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Relevant bibliographies by topics / Breast Segmentation / Dissertations / Theses

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Dissertations / Theses on the topic 'Breast Segmentation'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Pons, Rodríguez Gerard. "Computer-aided lesion detection and segmentation on breast ultrasound." Doctoral thesis, Universitat de Girona, 2014. http://hdl.handle.net/10803/129453.

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This thesis deals with the detection, segmentation and classification of lesions on sonography. The contribution of the thesis is the development of a new Computer-Aided Diagnosis (CAD) framework capable of detecting, segmenting, and classifying breast abnormalities on sonography automatically. Firstly, an adaption of a generic object detection method, Deformable Part Models (DPM), to detect lesions in sonography is proposed. The method uses a machine learning technique to learn a model based on Histogram of Oriented Gradients (HOG). This method is also used to detect cancer lesions directly,

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2

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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3

Al-Roubaie, Zahra. "Human breast images : segmentation, analysis and conversion to electrical parameter profiles for Semcad-X electromagnetic simulator." Thesis, McGill University, 2008. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=116044.

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Electrical parameter profiles of human breast images can be used to simulate and analyze the anticipated effects on tissue from its interaction with electromagnetic fields involved in the cancer treatment exposure. In part, the success of this approach depends on the accuracy and precision in identifying the different tissue types. In this work, we propose two methods of segmenting human breast images with malignant tumors. The first method of algorithmic partitioning of the image involves manual color-edge contouring of the tissues using a cursor and subsequent identification of the tissue ty

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4

von, Lavante Etienne. "Segmentation and sizing of breast cancer masses with ultrasound elasticity imaging." Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:81225f61-6b83-405b-aed5-17b316ed586a.

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Uncertainty in the sizing of breast cancer masses is a major issue in breast screening programs, as there is a tendency to severely underestimate the sizing of malignant masses, especially with ultrasound imaging as part of the standard triple assessment. Due to this issue about 20% of all surgically treated women have to undergo a second resection, therefore the aim of this thesis is to address this issue by developing novel image analysis methods. Ultrasound elasticity imaging has been proven to have a better ability to differentiate soft tissues compared to standard B-mode. Thus a novel seg

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Rojas, Dominguez Alfonso. "Automated detection, segmentation and classification of breast masses in digitised mammograms." Thesis, University of Liverpool, 2007. http://livrepository.liverpool.ac.uk/375/.

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A method for automatic detection of mammographic masses is presented. As part of this method, an enhancement algorithm is proposed that improves image contrast based on local statistical measures of the mammograms. After enhancement, regions are segmented via thresholding at multiple levels, and a set of features is computed from each of the segmented regions. A region-ranking system is also presented that identifies the regions most likely to represent abnormalities based on the features computed. The method was tested on 57 mammographic images of masses and achieved a sensitivity of 80% at 2

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6

Kwok, Sze Man Simon. "Attribute-driven segmentation and analysis of mammograms." University of Western Australia. Centre for Intelligent Information Processing Systems, 2005. http://theses.library.uwa.edu.au/adt-WU2005.0010.

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[Truncated abstract] In this thesis, we introduce a mammogram analysis system developed for the automatic segmentation and analysis of mammograms. This original system has been designed to aid radiologists to detect breast cancer on mammograms. The system embodies attribute-driven segmentation in which the attributes of an image are extracted progressively in a step-by-step, hierarchical fashion. Global, low-level attributes obtained in the early stages are used to derive local, high-level attributes in later stages, leading to increasing refinement and accuracy in image segmentation and anal

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7

Masek, Martin. "Hierarchical segmentation of mammograms based on pixel intensity." University of Western Australia. School of Electrical, Electronic and Computer Engineering, 2004. http://theses.library.uwa.edu.au/adt-WU2003.0033.

