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Dissertations / Theses on the topic 'Automated Segmentation Method'

Author: Grafiati

Published: 25 May 2024

Last updated: 19 July 2025

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1

Tran, Philippe. "Segmentation and characterization of cerebral white matter hyperintensities : application in individuals with multiple sclerosis and age-related pathologies." Electronic Thesis or Diss., Sorbonne université, 2022. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2022SORUS243.pdf.

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Les hyperintensités de la substance blanche (HSB) sont de plus en plus prises en compte dans le suivi clinique des personnes âgées et/ou des patients atteints de démences, et sont cruciales chez les patients atteints de Sclérose en Plaques (SEP). Des méthodes d'analyse ont été proposées pour aider à quantifier ces lésions à grande échelle, afin de mieux comprendre les mécanismes sous-jacents de ces pathologies. Cependant, à notre connaissance, il n'y a pas de consensus aujourd'hui sur la méthode à utiliser et aucune méthode n'est validée sur ces deux types de sujets. Cette thèse présente plusi

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Shan, Juan. "A Fully Automatic Segmentation Method for Breast Ultrasound Images." DigitalCommons@USU, 2011. https://digitalcommons.usu.edu/etd/905.

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Breast cancer is the second leading cause of death of women worldwide. Accurate lesion boundary detection is important for breast cancer diagnosis. Since many crucial features for discriminating benign and malignant lesions are based on the contour, shape, and texture of the lesion, an accurate segmentation method is essential for a successful diagnosis. Ultrasound is an effective screening tool and primarily useful for differentiating benign and malignant lesions. However, due to inherent speckle noise and low contrast of breast ultrasound imaging, automatic lesion segmentation is still a cha

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Vestergren, Sara, and Navid Zandpour. "Automatic Image Segmentation for Hair Masking: two Methods." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254258.

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We propose two different methods for image segmentation with the objective of marking contaminated regions in images from biochemical tests. The contaminated regions consists of thin hair or fibers and the purpose of this thesis is to eliminate the tedious task of masking the contaminated regions by hand by implementing automatic hair masking. Initially an algorithm based on Morphological Image Processing is presented, followed by solving the problem of pixelwise classification using a Convolutional Neural Network (CNN). Finally, the performance of each implementation is measured by comparing

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Benhabiles, Halim. "3D-mesh segmentation : automatic evaluation and a new learning-based method." Phd thesis, Université des Sciences et Technologie de Lille - Lille I, 2011. http://tel.archives-ouvertes.fr/tel-00834344.

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Dans cette thèse, nous abordons deux problèmes principaux, à savoir l'évaluation quantitative des algorithmes de segmentation de maillages ainsi que la segmentation de maillages par apprentissage en exploitant le facteur humain. Nous proposons les contributions suivantes : - Un benchmark dédié à l'évaluation des algorithmes de segmentation de maillages 3D. Le benchmark inclut un corpus de segmentations vérités-terrains réalisées par des volontaires ainsi qu'une nouvelle métrique de similarité pertinente qui quantifie la cohérence entre ces segmentations vérités-terrains et cel

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Sun, Felice (Felice Tzu-yun) 1976. "Integrating statistical and knowledge-based methods for automatic phonemic segmentation." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80127.

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Reavy, Richard Wilson. "Image segmentation for automatic target recognition : an investigation of a method of applying post-segmentation derived information to a secondary segmentation process." Thesis, University of Edinburgh, 1999. http://hdl.handle.net/1842/12840.

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A fundamental automatic target recognition (ATR) system can be composed of an object segmentation stage, followed by feature extraction from those objects produced by segmentation, and finally classification of these object features. The capability of such a system in terms of classification success is therefore limited not only by the quality of the feature extraction and classification methods used, but also by the quality of the initial object segmentation. In this thesis, a novel architecture is described which uses two stages of segmentation. This allows image features derived after a pri

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Arif, Omar. "Robust target localization and segmentation using statistical methods." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/33882.

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This thesis aims to contribute to the area of visual tracking, which is the process of identifying an object of interest through a sequence of successive images. The thesis explores kernel-based statistical methods, which map the data to a higher dimensional space. A pre-image framework is provided to find the mapping from the embedding space to the input space for several manifold learning and dimensional learning algorithms. Two algorithms are developed for visual tracking that are robust to noise and occlusions. In the first algorithm, a kernel PCA-based eigenspace representation is used.

