scientific and Technical Information of China (English)

    李淑芝; 晏啟明

    2015-01-01

    为了提高视频水印的鲁棒性和隐蔽性,提出一种将水印与视频内容特征相结合的零水印方案。通过帧间欧氏距离选取关键帧,利用改进帧差法提取视频关键帧中运动目标,对关键帧的运动目标进行子块分割,选择运动目标几何形心所在块构成三维体块;再将三维体块分割成多个大小相等的小三维体块,利用小三维体块中所有子块的离散余弦变换直流系数构造特征向量;最后利用特征向量实现将水印零嵌入到视频内容中。实验表明,该算法未破坏原视频内容,不仅具有很好的隐蔽性,还能有效地抵抗旋转、压缩编码等攻击。%In order to improve the robustness and invisibility of video watermarking,we propose a zero-watermarking scheme which com-bines the watermarking with video content characteristics.It selects the key frames through interframe Euclid distance,uses improved frame difference algorithm to extract the moving objects in key frame,and segments the moving objects of key frame into sub-blocks.After selecting the blocks at the geometric centroid of moving object to reconstruct three-dimension block,the scheme then segments the three-dimension block to a couple of small three-dimension blocks in same size,and constructs the feature vector using DC coefficients of discrete cosine trans-form of all blocks in small three-dimension block.Finally,it uses feature vector to realise embedding the zero-watermarking into video con-tents.Experiments show that the algorithm does not damage original video content,apart from having very good imperceptibility,it can also effectively resist the attacks of rotation and compression coding,etc.

  9. Is thinking worthwhile? A comparison of corporate segment choice strategies.

    OpenAIRE

    Buchta, Christian; Dolnicar, Sara; Freitag, Roman; Leisch, Friedrich; Meyer, David; Mild, Andreas; Ossinger, Martina

    2003-01-01

    The field of strategic marketing has long been identified as fruitful ground for gaining competitive advantage. Ever since the market segmentation concept was introduced in the late sixties, research interest steadily increased, covering issues as e.g. which fundamental segmentation strategy is most appropriate, in which ways can segments be identified or constructed, which algorithm provides optimal data-driven segmentation solutions, which number of segments should be constructed etc.. Inte...

  10. Comparison Study of Segmentation Techniques for Brain Tumour Detection

    OpenAIRE

    D. Manju; Dr.M.SEETHA; Dr. K. Venugopala Rao

    2013-01-01

    Image segmentation plays an important role in diagnosis and treatment of diseases. Imagesegmentation locates objects and boundaries with in images and the segmentation process is stopped whenregion of interest is separated from the input image. Based on the application, region of interest may differand hence none of the segmentation algorithm satisfies the global applications. Thus segmentation stillremains a challenging area for researchers. This paper emphasis on comparison study of segment...

  11. An Evaluation of Two Mammography Segmentation Techniques

    Directory of Open Access Journals (Sweden)

    Sujata, R. B. Dubey, R. Dhiman, T. J. Singh Chugh

    2012-12-01

    Full Text Available Mammographic mass detection is an important task for early detection of breast cancer diagnosis and treatment. This is however still remains a challenging task. In this paper, we have proposed a multilevel thresholding algorithm for segmenting the tumor. This paper compares two most popular method, namely between class variance (Otsu and entropy criterion (Kapur’s methods for segmenting the tumor. Our algorithms are tested on 20 mammograms and showing promising results.

  12. Combining Multiple Knowledge Sources for Discourse Segmentation

    CERN Document Server

    Litman, D J; Litman, Diane J.; Passonneau, Rebecca J.

    1995-01-01

    We predict discourse segment boundaries from linguistic features of utterances, using a corpus of spoken narratives as data. We present two methods for developing segmentation algorithms from training data: hand tuning and machine learning. When multiple types of features are used, results approach human performance on an independent test set (both methods), and using cross-validation (machine learning).

  13. Segmental neurofibromatosis.

    Science.gov (United States)

    Sobjanek, Michał; Dobosz-Kawałko, Magdalena; Michajłowski, Igor; Pęksa, Rafał; Nowicki, Roman

    2014-12-01

    Segmental neurofibromatosis or type V neurofibromatosis is a rare genodermatosis characterized by neurofibromas, café-au-lait spots and neurofibromas limited to a circumscribed body region. The disease may be associated with systemic involvement and malignancies. The disorder has not been reported yet in the Polish medical literature. A 63-year-old Caucasian woman presented with a 20-year history of multiple, flesh colored, dome-shaped, soft to firm nodules situated in the right lumbar region. A histopathologic evaluation of three excised tumors revealed neurofibromas. No neurological and ophthalmologic symptoms of neurofibromatosis were diagnosed. PMID:25610358

  14. ANATOMY ON PATTERN RECOGNITION

    OpenAIRE

    MAYANK PARASHER; SHRUTI SHARMA; A .K. SHARMA,; J.P.Gupta

    2011-01-01

    Pattern Recognition is the science of recognizing patterns by machines. This is very wide research area as of today, because every newresearch tries to make machine as intelligent as human for recognizing patterns. Pattern recognition is an active research and an importanttrait of ‘artificial intelligence’. This review paper introduces pattern recognition, its fundamental definitions, and provides understanding of related research work. This paper presents different types of algorithms, their...

  15. Anal anatomy and normal histology.

    Science.gov (United States)

    Pandey, Priti

    2012-12-01

    The focus of this article is the anatomy and histology of the anal canal, and its clinical relevance to anal cancers. The article also highlights the recent histological and anatomical changes to the traditional terminology of the anal canal. The terminology has been adopted by the American Joint Committee on Cancer, separating the anal region into the anal canal, the perianal region and the skin. This paper describes the gross anatomy of the anal canal, along with its associated blood supply, venous and lymphatic drainage, and nerve supply. The new terminology referred to in this article may assist clinicians and health care providers to identify lesions more precisely through naked eye observation and without the need for instrumentation. Knowledge of the regional anatomy of the anus will also assist in management decisions.