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Mammography is currently used to screen women in targeted risk classes for breast cancer. Computer assisted diagnosis of mammograms attempts to lower the workload on radiologists by either automating some of their tasks or acting as a second reader. The task of mammogram segmentation based on pixel intensity is addressed in this thesis. The mammographic process leads to images where intensity in the image is related to the composition of tissue in the breast; it is therefore possible to segment a mammogram into several regions using a combination of global thresholds, local thresholds and high

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8

Ball, John E. "Three stage level set segmentation of mass core, periphery, and spiculations for automated image analysis of digital mammograms." Diss., Mississippi State : Mississippi State University, 2007. http://sun.library.msstate.edu/ETD-db/ETD-browse/browse.

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9

Massich, Joan. "Segmentation d'objets déformables en imagerie ultrasonore." Thesis, Dijon, 2013. http://www.theses.fr/2013DIJOS090/document.

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Le cancer du sein est le type de cancer le plus répandu, il est la cause principale de mortalité chez les femmes aussi bien dans les pays occidentaux que dans les pays en voie de développement. L'imagerie médicale joue un rôle clef dans la réduction de la mortalité du cancer du sein, en facilitant sa première détection par le dépistage, le diagnostic et la biopsie guidée. Bien que la Mammographie Numérique (DM) reste la référence pour les méthodes d'examen existantes, les échographies ont prouvé leur place en tant que modalité complémentaire. Les images de cette dernière fournissent des inform

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10

Tardy, Mickael. "Deep learning for computer-aided early diagnosis of breast cancer." Thesis, Ecole centrale de Nantes, 2021. http://www.theses.fr/2021ECDN0035.

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Le cancer du sein est un des plus répandus chez la femme. Le dépistage systématique permet de baisser le taux de mortalité mais crée une charge de travail importante pour les professionnels de santé. Des outils d’aide au diagnostic sont conçus pour réduire ladite charge, mais un niveau de performance élevé est attendu. Les techniques d’apprentissage profond peuvent palier les limitations des algorithmes de traitement d’image traditionnel et apporter une véritable aide à la décision. Néanmoins, plusieurs verrous technologiques sont associés à l’apprentissage profond appliqué à l’imagerie du sei

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11

Malhaire, Caroline. "Optimization of the Prediction of Complete Response to Neoadjuvant Chemotherapy in Breast Cancer by Breast MRI : Contributions of Semantic Descriptors, Radiomics, and Segmentation Methods." Electronic Thesis or Diss., université Paris-Saclay, 2025. http://www.theses.fr/2025UPAST006.

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La chimiothérapie néoadjuvante (CNA) est une stratégie thérapeutique devenue centrale pour les cancers du sein agressifs et localement avancés. L'obtention d'une réponse pathologique complète (pCR), définie comme une réponse tumorale complète au niveau du sein et de l'aisselle est associée à une amélioration de la survie, notamment dans les cancers du sein de type triple négatif et HER2-positif. Cette stratégie permet d’adapter la prise en charge à la réponse tumorale, les traitements d’escalade permettant une amélioration de la survie des patientes en réponse incomplète. La dissection axillai

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12

Samala, Ravi K. "Efficient suspicious region segmentation algorithm for computer aided diagnosis of breast cancer based on tomosynthesis imaging." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001800.

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13

Massich, i. Vall Joan. "Deformable object segmentation in ultra-sound images." Doctoral thesis, Universitat de Girona, 2013. http://hdl.handle.net/10803/128329.

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This thesis analyses the current strategies to segment breast lesions in Ultra-Sound (US) data and proposes a fully automatic methodology for generating accurate segmentations of breast lesions in US data with low false positive rates. The proposed approach targets the segmentation as a minimization procedure for a multi-label probabilistic framework that takes advantage of min-cut/max- flow Graph-Cut (GC) minimization for inferring the appropriate label from a set of tissue labels for all the pixels within the target image. The image is divided into contiguous regions so that all the pixels b

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Swathanthira, Kumar Murali Murugavel M. "Magnetic Resonance Image segmentation using Pulse Coupled Neural Networks." Digital WPI, 2009. https://digitalcommons.wpi.edu/etd-dissertations/280.

