Relevant bibliographies by topics / Tissue image segmentation / Dissertations / Theses
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Dissertations / Theses on the topic 'Tissue image segmentation'

Author: Grafiati
Published: 5 June 2025
Last updated: 1 August 2025

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1

Lu, Jiang. "Transforms for multivariate classification and application in tissue image segmentation /." free to MU campus, to others for purchase, 2002. http://wwwlib.umi.com/cr/mo/fullcit?p3052195.

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2

Fakhrzadeh, Azadeh. "Computerized Cell and Tissue Analysis." Doctoral thesis, Uppsala universitet, Avdelningen för visuell information och interaktion, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-252425.

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The latest advances in digital cameras combined with powerful computer software enable us to store high-quality microscopy images of specimen. Studying hundreds of images manually is very time consuming and has the problem of human subjectivity and inconsistency. Quantitative image analysis is an emerging field and has found its way into analysis of microscopy images for clinical and research purposes. When developing a pipeline, it is important that its components are simple enough to be generalized and have predictive value. This thesis addresses the automation of quantitative analysis of ti
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Purwani, Sri. "Ensemble registration : combining groupwise registration and segmentation." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/ensemble-registration-combining-groupwise-registration-and-segmentation(5f3c06b4-4909-492b-bbc9-a0fecb77d216).html.

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Registration of a group of images generally only gives a pointwise, dense correspondence defined over the whole image plane or volume, without having any specific description of any common structure that exists in every image. Furthermore, identifying tissue classes and structures that are significant across the group is often required for analysis, as well as the correspondence. The overall aim is instead to perform registration, segmentation, and modelling simultaneously, so that the registration can assist the segmentation, and vice versa. However, structural information does play a role in
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Spottiswoode, Bruce Shawn. "Towards automating cine DENSE MRI image analysis : segmentation, tissue tracking and strain computation." Doctoral thesis, University of Cape Town, 2006. http://hdl.handle.net/11427/3204.

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Includes bibliographical references (p. 192-206).<br>Over the past two decades, magnetic resonance imaging (MRI) has developed into a powerful imaging tool for the heart. Imaging cardiac morphology is now commonplace in clinical practice, and a plethora of quantitative techniques have also arisen on the research front. Myocardial tagging is an established quantitative cardiac MRI method that involves magnetically tagging the heart with a set of saturated bands, and monitoring the deformation of these bands as the heart contracts.
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5

Jeuthe, Julius. "Automatic Tissue Segmentation of Volumetric CT Data of the Pelvic Region." Thesis, Linköpings universitet, Medicinsk informatik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-133153.

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Automatic segmentation of human organs allows more accurate calculation of organ doses in radiationtreatment planning, as it adds prior information about the material composition of imaged tissues. For instance, the separation of tissues into bone, adipose tissue and remaining soft tissues allows to use tabulated material compositions of those tissues. This approximation is not perfect because of variability of tissue composition among patients, but is still better than no approximation at all. Another use for automated tissue segmentationis in model based iterative reconstruction algorithms.
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Nguyễn, Hoài Nam. "Méthodes et algorithmes de segmentation et déconvolution d'images pour l'analyse quantitative de Tissue Microarrays." Thesis, Rennes 1, 2017. http://www.theses.fr/2017REN1S104/document.

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Ce travail de thèse a pour objectif de développer les méthodes originales pour l'analyse quantitative des images de Tissue Microarrays (TMAs) acquises en fluorescence par des scanners dédiés. Nous avons proposé des contributions en traitement d'images portant sur la segmentation des objets d'intérêts (i.e. des échantillons de tissus sur la lame de TMA scannée), la correction des artefacts d'acquisition liés aux scanners en question ainsi que l'amélioration de la résolution spatiale des images acquises en tenant compte des modalités d'acquisition (imagerie en fluorescence) et la conception des
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Nguyen, Lam K. "High-throughput image cytometer for detection of circulating tumor cells and contrast-enhancement filtering for automated 3D image segmentation of cartilage tissue explants." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3259052.