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Li, Xiaolong. "Semi-Automatic Segmentation of Normal Female Pelvic Floor Structures from Magnetic Resonance Images." Cleveland State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=csu1265412807.

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Kolesov, Ivan A. "Statistical methods for coupling expert knowledge and automatic image segmentation and registration." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/47739.

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The objective of the proposed research is to develop methods that couple an expert user's guidance with automatic image segmentation and registration algorithms. Often, complex processes such as fire, anatomical changes/variations in human bodies, or unpredictable human behavior produce the target images; in these cases, creating a model that precisely describes the process is not feasible. A common solution is to make simplifying assumptions when performing detection, segmentation, or registration tasks automatically. However, when these assumptions are not satisfied, the results are unsatisf

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McCormick, Neil Howie. "Bayesian methods for automatic segmentation and classification of SLO and SONAR data." Thesis, Heriot-Watt University, 2001. http://hdl.handle.net/10399/452.

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Isensee, Fabian [Verfasser], and Benedikt [Akademischer Betreuer] Brors. "From Manual to Automated Design of Biomedical Semantic Segmentation Methods / Fabian Isensee ; Betreuer: Benedikt Brors." Heidelberg : Universitätsbibliothek Heidelberg, 2020. http://d-nb.info/1226541739/34.

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Dambreville, Samuel. "Statistical and geometric methods for shape-driven segmentation and tracking." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/22707.

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Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2008.<br>Committee Chair: Allen Tannenbaum; Committee Member: Anthony Yezzi; Committee Member: Marc Niethammer; Committee Member: Patricio Vela; Committee Member: Yucel Altunbasak.

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Militzer, Arne [Verfasser], and Joachim [Akademischer Betreuer] Hornegger. "Boosting Methods for Automatic Segmentation of Focal Liver Lesions / Arne Militzer. Gutachter: Joachim Hornegger." Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2015. http://d-nb.info/1075480299/34.

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Lidayová, Kristína. "Fast Methods for Vascular Segmentation Based on Approximate Skeleton Detection." Doctoral thesis, Uppsala universitet, Avdelningen för visuell information och interaktion, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-318796.

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Modern medical imaging techniques have revolutionized health care over the last decades, providing clinicians with high-resolution 3D images of the inside of the patient's body without the need for invasive procedures. Detailed images of the vascular anatomy can be captured by angiography, providing a valuable source of information when deciding whether a vascular intervention is needed, for planning treatment, and for analyzing the success of therapy. However, increasing level of detail in the images, together with a wide availability of imaging devices, lead to an urgent need for automated t

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Kaipala, J. (Jukka). "Automatic segmentation of bone tissue from computed tomography using a volumetric local binary patterns based method." Master's thesis, University of Oulu, 2018. http://urn.fi/URN:NBN:fi:oulu-201802101221.

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Segmentation of scanned tissue volumes of three-dimensional (3D) computed tomography (CT) images often involves—at least partially—some manual process, as there is no standardized automatic method. There is a need to develop fully automatic approaches, not only to improve the objectivity of the task, but also to increase the overall speed of the segmentation process. Here we extend a 3D local binary patterns (LBP) based trabecular bone segmentation method with adaptive local thresholding and additional segmentation parameters to make it more robust yet still perform adequately when compared to

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Hillis, Yingli, and Yingli Hillis. "Validation of a Semi-Automatic Cell Segmentation Method to the Manual Cell Counting Method on Identifying Proliferating Cells in 3-D Confocal Microscope Images." Thesis, The University of Arizona, 2017. http://hdl.handle.net/10150/626739.

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Sphere-forming assay is an in-vitro technique to assess the self-renewal and differentiation potential of a homogenous or heterogenous population of cells. This technique is commonly used in the stem cell and cancer biology fields to assess the ability of a cell that is capable of self-proliferation and differentiation. (Schmitt, 2011, Lombaert et al., 2008) To detect proliferative growth, Ki-67, a marker of proliferation, is used in immunofluorescence staining of sphere-forming cells. The current gold standard methodology to quantify cell proliferation is to manually count the cells on images

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Roura, Pérez Eloy. "Automated methods on magnetic resonance brain imaging in multiple sclerosis." Doctoral thesis, Universitat de Girona, 2016. http://hdl.handle.net/10803/394030.