  16. K-means聚类算法在网游客户价值分类中的应用%The Application of K-means Clustering Algorithm Based on Network Game Customer Value Segmentation

    Institute of Scientific and Technical Information of China (English)

    张予垚; 黄霞; 史书畅; 陈学东

    2014-01-01

    随着网络游戏行业个性化需求增强,细分网游客户分析客户价值成为游戏运营盈利的关键。本文基于传统K-means聚类算法,结合网游用户消费特征,从初始聚类中心选择、聚类准则和聚类中心最优化方法三方面对该算法进行优化,建立更为完整、系统、准确的客户价值分类数学模型。并开发了客户相似度计算程序,对网游数据进行仿真实验,根据聚类结果对网游客户进行分类。%With the demand for personalized network game is enhanced, the segmentation of the network game customer and the analysis of the game customer value has become a key with which the game operation can be profitable. This paper is based on the traditional K-means clustering algorithm and combined with the consumption characteristics of the game customer to optimize the algorithm by the selection of the initial clustering center, the clustering criteria and the optimum of the clustering center. And then make a set of more complete,systematic and accurate mathematical model of customer value classification. And develop a program on the calculation of customer similarity to do the simulation experiment on some network game data and make a classification of the network game customer according to the experimental results .

  17. Image Segmentation Using Hierarchical Merge Tree

    Science.gov (United States)

    Liu, Ting; Seyedhosseini, Mojtaba; Tasdizen, Tolga

    2016-10-01

    This paper investigates one of the most fundamental computer vision problems: image segmentation. We propose a supervised hierarchical approach to object-independent image segmentation. Starting with over-segmenting superpixels, we use a tree structure to represent the hierarchy of region merging, by which we reduce the problem of segmenting image regions to finding a set of label assignment to tree nodes. We formulate the tree structure as a constrained conditional model to associate region merging with likelihoods predicted using an ensemble boundary classifier. Final segmentations can then be inferred by finding globally optimal solutions to the model efficiently. We also present an iterative training and testing algorithm that generates various tree structures and combines them to emphasize accurate boundaries by segmentation accumulation. Experiment results and comparisons with other very recent methods on six public data sets demonstrate that our approach achieves the state-of-the-art region accuracy and is very competitive in image segmentation without semantic priors.

  18. The Anatomy of Anatomy: A Review for Its Modernization

    Science.gov (United States)

    Sugand, Kapil; Abrahams, Peter; Khurana, Ashish

    2010-01-01

    Anatomy has historically been a cornerstone in medical education regardless of nation or specialty. Until recently, dissection and didactic lectures were its sole pedagogy. Teaching methodology has been revolutionized with more reliance on models, imaging, simulation, and the Internet to further consolidate and enhance the learning experience.…

  19. Anatomy adventure: a board game for enhancing understanding of anatomy.

    Science.gov (United States)

    Anyanwu, Emeka G

    2014-01-01

    Certain negative factors such as fear, loss of concentration and interest in the course, lack of confidence, and undue stress have been associated with the study of anatomy. These are factors most often provoked by the unusually large curriculum, nature of the course, and the psychosocial impact of dissection. As a palliative measure, Anatomy Adventure, a board game on anatomy was designed to reduce some of these pressures, emphasize student centered and collaborative learning styles, and add fun to the process of learning while promoting understanding and retention of the subject. To assess these objectives, 95 out of over 150 medical and dental students who expressed willingness to be part of the study were recruited and divided into a Game group and a Non-game group. A pretest written examination was given to both groups, participants in the Game group were allowed to play the game for ten days, after which a post-test examination was also given. A 20-item questionnaire rated on a three-point scale to access student's perception of the game was given to the game group. The post-test scores of the game group were significantly higher (P game counterparts. Also the post-test score of the game based group was significantly better (P game was interesting, highly informative, encouraged team work, improved their attitude, and perception to gross anatomy. PMID:23878076

  20. 基于中文分词算法的英语学习资源查询系统研究%A Study on Information Resources of English Learning Inquires System Based on Chinese Word Segmentation Algorithm

    Institute of Scientific and Technical Information of China (English)

    卢保娟

    2014-01-01

    Aiming at the usage of Artificial intelligence in the field of information search,this paper having introduced the information resources of English learning inquires system based on Chinese word segmentation algorithm.The system having achieved intelligent search of the English learning which through a kind of Chinese word segmentation’s search strategy and case- based reasoning technology. The results show that this system can get the users to gain satisfying results.%针对人工智能在信息搜索领域的实际应用,本文介绍了一种基于中文分词算法的英语学习资源查询系统。该系统通过一种基于中文分词算法的搜索策略,结合事例推理技术实现对英语学习资源的智能搜索。系统测试结果表明,用户可以通过该系统搜索到所提问问题的类似事例以及解决该问题的相关知识条款。

  1. 3D virtual table in anatomy education

    DEFF Research Database (Denmark)

    Dahl, Mads Ronald; Simonsen, Eivind Ortind

    The ‘Anatomage’ is a 3D virtual human anatomy table, with touchscreen functionality, where it is possible to upload CT-scans and digital. Learning the human anatomy terminology requires time, a very good memory, anatomy atlas, books and lectures. Learning the 3 dimensional structure, connections...

  2. Superresolution improves MRI cortical segmentation with FACE

    DEFF Research Database (Denmark)

    Eskildsen, Simon Fristed; Manjón, José V.; Coupé, Pierrick;

    Brain cortical surface extraction from MRI has applications for measurement of gray matter (GM) atrophy, functional mapping, source localization and preoperative neurosurgical planning. Accurate cortex segmentation requires high resolution morphological images and several methods for extracting...... the cerebral cortex have been developed during the last decade (Dale 1999, Kim 2005, Eskildsen 2006). In many studies, the resolution of the morphological image acquisition sequence is chosen to be relatively low (~1mm3) due to time and equipment constraints. To improve segmentation accuracy, such low...... the ability to effectively increase the image resolution while preserving sharp features of the underlying anatomy. In this study, we investigated the effect of applying superresolution as proposed in (Manjon 2010a) to the accuracy of cerebral cortex segmentation....

  3. Segmentation of moving images by the human visual system.

    Science.gov (United States)

    Chantelau, K

    1997-08-01

    New segments appearing in an image sequence or spontaneously accelerated segments are band limited by the visual system due to a nonperfect tracking of these segments by eye movements. In spite of this band limitation and acceleration of segments, a coarse segmentation (initial segmentation phase) can be performed by the visual system. This is interesting for the development of purely automatic segmentation algorithms for multimedia applications. In this paper the segmentation of the visual system is modelled and used in an automatic coarse initial segmentation. A suitable model for motion processing based on a spectral representation is presented and applied to the segmentation of synthetic and real image sequences with band limited and accelerated moving foreground and background segments.