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The Pulse Couple Neural Network (PCNN) was developed by Eckhorn to model the observed synchronization of neural assemblies in the visual cortex of small mammals such as a cat. In this dissertation, three novel PCNN based automatic segmentation algorithms were developed to segment Magnetic Resonance Imaging (MRI) data: (a) PCNN image 'signature' based single region cropping; (b) PCNN - Kittler Illingworth minimum error thresholding and (c) PCNN -Gaussian Mixture Model - Expectation Maximization (GMM-EM) based multiple material segmentation. Among other control tests, the proposed algorithms wer

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Jiménez, Garay Gabriel Alexandro. "Deep Learning for Semantic Segmentation versus Classification in Computational Pathology: Application to mitosis analysis in Breast Cancer grading." Master's thesis, Pontificia Universidad Católica del Perú, 2019. http://hdl.handle.net/20.500.12404/13969.

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Existing computational pathology approaches did not allow, yet, the emergence of effective/efficient computer-aided tools used as a second opinion for pathologists in the daily practice. Focusing on the case of computer-based qualification for breast cancer diagnosis, the present article proposes two deep learning architectures to efficiently and effectively detect and classify mitosis in a histopathological tissue sample. The first method consisted of two parts, entailing a preprocessing of the digital histological image and a free-handcrafted-feature Convolutional Neural Network (CNN) used f

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16

Oliver, i. Malagelada Arnau. "Automatic mass segmentation in mammographic images." Doctoral thesis, Universitat de Girona, 2007. http://hdl.handle.net/10803/7739.

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Aquesta tesi està emmarcada dins la detecció precoç de masses, un dels símptomes més clars del càncer de mama, en imatges mamogràfiques. Primerament, s'ha fet un anàlisi extensiu dels diferents mètodes de la literatura, concloent que aquests mètodes són dependents de diferent paràmetres: el tamany i la forma de la massa i la densitat de la mama. Així, l'objectiu de la tesi és analitzar, dissenyar i implementar un mètode de detecció robust i independent d'aquests tres paràmetres. Per a tal fi, s'ha construït un patró deformable de la massa a partir de l'anàlisi de masses reals i, a continuació,

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Irshad, Humayun. "Automated Mitosis Detection in Color and Multi-spectral High-Content Images in Histopathology : Application to Breast Cancer Grading in Digital Pathology." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENM007/document.

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La gradation de lames de biopsie fournit des informations pronostiques essentielles pour le diagnostic et le traitement. La détection et le comptage manuel des mitoses est un travail fastidieux, sujet à des variations inter-et intra- observateur considérables. L'objectif principal de cette thèse de doctorat est le développement d'un système capable de fournir une détection des mitoses sur des images provenant de différents types de scanners rapides automatiques, ainsi que d'un microscope multispectral. L'évaluation des différents systèmes proposés est effectuée dans le cadre du projet MICO (MI

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RIYAHI, ALAM MOHAMAD SADEGH. "Preoperative Systems for Computer Aided Diagnosis based on Image Registration: Applications to Breast Cancer and Atherosclerosis." Doctoral thesis, Politecnico di Torino, 2015. http://hdl.handle.net/11583/2592170.

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Computer Aided Diagnosis (CAD) systems assist clinicians including radiologists and cardiologists to detect abnormalities and highlight conspicuous possible disease. Implementing a pre-operative CAD system contains a framework that accepts related technical as well as clinical parameters as input by analyzing the predefined method and demonstrates the prospective output. In this work we developed the Computer Aided Diagnostic System for biomedical imaging analysis of two applications on Breast Cancer and Atherosclerosis. The aim of the first CAD application is to optimize the registration str

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19

Geeraert, Nausikaa. "Evaluation quantitative de tissu fibroglandulaire pour l'estimation de l'énergie absorbée différenciée par tissu en tomosynthèse du sein." Thesis, Paris, ENST, 2014. http://www.theses.fr/2014ENST0060/document.

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Cette thèse avait deux buts principaux : a) l'implémentation et l'amélioration d'une méthode de calcul de densité volumique du sein (VBD), et b) la proposition d'une mesure d'irradiation utilisable pour l'évaluation du risque individuel en mammographie avec une méthode pour l'estimer. La densité du sein est connue comme indicateur de risque du cancer. Une méthode de quantification objective de la VBD a été développée, à partir d'approches existantes, et améliorée. La méthode a été implémentée pour deux systèmes de mammographie. Elle repose sur l'étalonnage du système de mammographie et la chaî

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Al-Osta, Husam E. I. "Detection of breast cancer microcalcifications in digitized mammograms : developing segmentation and classification techniques for the processing of MIAS database mammograms based on the wavelet decomposition transform and support vector machines." Thesis, University of Bradford, 2010. http://hdl.handle.net/10454/4429.