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In this thesis, we have focused on the image pre-processing in order to enhance the image information. The main aspects of this enhancement rely on removing any image noise and correcting any intensity bias induced by the scanner. Besides, we also contributed with a new technique based on a multispectral, adaptive, region growing algorithm in order to segment the brain from the rest of the head. We include, as a pre-processing step, the image registration process, in which we proposed a novel pipeline by using information from multiple modalities to improve the results of this process. Furth

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Challa, Akkireddy. "Automatic Handwritten Digit Recognition On Document Images Using Machine Learning Methods." Thesis, Blekinge Tekniska Högskola, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-17656.

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Context: The main purpose of this thesis is to build an automatic handwritten digit recognition method for the recognition of connected handwritten digit strings. To accomplish the recognition task, first, the digits were segmented into individual digits. Then, a digit recognition module is employed to classify each segmented digit completing the handwritten digit string recognition task. In this study, different machine learning methods, which are SVM, ANN and CNN architectures are used to achieve high performance on the digit string recognition problem. In these methods, images of digit stri

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Escorcia, Gutierrez José. "Image Segmentation Methods for Automatic Detection of the Anatomical Structure of the Eye in People with Diabetic Retinopathy." Doctoral thesis, Universitat Rovira i Virgili, 2021. http://hdl.handle.net/10803/671543.

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Aquesta tesi s'emmarca dins del pla integral de prevenció precoç de la Retinopatia Diabètica (RD) posat en marxa pel govern espanyol seguint les recomanacions de l'Organització Mundial de la Salut de promoure iniciatives que consciencien sobre la importància de fer revisions oculars regulars entre les persones amb diabetis. Per tal de poder determinar el nivell de retinopatia diabètica cal localitzar i identificar diferents tipus de lesions a la retina. Per poder fer-ho, cal que primer s'eliminin de la imatge les estructures anatòmiques normals de l'ull (vasos sanguinis, disc òptic i fòvea

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Vernon, Zachary Isaac. "A comparison of automated land cover/use classification methods for a Texas bottomland hardwood system using lidar, spot-5, and ancillary data." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2744.

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Hast, Isak, and Asmelash Mehari. "Automating Geographic Object-Based Image Analysis and Assessing the Methods Transferability : A Case Study Using High Resolution Geografiska SverigedataTM Orthophotos." Thesis, Högskolan i Gävle, Samhällsbyggnad, GIS, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-22570.

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Geographic object-based image analysis (GEOBIA) is an innovative image classification technique that treats spatial features in an image as objects, rather than as pixels; thus resembling closer to that of human perception of the geographic space. However, the process of a GEOBIA application allows for multiple interpretations. Particularly sensitive parts of the process include image segmentation and training data selection. The multiresolution segmentation algorithm (MSA) is commonly applied. The performance of segmentation depends primarily on the algorithms scale parameter, since scale con

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Wang, Yan. "Etude de la méthode de Boltzmann sur réseau pour la segmentation d'anévrismes cérébraux." Thesis, Lyon, INSA, 2014. http://www.theses.fr/2014ISAL0078/document.

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L'anévrisme cérébral est une région fragile de la paroi d'un vaisseau sanguin dans le cerveau, qui peut se rompre et provoquer des saignements importants et des accidents vasculaires cérébraux. La segmentation de l'anévrisme cérébral est une étape primordiale pour l'aide au diagnostic, le traitement et la planification chirurgicale. Malheureusement, la segmentation manuelle prend encore une part importante dans l'angiographie clinique et elle est devenue couteuse en temps de traitement étant donné la gigantesque quantité de données générées par les systèmes d'imagerie médicale. Les méthodes de

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Arumuganainar, Ponnappan. "Automatic soft plaque detection from CTA." Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26690.

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Thesis (M. S.)--Biomedical Engineering, Georgia Institute of Technology, 2009.<br>Committee Chair: Tannenbaum, Allen; Committee Member: Skrinjar, Oskar; Committee Member: Yezzi, Anthony. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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Gloger, Oliver [Verfasser]. "Combined Applications of the Level Set Method with Multi-Step Recognition and Refinement Algorithms for Fully Automatic Organ and Tissue Segmentation in MRI Data / Oliver Gloger." Greifswald : Universitätsbibliothek Greifswald, 2012. http://d-nb.info/1022617842/34.

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Pavani, Sri-Kaushik. "Methods for face detection and adaptive face recognition." Doctoral thesis, Universitat Pompeu Fabra, 2010. http://hdl.handle.net/10803/7567.