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Thesis (Ph. D.)--University of California, San Diego, 2007.<br>Title from first page of PDF file (viewed June 11, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 223-234).
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8

Metzger, Andrew. "An automated tissue classification pipeline for magnetic resonance images of infant brains using age-specific atlases and level set segmentation." Thesis, University of Iowa, 2016. https://ir.uiowa.edu/etd/3143.

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Quantifying tissue volumes in pediatric brains from magnetic resonance (MR) images can provide insight into etiology and onset of neurological disease. Unbiased volumetric analysis can be applied to large population studies when automated image processing is possible. Standard segmentation strategies using adult atlases fail to account for varying tissue contrasts and types associated with the rapid growth and maturational changes seen in early neurodevelopment. The goal of this project was to develop an automated pipeline and two age-specific atlases capable of providing accurate tissue class
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Chaudry, Qaiser Mahmood. "Improving cancer subtype diagnosis and grading using clinical decision support system based on computer-aided tissue image analysis." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47745.

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This research focuses towards the development of a clinical decision support system (CDSS) based on cellular and tissue image analysis and classification system that improves consistency and facilitates the clinical decision making process. In a typical cancer examination, pathologists make diagnosis by manually reading morphological features in patient biopsy images, in which cancer biomarkers are highlighted by using different staining techniques. This process is subjected to pathologist's training and experience, especially when the same cancer has several subtypes (i.e. benign tumor subtyp
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Bianculli, Antonella. "Analysis of the scale effect in different computed tomography systems on the evaluation of bone tissue parameters." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/11207/.

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Tra le patologie ossee attualmente riconosciute, l’osteoporosi ricopre il ruolo di protagonista data le sua diffusione globale e la multifattorialità delle cause che ne provocano la comparsa. Essa è caratterizzata da una diminuzione quantitativa della massa ossea e da alterazioni qualitative della micro-architettura del tessuto osseo con conseguente aumento della fragilità di quest’ultimo e relativo rischio di frattura. In campo medico-scientifico l’imaging con raggi X, in particolare quello tomografico, da decenni offre un ottimo supporto per la caratterizzazione ossea; nello specifico la mic
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Sener, Emre. "Automatic Bayesian Segmentation Of Human Facial Tissue Using 3d Mr-ct Fusion By Incorporating Models Of Measurement Blurring, Noise And Partial Volume." Phd thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12615091/index.pdf.

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Segmentation of human head on medical images is an important process in a wide array of applications such as diagnosis, facial surgery planning, prosthesis design, and forensic identification. In this study, a new Bayesian method for segmentation of facial tissues is presented. Segmentation classes include muscle, bone, fat, air and skin. The method incorporates a model to account for image blurring during data acquisition, a prior helping to reduce noise as well as a partial volume model. Regularization based on isotropic and directional Markov Random Field priors are integrated to the algori
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Ghayoor, Ali. "Improved interpretation of brain anatomical structures in magnetic resonance imaging using information from multiple image modalities." Diss., University of Iowa, 2017. https://ir.uiowa.edu/etd/5477.

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This work explores if combining information from multiple Magnetic Resonance Imaging (MRI) modalities provides improved interpretation of brain biological architecture as each MR modality can reveal different characteristics of underlying anatomical structures. Structural MRI provides a means for high-resolution quantitative study of brain morphometry. Diffusion-weighted MR imaging (DWI) allows for low-resolution modeling of diffusivity properties of water molecules. Structural and diffusion-weighted MRI modalities are commonly used for monitoring the biological architecture of the brain in no
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Dichamp, Jules. "De l'imagerie tissu entier à la modélisation in silico du réseau vasculaire du tissu adipeux." Phd thesis, Toulouse, INPT, 2018. http://oatao.univ-toulouse.fr/23606/1/Dichamp.pdf.