  4. Unsupervised Segmentation Methods of TV Contents

    Directory of Open Access Journals (Sweden)

    Elie El-Khoury

    2010-01-01

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

  5. Unsupervised Color-texture Image Segmentation

    Institute of Scientific and Technical Information of China (English)

    YU Sheng-yang; ZHANG Fan; WANG Yong-gang; YANG Jie

    2008-01-01

    The measure J in J value segmentation (JSEG) falls to represent the discontinuity of color, which degrades the robustness and discrimination of JSEG. An improved approach for JSEG algorithm was proposed for unsupervised color-texture image segmentation. The texture and photometric invariant edge information were combined, which results in a discriminative measure for color-texture homogeneity. Based on the image whose pixel values are values of the new measure, region growing-merging algorithm used in JSEG was then employed to segment the image. Finally, experiments on a variety of real color images demonstrate performance improvement due to the proposed method.

  6. Soul Anatomy: A virtual cadaver

    Directory of Open Access Journals (Sweden)

    Moaz Bambi

    2014-01-01

    Full Text Available In the traditional science of medicine and medical education, teaching human anatomy in the class has always been done using human cadavers. Not only does this violate human sanctity, but according to our research, it is not adequate to provide students with the alleged educational value that it is supposed to deliver. It is very cumbersome to organise all the aspects of cadaver care. Cadavers are also very limited when it comes to controlling their structures and any benefit is almost completely altered the first time the cadaver is used (dissected, and ironically, it is very weak at delivering actual real-life scenarios of a human body to students. Virtual anatomy has been a promising solution that many are counting on. But even today, we have not found a complete solution that combines all the benefits of using human cadavers and those introduced by its technical counterparts. "Soul Anatomy" aims to do just that. It brings the best of all worlds, from a natural intuitive control system, life-like feel of organs, precise accuracy in moving and controlling bodily structures, to the smallest details of being able to show medical information overlays from various medical databases connected to the internet; thus making use of technology in teaching human anatomy by providing a modern learning experience.

  7. DAGAL: Detailed Anatomy of Galaxies

    CERN Document Server

    Knapen, Johan H

    2016-01-01

    The current IAU Symposium is closely connected to the EU-funded network DAGAL (Detailed Anatomy of Galaxies), with the final annual network meeting of DAGAL being at the core of this international symposium. In this short paper, we give an overview of DAGAL, its training activities, and some of the scientific advances that have been made under its umbrella.

  8. VIDEO SEGMENTATION USING A NOVEL LBP DESCRIPTOR

    Directory of Open Access Journals (Sweden)

    Zhongkun He

    2014-08-01

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

  9. Evaluation for Uncertain Image Classification and Segmentation

    CERN Document Server

    Martin, Arnaud; Arnold-Bos, Andreas

    2008-01-01

    Each year, numerous segmentation and classification algorithms are invented or reused to solve problems where machine vision is needed. Generally, the efficiency of these algorithms is compared against the results given by one or many human experts. However, in many situations, the location of the real boundaries of the objects as well as their classes are not known with certainty by the human experts. Furthermore, only one aspect of the segmentation and classification problem is generally evaluated. In this paper we present a new evaluation method for classification and segmentation of image, where we take into account both the classification and segmentation results as well as the level of certainty given by the experts. As a concrete example of our method, we evaluate an automatic seabed characterization algorithm based on sonar images.

  10. The future of gross anatomy teaching.

    Science.gov (United States)

    Malamed, S; Seiden, D

    1995-01-01

    A survey of U.S. departments of anatomy, physiology, and biochemistry shows that 39% of the respondent anatomy departments reported declines in the numbers of graduate students taking the human gross anatomy course. Similarly, 42% of the departments reported decreases in the numbers of graduate students teaching human gross anatomy. These decreases were greater in anatomy than in physiology and in biochemistry. The percentages of departments reporting increases in students taking or teaching their courses was 6% for human gross anatomy and 0% to 19% for physiology and biochemistry courses. To reverse this trend the establishment of specific programs for the training of gross anatomy teachers is advocated. These new teachers will be available as the need for them is increasingly recognized in the future.

  11. Virtual Temporal Bone Anatomy

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Background The Visible Human Project(VHP) initiated by the U.S. National Library of Medicine has drawn much attention and interests from around the world. The Visible Chinese Human (VCH) project has started in China. The current study aims at acquiring a feasible virtual methodology for reconstructing the temporal bone of the Chinese population, which may provide an accurate 3-D model of important temporal bone structures that can be used in teaching and patient care for medical scientists and clinicians. Methods A series of sectional images of the temporal bone were generated from section slices of a female cadaver head. On each sectional image, SOIs (structures of interest) were segmented by carefully defining their contours and filling their areas with certain gray scale values. The processed volume data were then inducted into the 3D Slicer software(developed by the Surgical Planning Lab at Brigham and Women's Hospital and the MIT AI Lab) for resegmentation and generation of a set of tagged images of the SOIs. 3D surface models of SOIs were then reconstructed from these images. Results The temporal bone and structures in the temporal bone, including the tympanic cavity, mastoid cells, sigmoid sinus and internal carotid artery, were successfully reconstructed. The orientation of and spatial relationship among these structures were easily visualized in the reconstructed surface models. Conclusion The 3D Slicer software can be used for 3-dimensional visualization of anatomic structures in the temporal bone, which will greatly facilitate the advance of knowledge and techniques critical for studying and treating disorders involving the temporal bone.

  12. Anatomy of Teaching Anatomy: Do Prosected Cross Sections Improve Students Understanding of Spatial and Radiological Anatomy?