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The focus of this thesis is on facial biometrics; specifically in the problems of face detection and face recognition. Despite intensive research over the last 20 years, the technology is not foolproof, which is why we do not see use of face recognition systems in critical sectors such as banking. In this thesis, we focus on three sub-problems in these two areas of research. Firstly, we propose methods to improve the speed-accuracy trade-off of the state-of-the-art face detector. Secondly, we consider a problem that is often ignored in the literature: to decrease the training time of the detec

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Lee, Chiu-Wen, and 李秋雯. "An Automated Method for Malaria Parasite Detection and Segmentation from Thin Blood Smear Image." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/44441282316855792954.

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碩士<br>國立中興大學<br>資訊科學與工程學系所<br>98<br>Malaria is an infectious parasitic disease which is widespread in Africa and South-East Asia. It is caused by a protozoan parasite of the genus Plasmodium. Since malaria parasites can be detected in the blood of infected patient, blood smear is commonly used to diagnose malaria under microscope. However, it is time-consuming and labor-intensive. Moreover, the experience of medical technologist has a great effect upon diagnostic accuracy. In this study, an automatic malaria parasite detector is proposed to perceive the malaria-infected erythrocytes from a blo

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Lin, Chun-yu, and 林淳郁. "Three stages automated pulmonary segmentation and RS based on WP-SVD method for classifying nodule." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/93867546957194390253.

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碩士<br>國立雲林科技大學<br>資訊管理系碩士班<br>99<br>Recently, high prevalence of lung cancer, more and more researcher concern about diagnosing pulmonary lesions in chest CT images. Chest computed tomography (CT) is a well-established tool, which is widely applied to related detection work. However, the great amount of CT scans of each patient still is a challenge for specialists. Hence, many literatures have proposed methods for automatic diagnosis by computer-aided detection (CAD) to assist artificial inspection. But there are some problems brought with those proposed methods, such as time-consuming work of

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Hung, Kai-Chun, and 洪愷均. "MRI Image Based Automatic Vertebrae Segmentation Method." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/70180157770959314085.

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碩士<br>國立中興大學<br>資訊管理學系所<br>102<br>This paper is based on SMRIVS method to refine the results of SMRIVS method by eliminating thecal sac, intervertebral disc and other tissues on a MRI image. The proposed method is divided into three stages. The first stage is preprocessing stage, which adjusts the intensities of the results of SMRIVS method for further use. The purpose of the second stage is to eliminate intervertebral disc and some adjacency darker tissues. Because the intensities of those parts are darker than those of the vertebra bone, local thresholding and monograph operators to eliminat

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Lai, Yi-Tung, and 賴奕同. "Automatic Video Object Segmentation Method with Predictive Extending Edge." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/77499525530311802290.

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碩士<br>國立中山大學<br>資訊工程學系研究所<br>92<br>Recently, for the new demands of nowadays multimedia system, such as video interaction, the MPEG-4 standard has been designed. In MPEG-4, because of those new demands of nowadays multimedia system the video stream can be divided into several video object planes ( VOPs ). Those VOPs can be separately encoded, stored, or transmitted. VOP is the basic interactive unit in MPEG-4 video stream, how to automatically or semi-automatically separate appropriate VOPs from an image sequence has become one of the most important issues for an MPEG-4 system, which is also t

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Chiou, Yan-Ru, and 邱彥儒. "Automatic Volume Quantification Method for ACM Image Segmentation Technique." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/74997237407295269881.

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碩士<br>中台醫護技術學院<br>醫學工程暨材料研究所<br>95<br>Recently, active contour model (ACM) algorithm has been widely used to perform image segmentation in many clinical imaging modalities. It has been proven to be an efficient and accurate imaging segmentation method to segment the region of interest in high noise or low contrast image. In addition to segment out the lesion contour, how to accurately quantify the volume of the lesion in an image is very important. The direct counting method has been used to quantify the volume of ACM segmented regions. Although the error of the direct counting method is quit

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Yeh, Chinson, and 葉清松. "A Dynamic Programming Based Automatic Nodule Image Segmentation Method." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/39206247516096756072.

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Cheng, WeiPing, and 鄭煒平. "A Method for Automatic Audio Segmentation in MPEG Movies." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/62494124763931311129.

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Jin-Jun, Huang, and 黃金璋. "A Dynamic Programming Based Semi-automatic Image Segmentation Method." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/55441208603700376531.

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HUANG, CHENG-HSIEN, and 黃政憲. "Deep Learning Based Automatic Organ Segmentation Method and Integrated Solution Applied in Radiotherapy." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/56kqm6.