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Mammography is used to aid early detection and diagnosis systems. It takes an x-ray image of the breast and can provide a second opinion for radiologists. The earlier detection is made, the better treatment works. Digital mammograms are dealt with by Computer Aided Diagnosis (CAD) systems that can detect and analyze abnormalities in a mammogram. The purpose of this study is to investigate how to categories cropped regions of interest (ROI) from digital mammogram images into two classes; normal and abnormal regions (which contain microcalcifications). The work proposed in this thesis is divided

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Tao, Wang. "Adapting multiple datasets for better mammography tumor detection." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231867.

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In Sweden, women of age between of 40 and 74 go through regular screening of their breasts every 18-24 months. The screening mainly involves obtaining a mammogram and having radiologists analyze them to detect any sign of breast cancer. However reading a mammography image requires experienced radiologist, and the lack of radiologist reduces the hospital's operating efficiency. What's more, mammography from different facilities increases the difficulty of diagnosis. Our work proposed a deep learning segmentation system which could adapt to mammography from various facilities and locate the posi

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CORDEIRO, Filipe Rolim. "Desenvolvimento de um mecanismo semi-supervisionado para segmentação de tumores em imagens de mamografia digital." Universidade Federal de Pernambuco, 2015. https://repositorio.ufpe.br/handle/123456789/17237.

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Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-07-01T12:22:19Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Tese_Filipe_Cordeiro.pdf: 19608976 bytes, checksum: a0ff2fa1256af4323f10bfcbb3df974d (MD5)<br>Made available in DSpace on 2016-07-01T12:22:19Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Tese_Filipe_Cordeiro.pdf: 19608976 bytes, checksum: a0ff2fa1256af4323f10bfcbb3df974d (MD5) Previous issue date: 2015-12-16<br>De acordo com a Organização Mundi

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Geeraert, Nausikaa. "Evaluation quantitative de tissu fibroglandulaire pour l'estimation de l'énergie absorbée différenciée par tissu en tomosynthèse du sein." Electronic Thesis or Diss., Paris, ENST, 2014. http://www.theses.fr/2014ENST0060.

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Cette thèse avait deux buts principaux : a) l'implémentation et l'amélioration d'une méthode de calcul de densité volumique du sein (VBD), et b) la proposition d'une mesure d'irradiation utilisable pour l'évaluation du risque individuel en mammographie avec une méthode pour l'estimer. La densité du sein est connue comme indicateur de risque du cancer. Une méthode de quantification objective de la VBD a été développée, à partir d'approches existantes, et améliorée. La méthode a été implémentée pour deux systèmes de mammographie. Elle repose sur l'étalonnage du système de mammographie et la chaî

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Fourcade, Constance. "Suivi de l'évolution du cancer du sein métastasé via le recalage et la segmentation d'images TEP en utilisant des réseaux entraînés et non-entraînés." Thesis, Ecole centrale de Nantes, 2022. http://www.theses.fr/2022ECDN0029.

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Le cancer du sein métastasé nécessite un suivi régulier. Au cours du traitement, des images de TEP- scan sont régulièrement acquises puis interprétées selon des recommandations telles que PERCIST pour décider d’un éventuel ajustement thérapeutique. Cependant, PERCIST se concentre seulement sur la lésion présentant l’activité tumorale la plus élevée. L’objectif de cette thèse est de développer des outils permettant de prendre en compte toutes les zones actives à l’aide du TEP-scan, afin de suivre au mieux l’évolution du cancer du sein. Notre première contribution est une méthode pour la segment

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SILVA, Luis Claudio de Oliveira. "Método de detecção de massas em mamas densas usando análise de componentes independentes." Universidade Federal do Maranhão, 2017. http://tedebc.ufma.br:8080/jspui/handle/tede/1897.