    Science.gov (United States)

    Vithoosan, S.; Kokulan, S.; Dissanayake, M. M.; Dissanayake, Vajira; Jayasekara, Rohan

    2016-01-01

    Introduction. Cadaveric dissections and prosections have traditionally been part of undergraduate medical teaching. Materials and Methods. Hundred and fifty-nine first-year students in the Faculty of Medicine, University of Colombo, were invited to participate in the above study. Students were randomly allocated to two age and gender matched groups. Both groups were exposed to identical series of lectures regarding anatomy of the abdomen and conventional cadaveric prosections of the abdomen. The test group (n = 77, 48.4%) was also exposed to cadaveric cross-sectional slices of the abdomen to which the control group (n = 82, 51.6%) was blinded. At the end of the teaching session both groups were assessed by using their performance in a timed multiple choice question paper as well as ability to identify structures in abdominal CT films. Results. Scores for spatial and radiological anatomy were significantly higher among the test group when compared with the control group (P < 0.05, CI 95%). Majority of the students in both control and test groups agreed that cadaveric cross section may be useful for them to understand spatial and radiological anatomy. Conclusion. Introduction of cadaveric cross-sectional prosections may help students to understand spatial and radiological anatomy better. PMID:27579181

  13. Anatomy of Teaching Anatomy: Do Prosected Cross Sections Improve Students Understanding of Spatial and Radiological Anatomy?

    Directory of Open Access Journals (Sweden)

    L. B. Samarakoon

    2016-01-01

    Full Text Available Introduction. Cadaveric dissections and prosections have traditionally been part of undergraduate medical teaching. Materials and Methods. Hundred and fifty-nine first-year students in the Faculty of Medicine, University of Colombo, were invited to participate in the above study. Students were randomly allocated to two age and gender matched groups. Both groups were exposed to identical series of lectures regarding anatomy of the abdomen and conventional cadaveric prosections of the abdomen. The test group (n=77, 48.4% was also exposed to cadaveric cross-sectional slices of the abdomen to which the control group (n=82, 51.6% was blinded. At the end of the teaching session both groups were assessed by using their performance in a timed multiple choice question paper as well as ability to identify structures in abdominal CT films. Results. Scores for spatial and radiological anatomy were significantly higher among the test group when compared with the control group (P<0.05, CI 95%. Majority of the students in both control and test groups agreed that cadaveric cross section may be useful for them to understand spatial and radiological anatomy. Conclusion. Introduction of cadaveric cross-sectional prosections may help students to understand spatial and radiological anatomy better.

  14. Segmentation of anatomical structures in chest CT scans

    NARCIS (Netherlands)

    van Rikxoort, E.M.

    2009-01-01

    In this thesis, methods are described for the automatic segmentation of anatomical structures from chest CT scans. First, a method to segment the lungs from chest CT scans is presented. Standard lung segmentation algorithms rely on large attenuation differences between the lungs and the surrounding

  15. Computer Aided Segmentation Analysis: New Software for College Admissions Marketing.

    Science.gov (United States)

    Lay, Robert S.; Maguire, John J.

    1983-01-01

    Compares segmentation solutions obtained using a binary segmentation algorithm (THAID) and a new chi-square-based procedure (CHAID) that segments the prospective pool of college applicants using application and matriculation as criteria. Results showed a higher number of estimated qualified inquiries and more accurate estimates with CHAID. (JAC)

  16. Anatomy of a Bird

    Science.gov (United States)

    2007-12-01

    Using ESO's Very Large Telescope, an international team of astronomers [1] has discovered a stunning rare case of a triple merger of galaxies. This system, which astronomers have dubbed 'The Bird' - albeit it also bears resemblance with a cosmic Tinker Bell - is composed of two massive spiral galaxies and a third irregular galaxy. ESO PR Photo 55a/07 ESO PR Photo 55a/07 The Tinker Bell Triplet The galaxy ESO 593-IG 008, or IRAS 19115-2124, was previously merely known as an interacting pair of galaxies at a distance of 650 million light-years. But surprises were revealed by observations made with the NACO instrument attached to ESO's VLT, which peered through the all-pervasive dust clouds, using adaptive optics to resolve the finest details [2]. Underneath the chaotic appearance of the optical Hubble images - retrieved from the Hubble Space Telescope archive - the NACO images show two unmistakable galaxies, one a barred spiral while the other is more irregular. The surprise lay in the clear identification of a third, clearly separate component, an irregular, yet fairly massive galaxy that seems to be forming stars at a frantic rate. "Examples of mergers of three galaxies of roughly similar sizes are rare," says Petri Väisänen, lead author of the paper reporting the results. "Only the near-infrared VLT observations made it possible to identify the triple merger nature of the system in this case." Because of the resemblance of the system to a bird, the object was dubbed as such, with the 'head' being the third component, and the 'heart' and 'body' making the two major galaxy nuclei in-between of tidal tails, the 'wings'. The latter extend more than 100,000 light-years, or the size of our own Milky Way. ESO PR Photo 55b/07 ESO PR Photo 55b/07 Anatomy of a Bird Subsequent optical spectroscopy with the new Southern African Large Telescope, and archive mid-infrared data from the NASA Spitzer space observatory, confirmed the separate nature of the 'head', but also added

  17. CT-based manual segmentation and evaluation of paranasal sinuses.

    Science.gov (United States)

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

    2009-04-01

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

  18. 基于分块采样和遗传算法的自动多阈值图像分割%Automatic Multilevel Thresholding for Image Segmentation Based on Block Sampling and Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    姜允志; 郝志峰; 林智勇; 袁淦钊

    2011-01-01

    图像多阈值分割在图像压缩、图像分析和模式识别等很多领域具有重要应用,但是阈值数的自动选择一直是至今未解决的难题.为此,基于分块采样和遗传算法提出一种自动多阈值图像分割算法.首先将一幅图像看成是由像素值组成的总体,运用分块采样得到若干子样本;其次在每一个子样本中运用遗传算法来使样本的均值与方差比极大化;再基于获得的样本信息对阈值数目和阈值进行自动预测;最后利用一种确定性的算法对阈值数和阈值做进一步的优化.该算法无需事先考虑图像的纹理和分割数等先验信息,具有较高的易用性,其计算复杂性对图像阈值个数敏感性较低,且无需进行灰度直方图分析.在Berkeley图像分割数据集上的大量仿真实验结果表明,文中算法能获得较准确、快速和稳定的图像分割.%Multilevel thresholding is an important technique for image compression, image analysis and pattern recognition. However, it is a hard problem to determine the number of thresholds automatically. In this paper, a new multilevel thresholding method called as automatic multilevel thresholding algorithm for image segmentation based on block sampling and genetic algorithm (AMT-BSGA) is proposed on the basis of block sampling and genetic algorithm. The proposed method can automatically determine the appropriate number of thresholds and the proper threshold values. In AMT-BSGA, an image is treated as a group of individual pixels with the gray values. First, an image is evenly divided into several blocks, and a sample is drawn from each block. Then, genetic algorithm based optimization is applied to each sample to maximize the ratio of mean and variance of the sample. Based on the optimized samples, the number of thresholds and threshold values are preliminarily determined. Finally, a deterministic method is implemented to further optimize the number of thresholds and