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Le tissu adipeux est traditionnellement décrit comme étant constitué de lobules : des entités de formes ovoïdales composées de cellules et de vaisseaux et faiblement connectées entre elles.Récemment, il a été montré qu’un potentiel métabolique spécifique (le browning) co-localise avec cette organisation en lobules au sein d’un même tissu. Dans ce travail de thèse, nous nous intéressons à décrire plus précisément l’organisation structurelle et fonctionnelle du tissu adipeux selon plusieurs aspects. Dans un premier temps, on s’attache à segmenter les lobules du tissu adipeux en utilisant une mét
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PUTZU, LORENZO. "Computer aided diagnosis algorithms for digital microscopy." Doctoral thesis, Università degli Studi di Cagliari, 2016. http://hdl.handle.net/11584/266877.

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Automatic analysis and information extraction from an image is still a highly chal- lenging research problem in the computer vision area, attempting to describe the image content with computational and mathematical techniques. Moreover the in- formation extracted from the image should be meaningful and as most discrimi- natory as possible, since it will be used to categorize its content according to the analysed problem. In the Medical Imaging domain this issue is even more felt because many important decisions that affect the patient care, depend on the use- fulness of the information
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Noschinski, Leonie. "Validierung einer neuen Software für halbautomatische Volumetrie – ist diese besser als manuelle Messungen?" Doctoral thesis, Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-210703.

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This study compared a manual program for liver volumetry with a semiautomated software. The hypothesis was that the software would be faster, more accurate and less dependent on the evaluator’s experience. Materials and Methods: Ten patients undergoing hemihepatectomy were included into this IRB approved study after written informed consent. All patients underwent a preoperative abdominal CTScan, which was used for whole liver volumetry and volume prediction for the liver part to be resected. Two different softwares were used: 1) manual method: borders of the liver had to be defined per slice
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Mikulka, Jan. "Segmentační metody ve zpracování biomedicínských obrazů." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2011. http://www.nusl.cz/ntk/nusl-233529.

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The PhD thesis deals with modern methods of image processing, especially image segmentation, classification and evaluation of parameters. It is focused primarily on processing medical images of soft tissues obtained by magnetic resonance tomography (MR) and microscopic images of tissues. It is easy to describe edges of the sought objects using of segmented images. The edges found can be useful for further processing of monitored object such as calculating the perimeter, surface and volume evaluation or even three-dimensional shape reconstruction. The proposed solutions can be used for the clas
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Wolters, Carsten H. "Influence of Tissue Conductivity Inhomogeneity and Anisotropy on EEG/MEG based Source Localization in the Human Brain." Doctoral thesis, Universitätsbibliothek Leipzig, 2004. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-37549.

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The inverse problem in Electro- and Magneto-EncephaloGraphy (EEG/MEG) aims at reconstructing the underlying current distribution in the human brain using potential differences and/or magnetic fluxes that are measured non-invasively directly, or at a close distance, from the head surface. The solution requires repeated computation of the forward problem, i.e., the simulation of EEG and MEG fields for a given dipolar source in the brain using a volume-conduction model of the head. The associated differential equations are derived from the Maxwell equations. Not only do various head tissues exhib
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Kullberg, Joel. "Assessment of Body Composition Using Magnetic Resonance Imaging." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-7739.

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Wu, Jue. "Brain image segmentation : from tissues to structures /." View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?BIEN%202008%20WU.

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Poláková, Veronika. "Využití konvolučních neuronových sítí pro segmentaci chrupavčitých tkání myších embryí v mikro-CT datech." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442503.

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Automatická segmentace biologických struktur v mikro-CT datech je stále výzvou, protože často objekt zájmu (v našem případě obličejová chrupavka) není charakterizovaný unikátním jasem či ostrými hranicemi. V posledních letech se konvoluční neuronové sítě (CNNs) staly mimořádně populárními v mnoha oblastech počítačového vidění. Konkrétně pro segmentaci biomedicínských obrazů je široce používaná architektura U-Net. Nicméně v případě mikro-CT dat vyvstává otázka, zda by nebylo výhodnější použít 3D CNN. Diplomová práce navrhla CNN architekturu založenou na síti V-Net včetně metodologie pro předzpr
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Kapur, Tina. "Segmentation of Brain Tissue from Magnetic Resonance Images." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/7067.