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Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-09-04T18:08:18Z No. of bitstreams: 1 LuisClaudioSilva.pdf: 4393489 bytes, checksum: 5c3cb715bd7992ba1cc5380c1a940f32 (MD5)<br>Made available in DSpace on 2017-09-04T18:08:18Z (GMT). No. of bitstreams: 1 LuisClaudioSilva.pdf: 4393489 bytes, checksum: 5c3cb715bd7992ba1cc5380c1a940f32 (MD5) Previous issue date: 2017-07-27<br>Breast cancer is the second type of cancer that most a ects women in the world, losing only for non melanoma skin cancer. Breast density can hinder the location of masses, especially in early stages. In this w

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Marcomini, Karem Daiane. "Caracterização de lesões em imagens digitais de ultrassonografia e elastografia da mama utilizando técnicas inteligentes." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/18/18152/tde-08122017-113952/.

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Muitos procedimentos vêm sendo desenvolvidos para auxiliar no diagnóstico precoce do câncer de mama. Devido a subjetividade na interpretação de imagens, os sistemas de diagnóstico auxiliado por computador (CADx) têm oferecido ao especialista uma segunda opinião mais precisa e confiável. Nesse propósito, essa pesquisa apresenta uma metodologia de investigação da potencialidade diagnóstica de um sistema computacional na classificação de achados suspeitos em imagens de ultrassom modo-B e de elastografia da mama. A base de dados foi constituída por 31 lesões malignas e 52 benignas e um conjunto ad

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McGarry, Gregory John. "Model-based mammographic image analysis." Thesis, Queensland University of Technology, 2002.

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Elseidi, Mohammed. "Quantile regression-based seasonal adjustment." Doctoral thesis, Università degli studi di Padova, 2019. http://hdl.handle.net/11577/3423191.

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Time series of different nature might be characterised by the presence of deterministic and/or stochastic seasonal patterns. By seasonality, we refer to periodic fluctuations affecting not only the mean but also the shape, the dispersion and in general the density of the variable of interest over time. Using traditional approaches for seasonal adjustment might not be efficient because they do not ensure, for instance, that the adjusted data are free from periodic behaviours in, say, higher-order moments. We introduce a seasonal adjustment method based on quantile regression that is capable of

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Carreiro, António Mesquita dos Santos Marques. "Anatomy Segmentation of Breast Ultrasound images." Master's thesis, 2019. https://hdl.handle.net/10216/123037.

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Breast cancer is one of the most common cancers in women, affecting hundreds of women. Even though the detection of cancer has been largely studied, the decision of which strategy to take concerning oncoplastic surgery still relies almost exclusively on the surgeon's perception of post-surgical aesthetic result, which sometime leads to unsatisfactory outcomes. In order to empower the patients on the joint decision process there needs to exist a better communication between the parts. This can be achieved by developing medical grade 3D models of the breast and explaining better the surgical opt

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Liu, Chia-Hsin, and 劉佳欣. "Breast Parenchyma Segmentation and Bias Correction of Whole Breast Ultrasound Imaging." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/25934317840149352545.

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碩士<br>臺灣大學<br>醫學工程學研究所<br>98<br>According to the statistic from Department of Health, breast cancer is one of the leading causes of cancer death among Taiwanese women. Medical research has shown that women with higher breast density have higher incidence of breast cancer. Therefore, estimation of breast density is worth paying more attention. Ultrasound imaging is one of the most important imaging modalities to diagnose breast cancer. Three-dimensional (3D) whole breast ultrasound imaging has been intensively studied, as it provides completed 3D anatomy of breast, which is helpful for diagnosi

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Huang, Pei-Shan, and 黃霈姍. "Automatic Lesion Segmentation in Breast DCE-MRI." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/v8x7u4.