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碩士<br>國立中正大學<br>資訊工程研究所<br>107<br>In the procedures of radiotherapy, delineating the organ at risk (OAR) is a time-consuming, laborious but still very important task, which is necessary to be done accurately. In the field of medical imaging analysis, the content of images has high complexity and variability. The traditional rule-based methods are often difficult to meet the clinical requirements. In this work, we study the deep learning segmentation techniques and apply them to clinical imaging systems. In the chapter of experimentation, we used public liver organ datasets, 3Dircadb, to verify

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Sun, Yu-Chiao, and 孫羽喬. "Fully Automatic Tumor Detection and Segmentation Based on Level-set Method Using Breast Sonography." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/22032793213424256772.

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碩士<br>國立臺灣大學<br>生醫電子與資訊學研究所<br>100<br>In recent years, the computer-aided diagnostic (CAD) is developed gradually providing second opinion for radiologists'' diagnosis. The CAD system should produce well segmentation result of tumor to precisely evaluate the tumor size, and the tumor can be further classified into benign and malignant by the extracted feature of shape. Concerning the previous techniques of the semi-automatic segmentation (e.g., level-set), the seed usually needs to be manually initialized at the appropriate position for the better segmentation result. Besides, most o

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Zhan, Yi-Tien, and 詹益典. "Automatic segmentation of the liver based on improved Level set method in CT images." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/sm366h.

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碩士<br>國立臺中科技大學<br>資訊管理系碩士班<br>102<br>This study proposes a new method for medical image segmentation, automatic Level set cutting method, the liver from computed tomography (CT) images quickly and accurately cut out. Automatic liver cut method of this study will be divided into a preliminary outline of the liver and liver Level set to detect cut. Liver preliminary outline detection system using a dedicated medical images in DICOM format Hounsfield Unit (HU), extracting the liver window width and window level to set the threshold, and morphological techniques to complete the initial liver conto

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Lin, Xiao-Yu, and 林曉郁. "The Automatic Segmentation of Gray Matter of the Brain MR Images with Level-Set Method." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/53634786671629451553.

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碩士<br>國立中興大學<br>應用數學系所<br>94<br>In the paper proposes a New Adaptive Threshold Level Set Model. The model is based on the methodology of Active Contours Without Edges . The proposed method is then applied to the segmentation of gray matter in brain MR images. There are two threshold values, lower threshold and upper threshold, to be decided for locating the contours of the gray matter of the brain MR images. The threshold values are determined by Fuzzy C-Means Algorithm. By combining segmentation of 134 planar MR brain gray images. A three-dimensional model of the brain gray matter has been s

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Pereira, Sérgio Rafael Mano. "Automatic segmentation and classification of brain tumors based on multisequence MRI images with deep learning methods." Doctoral thesis, 2019. http://hdl.handle.net/1822/65616.

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Programa de Doutoramento em Informática (MAP-i) das Universidades do Minho, de Aveiro e do Porto<br>Gliomas are the most common primary brain tumors. Unfortunately, these neoplasms hold the worst prognosis among all brain tumors, as well. They can be broadly categorized as low or high grade gliomas. Magnetic Resonance Imaging is the standard imaging technique for their assessment. Using it, physicians can extract measurements that are crucial for treatment planning and follow-up. Notwithstanding, manual segmentation is time-demanding and prone to variability. Also, tumor grading by biopsy

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Hou, Chun-Han, and 侯淳瀚. "Evaluation of the correlation between bone mineral density and core muscle area using semi-automatic image segmentation method." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/56755076382181850977.

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碩士<br>高雄醫學大學<br>醫學影像暨放射科學系碩士在職專班<br>105<br>Background and Objective: Magnetic Resonance Imaging (MRI) has been previously utilized to evaluate the extent of muscle mass loss by manual drawing of muscle area which however is prone to subjective errors. The purpose of this study was to investigate the correlation between the bone mineral density (BMD) obtained from dual-energy X-ray absorptiometry (DXA) and the muscle area obtained from MRI using semi-automatic segmentation. Materials and Methods: This study reviewed 85 postmenopausal women who were older than 50 years old and had undergone bot

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Chiu, Chien-Chin, and 邱建欽. "An Automatic Counting Technique for Small Size Pests Using Marker Controlled Watershed and Mean Shift Segmentation Methods." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/04593550580000009900.