  19. REDUCTION ALGORITHM OF POINT CLOUD SEGMENTATION BASED ON ADAPTIVE ELLIPTICAL DISTANCE%基于自适应椭圆距离的点云分区精简算法

    Institute of Scientific and Technical Information of China (English)

    吴禄慎; 俞涛; 陈华伟

    2016-01-01

    Applying traditional point cloud reduction algorithm to reducing scattered point cloud will lead to missing or fuzzy of some detail features of the point cloud model and affecting the smoothness of non planar region.Aiming at these problems,we put forward the adaptive elliptical distance-based point cloud segmentation reduction algorithm.First,by fitting the tangent plane and local surface on neighbourhood set,it calculates the normal vector and curvature of each point;secondly,it uses the derived geometric feature information to extract point cloud boundary characteristics and to complete the partition of planar regions and non planar regions of point cloud;finally,it uses the improved reduction algorithm to simplify different regions.Experimental results show that the algorithm can not only rapidly accomplish data simplification in accord with the required reduction rate,but can also protect the detail characteristics of point cloud model and ensure the smoothness of non planar portion of model.Through software analysis,it is found that the standard deviation between the reduced model and the original model is 0.015 mm.%利用传统点云精简算法进行散乱点云简化会导致点云模型部分细节特征的丢失或模糊以及影响非平面区域的光顺性。针对这些问题,提出基于自适应椭圆距离的点云分区精简算法。首先,通过对邻域点集进行微切平面与局部曲面的拟合,计算出各点的法矢及曲率等;其次,利用所得几何特征信息,提取点云边界特征以及完成点云平面区域与非平面区域的划分;最后,采用改进后的精简算法对不同区域进行简化。实验结果表明,该算法不但能够快速完成符合要求精简率的数据简化,还能保护点云模型的细节特征以及保证模型非平面部分的光顺性。经过软件分析得出,精简后模型与原始模型的距离误差的标准偏差为0.015 mm。

  20. 基于变异系数的双聚类算法及其在电信客户细分的应用研究%ON VARIATION COEFFICIENT-BASED BICLUSTERING ALGORITHM AND ITS APPLICATION IN TELECOMMUNICATION CUSTOMER SEGMENTATION

    Institute of Scientific and Technical Information of China (English)

    林勤; 薛云; 杨柏高

    2016-01-01

    To improve the refinement degree of traditional customer value segmentation method,we proposed the variation coefficient-based biclustering algorithm.The algorithm selects the variation coefficient as the similarity measurement,applies the heuristic greedy strategy,and by the way of iterating the rows’or columns’insertion and deletion,the algorithm mines the customer groups with similar local consuming behaviours from their consumption records.Taking the telecommunication customers segmentation in a certain Telecom as the example,we compared the performances of the proposed algorithm with k-means clustering algorithm.Experimental result indicated that the proposed algorithm has better ability of customer segmentation and stronger interpretable ability on customer behaviours.Therefore,it is more conducive to guiding the enterprises to develop differentiated marketing strategies.%针对传统客户价值细分方法不够精细化的问题,提出一种基于变异系数的双聚类算法。该算法选用了变异系数作为相似性度量,运用启发式贪心策略,通过迭代增删行列的方式挖掘出客户消费记录中局部消费行为相似的客户群体。以某电信公司的电信客户细分为实例,将所提算法与 K 均值(K-means)算法进行性能比较,实验结果表明,所提算法具有更优的客户细分能力和更强的客户行为可解释能力。因此,它更有助于指导企业制定差异化营销策略。

  1. Image Fusion Algorithm Based on Region Segmentation and Lifting Wavelet Transform%基于区域分割与提升小波变换的图像融合算法

    Institute of Scientific and Technical Information of China (English)

    高颖; 王阿敏; 支朋飞; 葛飞

    2014-01-01

    针对精确制导武器系统中,利用传统方法获取的融合图像使得红外目标模糊、识别率低、定位性差及不能继承可见光图像色彩特性而出现光谱扭曲与失真的现象,提出了一种基于区域分割和提升小波变换的红外与可见光图像融合方法。首先结合区域生长与边缘提取图像分割法,将红外图像背景区域与目标区域分开;其次采用像素邻域能量取大法,将红外目标区域映射到可见光背景中;最后将上步得到的融合图像与原图像进行低频加权,高频平均梯度的提升小波融合变换,防止因图像分割所形成的拼接错误而导致重要信息丢失现象。实验结果表明:融合后的图像,目标凸显,背景自然,能够达到准确定位与快速识别的目的,并对隐藏目标的检测有着重要的指导意义。%As regards precision-guided weapons systems, the fused images obtained by traditional methods give fuzzy detection , low recognition rate and poor positioning for infrared target;meanwhile they are unable to highlight the visible color characteristics;thus spectral distortion results. We present a fusion method of region-based segmen-tation and lifting wavelet transform for infrared and visible image. We do three things: (1) making the infrared background and destination areas separate with image segmentation methods of regional growth combined with edge detection;(2) using the maximum energy around pixel neighborhood to make infrared target mapped to the visible background;(3) for the fused image acquired by the step above-mentioned steps and the original images, utilizing the lifting wavelet transform about the weighted algorithm for low frequency and the average gradient for high fre-quency, thus avoiding important information being missed because of segmentation error. The experimental results and their analysis show preliminarily that:the fused image can highlight target, make background

  2. Farmland Cropping System Identification in China Based on a Sliding Segmentation Algorithm%基于滑动分割算法的我国耕地熟制识别研究

    Institute of Scientific and Technical Information of China (English)