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碩士<br>慈濟大學<br>醫學資訊學系碩士班<br>105<br>Breast cancer is a common cancer in women. Early detection and treatment is the key to cure. Dedicated breast MRI system with advanced imaging technology is an effective tool, which delivers high sensitive and resolution. However, the big image data analysis is time consuming and depends on reader expertise. To discover cancer disease as early as possible in a support role, this study proposed an automatic method to segment suspicious breast lesions without any ROI given or user interaction. Firstly, the noise was removed to get initial breast tissue by a thre

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Gallego, Cristina. "Automatic 3D Segmentation of the Breast in MRI." Thesis, 2011. http://hdl.handle.net/1807/30619.

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Breast cancer is currently the most common diagnosed cancer among women and a significant cause of death. Breast density is considered a significant risk factor and an important biomarker influencing the later risk of breast cancer. Therefore, ongoing epidemiological studies using MRI are evaluating quantitatively breast density in young women. One of the challenges is segmenting the breast in order to calculate total breast volume and exclude non-breast surrounding tissues. This thesis describes an automatic 3D breast volume segmentation based on 3D local edge detection using phase congruency

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Liu, Tzung-Shin, and 呂宗鑫. "Texture Based Segmentation of Breast Tumors in Ultrasound Images." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/82421045063308231500.

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碩士<br>元智大學<br>資訊管理學系<br>97<br>In this study, we propose an automatic texture based segmentation method for breast tumors in ultrasound images. Image processing techniques are used to segment the contour of breast tumors to assist doctors for further differential diagnosis. The correlation coefficients were selected as the main texture feature to represent the characteristics breast tumor. The modified colony algorithm with optimum searching stratagem was then used to find the relationship among pixels. The inverse mapping and region classification were used to classify the position of pixels.

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Kuo, Li-Yan, and 郭立彥. "Shape-Based Level Set Method for Breast Mass Segmentation." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/56817167316395880093.

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碩士<br>長榮大學<br>資訊管理學系碩士班<br>99<br>Breast cancer is the most common type of cancer in the females and breast masses generally present as the major symptom of breast cancer. In order to assist radiologists in detecting masses in the early stage of breast cancer, it is highly desirable to develop a reliable computer aided diagnostic system as an assistant. This paper presents a shape-based level set method for mass segmentation on the breast magnetic resonance imaging (MRI).Because the level set model proposed by Chan and Vese can not work well on the breast mass segmentation, this paper adds the

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Wu, Guan-Ze, and 吳冠澤. "Three-Dimensional Segmentation for Fibroglandular Tissues on Breast MRI." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/2kh5yz.

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碩士<br>東海大學<br>資訊工程學系<br>106<br>Breast cancer is the most common cancer in woman. The development and progress of medical research, if early detection and treatment can improve the cure rate of breast cancer. There are many ways to diagnose breast tumors in medical imaging tools, such as mammography, ultrasonography and magnetic resonance imaging (MRI). In computer aided analysis of MRI, contouring of breast fibroglandular region is an important step. Accurate volume of fibroglandular tissue and breast density should help physicians to effective predict the risk of cancer. As breast MRI becomes

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Chang, Shun-Chan, and 張順展. "Three-dimensional region growing segmentation for breast tumor on sonography." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/62964183381682207283.

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碩士<br>東海大學<br>資訊工程學系<br>98<br>Breast malignant and benign tumor exist discrepancy in shape and size on sonography, information about shape and size provided by tumor’s contour is important in clinical diagnosis. Due to ultrasound image includes noises and tissue texture, clinical diagnosis must be highly depends on expertise experience. However, manually sketch the three-dimensional (3D) breast tumor contour is a time-consuming and complicated task. Automatic contouring which provided the similar contour with manual sketch of the breast tumor in the ultrasonic images might assist physicians in

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LIU, YZU-YU, and 劉子堉. "Precise Three-Dimensional Segmentation for Breast Region on Magnetic Resonance Imaging." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/esjzrx.

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碩士<br>東海大學<br>資訊工程學系<br>104<br>Contouring of breast region is an important step in computer aided analysis of magnetic resonance imaging (MRI). The volume of breast region is helpful to physician in surgical operation. During the operation, physicians have to estimate the volume of the breast they removed by experience, then put the same weight of normal saline bag or silica gel in human body. Automatic contouring for breast region may assist physicians in making correct decision at surgical operation. However, automatic segmentation is difficult due to there are several resembled tissues arou

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Zheng, Sheng-Wen, and 鄭勝文. "A Dynamic contours-Based Breast Tumors Segmentation Algorithm for Digital Mammograms." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/52792533085174787068.