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Hauptfleisch, Andries Carl. "Automatic road network extraction from high resolution satellite imagery using spectral classification methods." Diss., 2010. http://hdl.handle.net/2263/26866.

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Road networks play an important role in a number of geospatial applications, such as cartographic, infrastructure planning and traffic routing software. Automatic and semi-automatic road network extraction techniques have significantly increased the extraction rate of road networks. Automated processes still yield some erroneous and incomplete results and costly human intervention is still required to evaluate results and correct errors. With the aim of improving the accuracy of road extraction systems, three objectives are defined in this thesis: Firstly, the study seeks to develop a flexible

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Chien, Chih-Hung, and 簡志宏. "A new DCT-based image segmentation method for automatic defect detection on an object embedded in noisy low-contrast unbalanced background." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/6jk45g.

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碩士<br>國立臺北科技大學<br>自動化科技研究所<br>97<br>This article presents an innovative image segmentation method to extract an object underlying defect detection from its background image. 2-D automatic optical inspection (AOI) technology for defect detection and classification has played a vital role for in-situ manufacturing industrial sectors nowadays. Image segmentation is a crucial step to extract component information from its neighboring background. Due to potential complexity in such an image processing operation, considerable challenges are crucially encountered in establishing a robust approach. In

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Niu, Tsai Wen, and 鈕采紋. "Automatic tumor segmentation of ultra-sound breast images using a distance-regularized level-set evolution method with initial contour based on morphology." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/40768096342961763593.

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碩士<br>國立清華大學<br>電機工程學系<br>104<br>Lesion segmentation for breast ultrasound images has been studied by many people, but it is hard to achieve using traditional edge detection because ultrasound images don’t have sharp contours and exist a lot of noise. In this thesis, we propose an automatic segmentation method for breast ultrasound images which combines morphological image processing and distance-regularized level-set evolution method (DRLSE), and improve combined DRSLE (cDRLSE) proposed by Yung-Hsuan Hsu. The most serious problem of cDRLSE is that it spend a lot of time on obtaining initial c

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Wu, Jia-Bao, and 吳家寶. "Automatic segmentation of different functional groups of lower extremity muscle on MRI : Combination of mathematical morphology and anatomy knowledge methods." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/06002016220192743442.

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碩士<br>中原大學<br>電機工程研究所<br>98<br>Segmentation of magnetic resonance (MR) images has numerous clinical applications: Being an auxiliary tool in diagnosis and treatment, making epidemiological statistics easier to carry on, being an important step in data analysis of all kinds of medical researches. However, most of the segmentation has been done manually or at most semi-automatically. The process is time- and energy-consuming and difficult to be standardized. Automatic segmentation algorithms of MR images for some of the body parts, such as the brain, have been developed with success. The muscula

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Lopes, Vasco Miguel Graça. "Seeded region growing methods for automatic upwelling detection from sea surface temperature images." Master's thesis, 2015. http://hdl.handle.net/10362/16088.

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Hsieh, Hsun, and 謝. 洵. "Automatic tumor segmentation of breast ultra-sound images using a distance-regularized level-set evolution method with initial contour obtained by guided image filter, L0 gradient minimization smoothing pre-processing, and morphological features." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/t6z6cs.

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碩士<br>國立清華大學<br>電機工程學系所<br>105<br>Due to the speckle noise and low contrast in breast ultrasound images, it is hard to locate the contour of the tumor by using a single method. In this thesis, a new method for finding an initial contour is proposed, which can improve the result of DRLSE on the segmentation of BUS images. The new method focuses on improving the algorithm proposed by Tsai-Wen Niu, which is a way to search an initial contour based on the local minimum in the images. When the BUS images contain calcification, it is possible to fail in searching of initial contour through such algo

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(9187466), Bharath Kumar Comandur Jagannathan Raghunathan. "Semantic Labeling of Large Geographic Areas Using Multi-Date and Multi-View Satellite Images and Noisy OpenStreetMap Labels." Thesis, 2020.

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<div>This dissertation addresses the problem of how to design a convolutional neural network (CNN) for giving semantic labels to the points on the ground given the satellite image coverage over the area and, for the ground truth, given the noisy labels in OpenStreetMap (OSM). This problem is made challenging by the fact that -- (1) Most of the images are likely to have been recorded from off-nadir viewpoints for the area of interest on the ground; (2) The user-supplied labels in OSM are frequently inaccurate and, not uncommonly, entirely missing; and (3) The size of the area covered on the gro

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