    刘爽; 马欣; 李玉娥; 张平究

    2014-01-01

    熟制时空格局的正确识别对评估粮食产量的变化及其原因和农业发展的科学决策都有非常重要的意义,卫星遥感监测是获取区域和全国尺度熟制格局的有效手段.本文在对启发式分割算法改进的基础上行成了基于作物生长周期的滑动分割算法,并首次运用到耕地熟制的识别提取.针对NDVI时间序列曲线特征,在不引入熟制分区和物候等信息,仅以土地利用为辅助数据的前提下识别了1982-2006年我国耕地熟制格局.结果表明,本方法监测结果与统计数据和前人监测结果均呈显著相关性,为正相关关系,相关系数分别为0.77和0.93,均通过0.001水平的显著性检验;熟制的分布为区域性和复杂性并存,其空间分布规律性显著但熟制区内复杂性较明显;一熟区总体变动不明显但区域范围在逐步缩小,两熟区整体向北、向西扩展,向北扩展趋势明显,三熟区缓慢扩大并出现零星区域的北移、西移.%Multiple cropping is an important feature of China' s farmland cropping system and an important way to improve food production.Correct recognition of cropping spatio-temporal patterns is important to assess changes,understand grain yield,and the development of agriculture scientific decision-making.Here we present an improved heuristic segmentation algorithm and sliding segmentation algorithm based on crop growth cycles,and apply this to the identification of farmland cropping system extraction.NDVI time series curve characteristics analysis for the 1982-2006 cropping pattern of cultivated land in China was used.We found that the statistical check between monitoring results,statistical data and previous monitoring were positively correlated; the correlation coefficients were 0.77 and 0.93.The distribution of cropping systems is regional and complex,the space distribution of the main cropping system is regular,but the cropping system shows complexity within the cropping area

  3. 采用几何模型切分的人脸纹理图像生成算法%Algorithm for generating human face texture images based on geometric model segmentation

    Institute of Scientific and Technical Information of China (English)

    陈婵娟; 康宝生; 冯筠

    2011-01-01

    为了克服传统的照片图像拼接方法中利用特征线进行不同照片之间公共交界线定位不准确的缺点,提出一种“几何模型切分”的人脸纹理图像生成算法.通过对人脸几何模型进行切分,以切分后模型图片的轮廓作为边界线裁剪相应的人脸照片,实现不同照片之间交界线的准确对接,并采用柱面纹理映射方法将生成的纹理图像映射到特定人脸几何模型上.实验结果表明,采用提出的“几何模型切分”算法生成的人脸纹理图像进行纹理映射可以得到较好的真实感三维人脸模型,是一种生成人脸纹理图像的有效方法.%To avoid the shortcomings that it is imprecise to use feature line to locate the intersection of the adjacent photographic images in traditional texture image generation method,a new algorithm called "geometric model segmentation" is introduced. Through cutting the geometry model of human's head,the contours of the divided model photos are obtained to manicure the corresponding face photos as the boundary line.The manicured face photos can be used to generate texture picture without overlapping and gap between the adjacent pictures.The cylindrical projection is introduced to construct 3D specific face model through the texture mapping by using of the above texture picture.The experiments show that the new algorithm is an effective way to generate texture images in photo-realistic 3D human face modeling.

  4. 基于Random Walks算法的心脏双源CT左心房分割%Study of left atrium segmentation in dual source CT image with random walks algorithms

    Institute of Scientific and Technical Information of China (English)

    何昌保; 马秀丽; 余长明

    2016-01-01

    For dual source CT image with contrast media,due to heart soft tissue density and contrast media uneven distribution result in the CT value of heart tissues uneven and boundary fuzzy,taking a single image segmentation algorithm is too difficult to obtain satisfactory results,so morphological reconstruction and random walks hybrid method is proposed in this paper.Firstly,we used morphological reconstruction operation on image smoothing filtering, which makes the heart cavity gray information convergence and gray level differences with the surrounding tissue and get the left atrium area with the fuzzy boundary;Then the random walks algorithm sets the seed points for each region of the image,and gives the weight of each side,and takes the weight of the edge as the transfer probability.For each unlabeled point is calculated from the point of first arrival probability of seed points.Finally,according to the first hit probability to choose the maximum that a class as belonging to the class,attribute of the unlabeled points and finally get the accurate left atrial.%针对在传统的CT介入式治疗过程中,胸腔中软组织较多软组织的厚度和注射的造影剂在心脏中呈现的不均匀分布,导致在采用CT成像的图像中胸腔内部各组织之间存在边界模糊或者确实等状况,本文提出一种采用形态重构和随机行走相结合的分割方法。首先利用形态学开闭运算对图像进行化简,并使得心脏 CT腔体边界分离,进而使得各个组织组织分离,再结合Random walks算法。从而使得不需要标记太多种子点的情况下提高了分割的速度和准确性,实验证明该方法能够达到预期的目标。

  5. Poster — Thur Eve — 70: Automatic lung bronchial and vessel bifurcations detection algorithm for deformable image registration assessment

    Energy Technology Data Exchange (ETDEWEB)

    Labine, Alexandre; Carrier, Jean-François; Bedwani, Stéphane [Centre hospitalier de l' Université de Montréal (Canada); Chav, Ramnada; De Guise, Jacques [Laboratoire de recherche en imagerie et d' orthopédie-CRCHUM, École de technologie supérieure (Canada)

    2014-08-15

    Purpose: To investigate an automatic bronchial and vessel bifurcations detection algorithm for deformable image registration (DIR) assessment to improve lung cancer radiation treatment. Methods: 4DCT datasets were acquired and exported to Varian treatment planning system (TPS) EclipseTM for contouring. The lungs TPS contour was used as the prior shape for a segmentation algorithm based on hierarchical surface deformation that identifies the deformed lungs volumes of the 10 breathing phases. Hounsfield unit (HU) threshold filter was applied within the segmented lung volumes to identify blood vessels and airways. Segmented blood vessels and airways were skeletonised using a hierarchical curve-skeleton algorithm based on a generalized potential field approach. A graph representation of the computed skeleton was generated to assign one of three labels to each node: the termination node, the continuation node or the branching node. Results: 320 ± 51 bifurcations were detected in the right lung of a patient for the 10 breathing phases. The bifurcations were visually analyzed. 92 ± 10 bifurcations were found in the upper half of the lung and 228 ± 45 bifurcations were found in the lower half of the lung. Discrepancies between ten vessel trees were mainly ascribed to large deformation and in regions where the HU varies. Conclusions: We established an automatic method for DIR assessment using the morphological information of the patient anatomy. This approach allows a description of the lung's internal structure movement, which is needed to validate the DIR deformation fields for accurate 4D cancer treatment planning.