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碩士<br>國立勤益科技大學<br>電子工程系<br>101<br>Breast cancer is one of the most common cancers in women. Screening and early detection is essential for better outcomes in breast cancer treatment. For screening of breast cancer, mammography has been utilized widely in various clinical settings for many years. With regards to the mammogram processing, extracting the region of interest (the breast tumour) accurately from a mammogram is one kernel stage of the mammogram processing. It significantly influences the overall analysis accuracy and processing speed of the mammogram. The main goal of this paper is to

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Lin, Yu-Chih, and 林昱志. "Breast Tumor Segmentation Based on Level-set Method in 3D Sonography." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/46013067278669247023.

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碩士<br>東海大學<br>資訊工程學系<br>101<br>Malignant and benign breast tumor present differently in their shape and size on sonography. Morphological information provided by the contour of tumor is important in clinical diagnosis. However, ultrasound images contain noises and tissue texture; clinical diagnosis thus highly depends on the experience of physicians. The manual way to sketch three-dimensional (3D) breast tumor contours is a time-consuming and complicated task. Automatic contouring provided the similar breast tumor contour by manual sketch in the ultrasonic images, that might assist physicians

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Lin, Wan-Ting, and 林琬婷. "Breast Tumor Segmentation on Ultrasonography Based on 3D Region Growing Method." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/89861886175712856976.

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碩士<br>東海大學<br>資訊工程學系<br>103<br>Breast cancer is the most common cancer in the woman. There is an upward trend in the number of such cases in the past years. Early diagnosis and early treatment is the most effective way of reducing mortality caused by breast cancer. Ultrasound is the common examination technology because of fast, cheap and noninvasive. The difficult part is that there are many noises and speckles on the ultrasonic images. Malignant and benign breast tumors are present different shape and size, thus this study propose a robust segmentation method to assist the physician on conto

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Lin, Xun-Yao, and 林勳耀. "Contour Detection for the Breast Tumor in Ultrasonic Images Using Watershed Segmentation." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/4wc3r9.

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碩士<br>朝陽科技大學<br>資訊管理系碩士班<br>92<br>Automatic contour finding for breast tumor in medical ultrasound (US) im-aging may assist physicians without experience in making a correct diagnosis. The purpose of this thesis combined the advantages of texture analysis tech-niques and watershed segmentation to extract precise contour of breast tumor from ultrasound images. Watershed transformation is a very reliable, automatic and unsupervised segmentation technique. However, the ultrasonic images al-ways include lots of noise and irregular texture. It usually generates over-segmentation regions after water

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Chiang, Hsin-Hong, and 江昕鴻. "Cell-Based Graph Cut for Segmentation of 2D/3D Sonographic Breast Images." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/63418479540837644873.

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碩士<br>國立臺灣大學<br>醫學工程學研究所<br>97<br>In sonographic breast lesions image, circling the lesion part is the complicated and time consuming work, moreover it should be done by experienced doctors or experts. In three dimensional sonographic breast lesions image, circling the lesion part becomes more complicated and more procedure. Therefore, circling the lesion part by computer aided diagnosis(CAD) is not only simplified the circling work and saving the doctor’s precious time, but also providing more medical information by computer. Segmenting the medical image by graph theory has been used and deve

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Li, Jian-Sin, and 李建新. "Study on Segmentation of Breast Tumors in Ultrasound Images Using Active Contour Model." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/69108440680549658636.

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碩士<br>元智大學<br>資訊管理學系<br>97<br>In this study, we propose a new active contour model based segmentation method for breast tumor in ultrasound images. An initial contour is marked automatically and the corresponding parameters are used to enhance the convergence effect of overall contour. To improve the poor convergence in concave boundaries of traditional active contour model, the gradient vector flow is considered as the guidance of edged energy. The additional information makes the contour converge to the correct boundary closely. Moreover, local binary pattern (LBP) is used as texture feature

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wu, wen lin, and 吳文鈴. "Segmentation of Breast Tumor in 3D Ultrasound Images Using Discrete Active Contour Model." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/38169500546640047065.