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Segmentation of medical imagery is a challenging problem due to the complexity of the images, as well as to the absence of models of the anatomy that fully capture the possible deformations in each structure. Brain tissue is a particularly complex structure, and its segmentation is an important step for studies in temporal change detection of morphology, as well as for 3D visualization in surgical planning. In this paper, we present a method for segmentation of brain tissue from magnetic resonance images that is a combination of three existing techniques from the Computer Vision
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Woods, Keri. "Tissue segmentation of the cerebellum from MR images." Master's thesis, University of Cape Town, 2011. http://hdl.handle.net/11427/11052.

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The cerebellum is known to be very susceptible to prenatal exposure to alcohol and people affected by Fetal Alcohol Spectrum Disorder (FASD) show a decrease in cerebellar volume. Unfortunately, there seems to be little work that focuses specifically on cerebellum tissue segmentation. We set out to produce a method, as automated as possible, that segments the cerebellum into grey and white matter, capturing as much of the fine detail as possible.
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McGarry, Gregory John. "Model-based mammographic image analysis." Thesis, Queensland University of Technology, 2002.

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Mouroutis, Theodoros. "Segmentation and classification of cell nuclei in tissue sections." Thesis, Imperial College London, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343898.

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Valverde, Valverde Sergi. "Automated brain tissue segmentation of magnetic resonance images in multiple sclerosis." Doctoral thesis, Universitat de Girona, 2016. http://hdl.handle.net/10803/386468.

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L'objectiu principal d'aquesta tesi és el desenvolupament d'un nou mètode de segmentació totalment automàtic capaç de mesurar amb precisió el volum cerebral en imatges de pacients d'EM amb lesions. El mètode que hem proposat s'ha desenvolupat i implementat integrant no només la informació provinent de la intensitat dels vòxels, sinó a través de la incorporació d'atles morfològics i estructurals que guien la segmentació del teixit. Els vòxels candidats de ser lesions són estimats i processats abans de la segmentació del teixit utilitzant un algoritme de post-processat basat en la informació del
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Hua, Panfang. "Segmentation of lung tissue in CT images with disease and pathology." Thesis, University of Iowa, 2010. https://ir.uiowa.edu/etd/819.

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Lung segmentation is an important first step for quantitative lung CT image analysis and computer aided diagnosis. However, accurate and automated lung CT image segmentation may be made difficult by the presence of the abnormalities. Since many lung diseases change tissue density, resulting in intensity changes in CT image data, intensity-only segmentation algorithms will not work for most pathological lung cases. This thesis presents two automatic algorithms for pathological lung segmentation. One is based on the geodesic active contour, another method uses graph search driven by a cost funct
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Kardell, Martin. "Automatic Segmentation of Tissues in CT Images of the Pelvic Region." Thesis, Linköpings universitet, Institutionen för medicinsk teknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-112540.

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In brachytherapy, radiation therapy is performed by placing the radiation source into or very close to the tumour. When calculating the absorbed dose, water is often used as the radiation transport and dose scoring medium for soft tissues and this leads to inaccuracies. The iterative reconstruction algorithm DIRA is under development at the Center for Medical Imaging Science and Visualization, Linköping University. DIRA uses dual-energy CT to decompose tissues into different doublets and triplets of base components for a better absorbed dose estimation. To accurately determine mass fractions o
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Koller, Daniela. "Processing of Optical Coherence Tomography Images : Filtering and Segmentation of Pathological Thyroid Tissue." Thesis, Linköpings universitet, Institutionen för medicinsk teknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-161988.

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In the human body, the main function of the healthy thyroid gland is the regulation of the metabolism and hormone production. Included in the thyroid are organized structured and uniformly shaped follicles ranging from 50-500 μm in diameter. Pathologies lead to morphological changes of these follicles, affecting the density and size, but can also lead to an absence. In this study optical coherence tomography (OCT) was used to examine pathological thyroid tissue by extracting structural information of the follicles from image segmentation. However, OCT images usually include a high amount of sp
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Mohamed, Samar. "Integrated Feature Analysis for Prostate Tissue Characterization Using TRUS Images." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2888.