  6. Optimization of Segmentation Quality of Integrated Circuit Images

    Directory of Open Access Journals (Sweden)

    Gintautas Mušketas

    2012-04-01

    Full Text Available The paper presents investigation into the application of genetic algorithms for the segmentation of the active regions of integrated circuit images. This article is dedicated to a theoretical examination of the applied methods (morphological dilation, erosion, hit-and-miss, threshold and describes genetic algorithms, image segmentation as optimization problem. The genetic optimization of the predefined filter sequence parameters is carried out. Improvement to segmentation accuracy using a non optimized filter sequence makes 6%.Artcile in Lithuanian

  7. Ecological anatomy of ferns fronds

    Directory of Open Access Journals (Sweden)

    Nina M. Derzhavina

    2014-04-01

    Full Text Available Structural types of frond anatomy are distinguished on the basis of investigation of 30 species of homosporous ferns and with regard for literature: hydromorphic, hygromorphic, mesomorphic, subxeromorphic, and subsucculent (cryptic succulent. Following frond traits are of highest adaptive value: their area and thickness, type of mesophyll, dry weight of an area unit – specific superficial density, cellular volume, and number of cells per unit of frond area.

  8. [Functional dental anatomy and amalgam].

    Science.gov (United States)

    Tavernier, B; Colon, P

    1989-01-01

    Very often, the functional dental anatomy are reflected during the rehabilitation of posterior quadrants. However, the placement, the shaping in correct relation of the different dental components are indispensable conditions to respect, in order to achieve an adequate integration of the restoration within the neuro-muscular system. A clinical protocol is proposed in order to reconcile the anatomical and biological prerequisite and the setting time of modern alloys.

  9. Anatomy of the infant head

    International Nuclear Information System (INIS)

    This text is mainly an atlas of illustration representing the dissection of the head and upper neck of the infant. It was prepared by the author over a 20-year period. The commentary compares the anatomy of the near-term infant with that of a younger fetus, child, and adult. As the author indicates, the dearth of anatomic information about postnatal anatomic changes represents a considerable handicap to those imaging infants. In part 1 of the book, anatomy is related to physiologic performance involving the pharynx, larynx, and mouth. Sequential topics involve the regional anatomy of the head (excluding the brain), the skeleton of the cranium, the nose, orbit, mouth, larynx, pharynx, and ear. To facilitate use of this text as a reference, the illustrations and text on individual organs are considered separately (i.e., the nose, the orbit, the eye, the mouth, the larynx, the pharynx, and the ear). Each part concerned with a separate organ includes materials from the regional illustrations contained in part 2 and from the skeleton, which is treated in part 3. Also included in a summary of the embryologic and fetal development of the organ

  10. Segmentation of individual ribs from low-dose chest CT

    Science.gov (United States)

    Lee, Jaesung; Reeves, Anthony P.

    2010-03-01

    Segmentation of individual ribs and other bone structures in chest CT images is important for anatomical analysis, as the segmented ribs may be used as a baseline reference for locating organs within a chest as well as for identification and measurement of any geometric abnormalities in the bone. In this paper we present a fully automated algorithm to segment the individual ribs from low-dose chest CT scans. The proposed algorithm consists of four main stages. First, all the high-intensity bone structure present in the scan is segmented. Second, the centerline of the spinal canal is identified using a distance transform of the bone segmentation. Then, the seed region for every rib is detected based on the identified centerline, and each rib is grown from the seed region and separated from the corresponding vertebra. This algorithm was evaluated using 115 low-dose chest CT scans from public databases with various slice thicknesses. The algorithm parameters were determined using 5 scans, and remaining 110 scans were used to evaluate the performance of the segmentation algorithm. The outcome of the algorithm was inspected by an author for the correctness of the segmentation. The results indicate that over 98% of the individual ribs were correctly segmented with the proposed algorithm.

  11. Multilevel Threshold Based Gray Scale Image Segmentation using Cuckoo Search

    OpenAIRE

    Samantaa, Sourav; Dey, Nilanjan; Das, Poulami; Acharjee, Suvojit; Chaudhuri, Sheli Sinha

    2013-01-01

    Image Segmentation is a technique of partitioning the original image into some distinct classes. Many possible solutions may be available for segmenting an image into a certain number of classes, each one having different quality of segmentation. In our proposed method, multilevel thresholding technique has been used for image segmentation. A new approach of Cuckoo Search (CS) is used for selection of optimal threshold value. In other words, the algorithm is used to achieve the best solution ...

  12. A comparative study on medical image segmentation methods

    OpenAIRE

    Praylin Selva Blessy SELVARAJ ASSLEY; Helen Sulochana CHELLAKKON

    2014-01-01

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

  13. ENHANCED GRAPH BASED NORMALIZED CUT METHODS FOR IMAGE SEGMENTATION

    OpenAIRE

    S.D. Kapade; S.M. Khairnar; B.S. Chaudhari

    2014-01-01

    Image segmentation is one of the important steps in digital image processing. Several algorithms are available for segmenting the images, posing many challenges such as precise criteria and efficient computations. Most of the graph based methods used for segmentation depend on local properties of graphs without considering global impressions of image, which ultimately limits segmentation quality. In this paper, we propose an enhanced graph based normalized cut method for extracting global imp...

  14. Multicriterion Market Segmentation: A New Model, Implementation, and Evaluation

    OpenAIRE

    Ying Liu; Sudha Ram; Lusch, Robert F; Michael Brusco

    2010-01-01

    Market segmentation is inherently a multicriterion problem even though it has often been modeled as a single-criterion problem in the traditional marketing literature and in practice. This paper discusses the multicriterion nature of market segmentation and develops a new mathematical model that addresses this issue. A new method for market segmentation based on multiobjective evolutionary algorithms, called MMSEA, is developed. It complements existing segmentation methods by optimizing multi...