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碩士<br>國立中正大學<br>資訊工程研究所<br>89<br>In this paper, we make use of the discrete active contour model to overcome the natural properties of ultrasound images, speckles, noise, and tissue-related textures, to segment the breast tumors precisely. Before the snake deformation process, a good initial contour is needed and it will make the final contour as close as to the real tumor boundary. However, the manual way to sketch an initial contour is very time-consuming. Thus, we propose an automatic initial contour finding method, which not only maintains the tumor shape but also is close to the tumor bou

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Huang, Li-Yuan, and 黃立苑. "Segmentation of Breast Tumor inUltrasound Images Using Texture Analysis and Discrete Active Contour Model." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/73935333732232910861.

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碩士<br>國立中正大學<br>資訊工程研究所<br>88<br>Due to the speckles, noise, and tissue-related textures, most techniques for segmenting ultrasound images do not perform well. In this paper, we combine texture analysis schemes and the discrete active contour model to segment the breast tumors in the ultrasound images. There are two main steps in the proposed segmentation method, the initial contour finding and the snake deformation process. In the initial contour finding, we propose several methods to get a proper initial contour, which maintains the tumor shape and is close to the tumor boundary and inside t

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Lee, Wei, and 李偉. "Segmentation of Breast Tumor in 3D Ultrasound Images Using 3D Discrete Active Contour Model." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/96229323169578558914.

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碩士<br>國立中正大學<br>資訊工程研究所<br>89<br>In this paper, we apply the 3D active contour model to a 3D ultrasonic data file for segmenting of the breast tumor. The 3D ultrasonic file is composed of a series of 2D images. The traditional techniques of 2D image segmentation will not use the information between adjacent images. In order to suit with the property of the 3D data, we introduce the concept of the 3D stick, the 3D morphological process, and the 3D active contour model. The 3D stick can get over the problem that the ultrasound image is full of speckle noise, and highlight the edge information in

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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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Chen, Yu-Cheng, and 陳昱丞. "Development of Deep learning Models for Segmentation of Histopathological Images in Breast Cancer Diagnosis." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/t3rxt3.

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碩士<br>國立臺灣科技大學<br>醫學工程研究所<br>107<br>Breast cancer, the most common cancer in women, is primarily diagnosed with inspection of histopathological slides by pathologists. Manual diagnosis and classification of breast cancer is time consuming and needs experienced pathologists,and thus this research use deep learning for segmentation of breast cancer histopathological image and recognition of benign or malignancy tissue. About the detection and classification of breast cancer by Deep Learning. Most of the existing works focus only on binary classification of breast tumor (benign and malignant).We

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Yang, Huanyi. "Performance analysis of EM-MPM and K-means clustering in 3D ultrasound breast image segmentation." 2014. http://hdl.handle.net/1805/3875.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>Mammographic density is an important risk factor for breast cancer, detecting and screening at an early stage could help save lives. To analyze breast density distribution, a good segmentation algorithm is needed. In this thesis, we compared two popularly used segmentation algorithms, EM-MPM and K-means Clustering. We applied them on twenty cases of synthetic phantom ultrasound tomography (UST), and nine cases of clinical mammogram and UST images. From the synthetic phantom segmentation comparison we found that EM-MPM performs better

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Zhang, Shu-Wei, and 張書瑋. "Level Set Method with Cell Structure and Graph Partition Prior for Segmentation of Sonographic Breast Lesions." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/69445629325251191059.

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碩士<br>國立臺灣大學<br>醫學工程學研究所<br>95<br>Automatic boundary extraction of multiple targets of interest in an ultrasound image can not only help clinicians find out most perceptible objects, but also save sonologists’ time for boundary delineation. Moreover, it is potentially helpful for the novice instruction and medical research. In this paper we propose a new method combining the level set method with the cell competition structure information and graph partition prior in ultrasound image segmentation. Because of the intrinsic properties in ultrasound images, such as low contrast, high noises, spec

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