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The Prostate is a male gland that is located around the urethra. Prostate Cancer is the second most diagnosed malignancy in men over the age of fifty. Typically, prostate cancer is diagnosed from clinical data, medical images, and biopsy. <br /><br /> Computer Aided Diagnosis (CAD) was introduced to help in the diagnosis in order to assist in the biopsy operations. Usually, CAD is carried out utilizing either the clinical data, using data mining techniques, or using features extracted from either TransRectal UltraSound (TRUS) images or the Radio Frequency (RF) signals. <br /><br
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Zlateski, Aleksandar. "Scalable algorithms for semi-automatic segmentation of electron microscopy images of the brain tissue." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/105955.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 139-145).<br>I present a set of fast and scalable algorithms for segmenting very large 3D images of brain tissue. Currently, light and electron microscopy can now produce terascale 3D images within hours. Extracting the infor
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Würslin, Christian [Verfasser]. "Automatic Segmentation of Distinct Adipose Tissue Compartments from Human Magnetic Resonance Images / Christian Würslin." München : Verlag Dr. Hut, 2015. http://d-nb.info/1067707999/34.

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Feudjio, Kougoum Cyrille Désiré. "Segmentation of mammographic images for computer aided diagnosis." Thesis, Lille 1, 2016. http://www.theses.fr/2016LIL10152/document.

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Les outils d’aide au diagnostic sont de nos jours au cœur de plusieurs protocoles cliniques car ils améliorent la qualité du diagnostic posé et des soins médicaux. Ce travail de recherche met en avant une architecture hiérarchique pour la conception d'un outil d'aide à la détection du cancer du sein robuste et performant. Il s’intéresse à la réduction des fausses alarmes en identifiant les régions potentiellement cancérogènes. La gamme dynamique des niveaux de gris des zones sombres est étirée pour améliorer le contraste entre la région du sein et l'arrière plan et permettre une meilleure extr
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Haj, Hassan Hawraa. "Détection et classification temps réel de biocellules anormales par technique de segmentation d’images." Thesis, Université de Lorraine, 2018. http://www.theses.fr/2018LORR0043.

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Le développement de méthodes de la détection en temps réel de cellules anormales (pouvant être considérées comme des cellules cancéreuses) par captures et traitements bio-images sont des axes de recherche importants dans le domaine biomédical car cela contribue à diagnostiquer un cancer. C’est dans ce contexte que se situe ces travaux de thèse. Plus précisément, les travaux présentés dans ce manuscrit, se focalise sur le développement de procédures de lecture, de détection et de classification automatiques de bio-images de cellules anormales considérées comme des cellules cancéreuses. Par cons
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Haj, Hassan Hawraa. "Détection et classification temps réel de biocellules anormales par technique de segmentation d’images." Electronic Thesis or Diss., Université de Lorraine, 2018. http://www.theses.fr/2018LORR0043.

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Le développement de méthodes de la détection en temps réel de cellules anormales (pouvant être considérées comme des cellules cancéreuses) par captures et traitements bio-images sont des axes de recherche importants dans le domaine biomédical car cela contribue à diagnostiquer un cancer. C’est dans ce contexte que se situe ces travaux de thèse. Plus précisément, les travaux présentés dans ce manuscrit, se focalise sur le développement de procédures de lecture, de détection et de classification automatiques de bio-images de cellules anormales considérées comme des cellules cancéreuses. Par cons
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Tran, Thi Nhu Hoa. "Analyse et modélisation 3D de l’organisation spatiale des tissus dans des images biologiques." Electronic Thesis or Diss., Sorbonne université, 2018. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2018SORUS457.pdf.

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Nombreux travaux ont été menés pour analyser automatiquement des cellules dans des images de microscopie. Néanmoins, ces travaux se concentrent principalement sur l’application de traitement et d’analyse d’images sur des cellules individuelles. Il y a un manque d’un outil générique pour analyser les interactions entre les cellules et leur organisation spatiale au sein de tissus biologiques. De plus, il existe une demande pour une approche qui est plus efficace pour gérer des images de cellules en 3D à haut débit. Car l’étude des cellules dans l’espace tridimensionnel (3D) donne une meilleure i
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Ogier, Augustin. "La segmentation et la caractérisation des déformations d'organes à tissus mous à partir de l'IRM : applications à l'imagerie du muscle et à l'imagerie pelvienne." Electronic Thesis or Diss., Aix-Marseille, 2021. http://www.theses.fr/2021AIXM0461.