  15. Sports Video Segmentation using Spectral Clustering

    Directory of Open Access Journals (Sweden)

    Xiaohong Zhao

    2014-07-01

    Full Text Available With the rapid development of the computer and multimedia technology, the video processing technique is applied to the field of sports in order to analyze the sport video. For sports video analysis, how to segment the sports video image has become an important research topic. Nowadays, the algorithms for video image segmentation mainly include neural network, K-means and so on. However, the accuracy and speed of these algorithms for moving objects segmentation are not satisfied, and easily influenced by the irregular movement of the object and illumination, etc. In view of this, this paper proposes an algorithm for object segmentation in sports video image sequence, based on the spectral clustering. This algorithm simultaneously considers the pixel level visual feature and the edge information of the neighboring pixels to make the calculation of similarity is more intuitive and not affected by factors such as image texture. When clustering the image feature, the proposed method: (1 preprocesses video image sequence and extracts the image feature. (2Using weight function to build and calculate the similar matrix between pixels. (2 Extract feature vector. (3 Perform clustering using spectral clustering algorithm to segment the sports video image. The experimental results indicate that the method proposed in this paper has the advantages, such as lower complexity, high computational effectiveness, low computational amount, and so on. It can get better extraction effects on video image

  16. Brachial Plexus Anatomy: Normal and Variant

    Directory of Open Access Journals (Sweden)

    Steven L. Orebaugh

    2009-01-01

    Full Text Available Effective brachial plexus blockade requires a thorough understanding of the anatomy of the plexus, as well as an appreciation of anatomic variations that may occur. This review summarizes relevant anatomy of the plexus, along with variations and anomalies that may affect nerve blocks conducted at these levels. The Medline, Cochrane Library, and PubMed electronic databases were searched in order to compile reports related to the anatomy of the brachial plexus using the following free terms: "brachial plexus", "median nerve", "ulnar nerve", "radial nerve", "axillary nerve", and "musculocutanous nerve". Each of these was then paired with the MESH terms "anatomy", "nerve block", "anomaly", "variation", and "ultrasound". Resulting articles were hand searched for additional relevant literature. A total of 68 searches were conducted, with a total of 377 possible articles for inclusion. Of these, 57 were found to provide substantive information for this review. The normal anatomy of the brachial plexus is briefly reviewed, with an emphasis on those features revealed by use of imaging technologies. Anomalies of the anatomy that might affect the conduct of the various brachial plexus blocks are noted. Brachial plexus blockade has been effectively utilized as a component of anesthesia for upper extremity surgery for a century. Over that period, our understanding of anatomy and its variations has improved significantly. The ability to explore anatomy at the bedside, with real-time ultrasonography, has improved our appreciation of brachial plexus anatomy as well.

  17. [New findings of clinical anatomy in pelvis].

    Science.gov (United States)

    Muraoka, Kuniyasu; Takenaka, Atsushi

    2016-01-01

    Surgical anatomy involves clarifying the mutual relationships of each structure in the operative field. Knowledge of new surgical anatomy has arisen via new methods or approaches. Associated with the development and spread of laparoscopic surgery in recent years, adaptation to changes in surgical techniques using knowledge of classical pelvic anatomy has been difficult. Better knowledge of the delicate structures surrounding the prostate is essential in order to provide both cancer control and functional preservation with regard to radical prostatectomy. In this report, we review the progress in knowledge of pelvic anatomy, particularly regarding the endopelvic fascia, prostatic fascia and Denonvilliers' fascia.

  18. 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.

  19. Microsurgical anatomy of the anterior cerebral artery in Indian cadavers

    Directory of Open Access Journals (Sweden)

    Shweta Kedia

    2013-01-01

    Full Text Available Background: The microanatomy features of cerebral arteries may be variable and may be different in different ethnic groups. Aim: To study the anterior cerebral artery (ACA anatomy in North-West Indian cadavers. Materials and Methods: Microanatomy features of the ACA were studied in 15 formalin fixed human cadaveric brains under microscope. The outer diameter, length, and number of perforating branches with respective anomalies were measured for each of the following vessels: ACA (proximal A1 segment to distal A2 segment, anterior communicating artery (ACoA, Recurrent artery of Heubner (RAH, and callosomarginal artery and photographed for documentation. Results: The mean length and external diameter of right and left A1 segment was 12.09 mm and 12.0 mm and 2.32 mm and 2.36 mm respectively. Narrowing, duplication, and median ACA were seen in 6.6%, 3.3% and 6.6% of the vessels respectively. Complex ACoA type was seen in 40% cadavers. RAH originated at an average point of 0.2 mm distal to ACoA, but in one cadaver it arose 5 mm proximal to ACoA. Double RAH was found in 26.6%. The course of RAH in relation to A1 was superiorly in 60%, in anteriorly 30% and posteriorly in 10% of cadavers. The orbitofrontal artery (OFA and frontopolar artery (FPA arose from A2 in 83.3% to 40% respectively. The mean distance of OFA and FPA from ACoA was 4.17 mm and 8.5 mm respectively. After giving rise to central, callosal and cortical branches, pericallosal artery terminated near the splenium of the corpus callosum or on the precuneus as the inferomedial parietal artery. Conclusion: Knowledge of the microvascular anatomy is indispensable and it is mandatory to be aware of the possible variations in the anomalies to minimize morbidity.

  20. 基于分段运动特性的空间目标检测算法%A Detection Algorithm of Space Target Based on Segment Movement Characteristics

    Institute of Scientific and Technical Information of China (English)

    田瑞琦; 鲍庆龙; 王丁禾; 陈曾平

    2014-01-01

    In order to improve the detection ability of space targets,we need to analyze the echo model and study the solution of range cell migration.In this paper,aiming at the range cell migration of space tar-gets,bistatic radar-target 3D model and echo model are built.The effect of target motion on range cell mi-gration is analyzed.A method based on segment movement characteristics is proposed to eliminate the influ-ence of high speed on range cell migration.A two-stage algorithm of velocity compensation is put forward, which has both high estimation precision and calculation speed.The international space station(ISS)is cho-sen as study obj ect for simulation,which verifies the validity and effectiveness of the proposed method and its good robust property.%为提高空间目标检测性能,需要分析目标回波模型,研究高速运动目标距离走动补偿方法。针对双基地雷达对空检测过程中可能出现的距离走动问题,建立双基地雷达目标三维模型和回波模型,分析了全过程中目标运动对距离走动的影响,提出了基于分段运动特性的目标检测方法。通过引入两级速度补偿算法,保证参数估计精度的同时提高计算速度。并以空间目标 ISS(International Space Station)为例进行仿真实验,验证算法的有效性和对噪声的鲁棒性。