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Le déploiement de méthodes d’anatomie computationnelle demeure limité pour l'exploration des organes à tissus mous, notamment dans le cadre des deux contextes applicatifs abordés dans cette thèse que sont l'étude des troubles du plancher pelvien et des maladies neuromusculaires via l'imagerie par résonance magnétique (IRM). Dans ces domaines, l'étape de segmentation est essentielle pour la caractérisation des altérations physiologiques au sein des organes d'intérêt. Le manque de méthodes automatiques robustes freine les recherches cliniques sur de larges populations. La première contribution d
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Redortier, Bernard. "Contribution de l'analyse de Fourier à la segmentation et la quantification des surfaces multi-texturées : application à l'analyse d'aspect des surfaces textiles." Saint-Etienne, 1992. http://www.theses.fr/1992STET4018.

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L'image d'une surface textile est définie comme la superposition de textures élémentaires. Un premier niveau de décomposition consiste à séparer les composantes périodique et non périodique. Ceci est réalisé par un processus automatique de filtrage sur la transformée de Fourier de l'image. Les pics de périodicité sont reconnus par un noyau basé sur des règles d'expertise et reproduisant le caractère incertain du jugement humain. La fonction de transfert du filtre s'autoadapte ensuite à la morphologie du spectre pour prendre en compte les distorsions de périodicité et les artefacts amenés par l
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Ionescu, Gelu. "Segmentation et recalage d'images échographiques par utilisation de connaissances physiologiques et morphologiques." Phd thesis, Université Joseph Fourier (Grenoble), 1998. http://tel.archives-ouvertes.fr/tel-00005189.

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L'échographie est un outil qui s'impose de plus en plus dans le domaine des Gestes Médico-Chirurgicaux Assistés par Ordinateur (GMCAO). Les médecins et les chirurgiens disposent en conséquence d'un excellent outil de travail qui les aide à planifier et surtout à réaliser des interventions chirurgicales. Pour cela, ils ont besoin également de logiciels automatiques et faciles à utiliser fondés sur d'algorithmes robustes, précis et rapides. L'objectif majeur de cette thèse est d'exploiter la dualité segmentation- recalage pour extraire de l'information pertinente des images échographiques. Cette
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巫宗昇. "Computer image segmentation for liver tissue by using color in formation." Thesis, 1992. http://ndltd.ncl.edu.tw/handle/86043186497615696595.

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Wolters, Carsten H. "Influence of Tissue Conductivity Inhomogeneity and Anisotropy on EEG/MEG based Source Localization in the Human Brain." 2003. https://ul.qucosa.de/id/qucosa%3A10978.

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The inverse problem in Electro- and Magneto-EncephaloGraphy (EEG/MEG) aims at reconstructing the underlying current distribution in the human brain using potential differences and/or magnetic fluxes that are measured non-invasively directly, or at a close distance, from the head surface. The solution requires repeated computation of the forward problem, i.e., the simulation of EEG and MEG fields for a given dipolar source in the brain using a volume-conduction model of the head. The associated differential equations are derived from the Maxwell equations. Not only do various head tissues exhib
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Noschinski, Leonie. "Validierung einer neuen Software für halbautomatische Volumetrie – ist diese besser als manuelle Messungen?" Doctoral thesis, 2015. https://ul.qucosa.de/id/qucosa%3A14957.

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This study compared a manual program for liver volumetry with a semiautomated software. The hypothesis was that the software would be faster, more accurate and less dependent on the evaluator’s experience. Materials and Methods: Ten patients undergoing hemihepatectomy were included into this IRB approved study after written informed consent. All patients underwent a preoperative abdominal CTScan, which was used for whole liver volumetry and volume prediction for the liver part to be resected. Two different softwares were used: 1) manual method: borders of the liver had to be defined per
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Lin, Jian-An, and 林建安. "Tissue Segmentation of Brain MR Images by Using Hierarchical Classifiers." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/99340845479313947264.

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碩士<br>國立臺灣海洋大學<br>通訊與導航工程學系<br>99<br>Currently, many brain lesions or diseases are diagnosed by observing the magnetic resonance (MR) images. Especially, the volume of gray matter and white matter tissue in brain is changed with different diseases. In contrast to the brain diseases diagnosed according the the physician’s knowledge and experience, the development of the brain tissue classification algorithm could provide a valuable medical help in prevention and treatment of diseases. However, the grayscale value of the various parts of brain tissue in MR images is close to and difficult to be
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Liou, Geng-Jin, and 劉耿進. "A Research on Brain Tissue Segmentation for Brain Magnetic Resonance Images." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/04503619068303899215.

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碩士<br>國立勤益科技大學<br>電子工程系<br>102<br>Due to magnetic resonance (MR) imaging has noninvasive properties and can provide very high resolution images for living tissues. It is frequently used to detect the states of tissue and organ to distinguish the difference between the tumor and the cancer cells. At present, MR imaging is widely used to diagnose and monitor the activity of brain disease such as brain stroke, cerebellar atrophy, multiple sclerosis, Parkinson’s disease, Alzheimer’s disease and so on. An accurate automatic brain MR image segmentation system is required, it can save numerous manpow
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Azevedo, Liliana. "Segmentation and 3D Reconstruction of Animal Tissues in Histological Images." Dissertação, 2013. http://hdl.handle.net/10216/73346.

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Azevedo, Liliana Sofia Sales. "Segmentation and 3D Reconstruction of Animal Tissues in Histological Images." Master's thesis, 2013. https://repositorio-aberto.up.pt/handle/10216/69363.

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Azevedo, Liliana Sofia Sales. "Segmentation and 3D Reconstruction of Animal Tissues in Histological Images." Dissertação, 2013. https://repositorio-aberto.up.pt/handle/10216/69363.

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Wang, Ying-Siou, and 王瀅琇. "Liver Cell Nucleus Segmentation and Fibrosis Grading Recognition System for Liver Tissue Images." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/67760551619464785117.

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碩士<br>國立中興大學<br>資訊管理學系所<br>100<br>This study proposes image segmentation and grading recognition system for liver fibrosis tissue images. It is a new idea to recognize the grades by extracting the object features in liver fibrosis tissue images. In this thesis, two objects of nucleus and vacuole for liver tissue images are retrieved by using the segmentation methods, and then the features are used to recognize which grade of liver fibrosis image is. In segmentation phase, some image processing methods are applied to segment the object regions of nucleuses and vacuoles. For nucleus regions segm
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BENEDIKTYOVÁ, Zuzana. "Imaging of fluorescence emission signals from healthy and infected leaf tissues." Doctoral thesis, 2009. http://www.nusl.cz/ntk/nusl-52374.

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Auto-fluorescence emission of plant tissues can be a powerful reporter on plant biochemistry and physiology since it originates in substances inherent to primary or secondary metabolism. Plant bodies contain a plethora of intrinsic fluorescent compounds emitting practically all wavelengths of visible light. Moreover, the spectrum of fluorescent reporter signals was recently extended by a variety of fluorescent proteins that provide a new tool to mark whole cells or sub-cellular structures, study protein localization and monitor gene expression and molecule interactions. The imaging of such flu
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GUACHI, ROBINSON. "Nonlinear effects in finite elements analysis of colorectal surgical clamping." Doctoral thesis, 2019. http://hdl.handle.net/11573/1242194.

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Minimal Invasive Surgery (MIS) is a procedure that has increased its applications in past few years in different types of surgeries. As number of application fields are increasing day by day, new issues have been arising. In particular, instruments must be inserted through a trocar to access the abdominal cavity without capability of direct manipulation of tissues, so a loss of sensitivity occurs. Generally speaking, the student of medicine or junior surgeons need a lot of practice hours before starting any surgical procedure, since they have to difficulty in acquiring specific skills (hand–ey
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