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Dissertations / Theses on the topic 'Computer-aided Medical Diagnosis System'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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1

Thandani, Samir Ram. "A software-based ultrasound system for medical diagnosis." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/43496.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.<br>Includes bibliographical references (p. 113-115).<br>by Samir Ram Thadani.<br>M.Eng.

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2

Wu, Bangxian, and 吴邦限. "Clinical applications of imaging informatics: computer aided diagnosis of nasopharyngeal carcinoma based on PET-CTand multimedia electronic patient record system for neurosurgery." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48521917.

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Medical imaging informatics is one of the important research areas in radiology that studies how information available on medical images is retrieved, analyzed, and enhanced. Recent development in medical imaging informatics has resulted in improvement of diagnostic accuracy based on imaging examinations, as well as efficiency in clinical workflow. Computer aided diagnosis (CAD) and electronic patient record system (ePR) are both topics in medical imaging informatics that have matured from research concepts into commercially available computerized systems in clinical environment. The current

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3

Todd, Bryan S. "A formal approach to the design of medical diagnostic programs." Thesis, University of Oxford, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.670360.

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4

Elieson, S. Willard (Sanfred Willard). "Development of an Expert System to Teach Diagnostic Skills." Thesis, University of North Texas, 1990. https://digital.library.unt.edu/ark:/67531/metadc331448/.

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The primary purpose of the study was to develop an expert system that could C D perform medical diagnoses In selected problem areas, and C2) provide diagnostic Insights to assist medical students In their training. An expert system Is a computer-based set of procedures and algorithms that can solve problems In a given domain. Two research questions were proposed. The first was "Given a problem space defined by a matrix of diseases and symptoms, can a computer-based model be derived that will consistently perform accurate and efficient diagnoses of cases within that problem area?" The second qu

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5

Nie, Yali. "Automatic Melanoma Diagnosis in Dermoscopic Imaging Base on Deep Learning System." Licentiate thesis, Mittuniversitetet, Institutionen för elektronikkonstruktion, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-41751.

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Melanoma is one of the deadliest forms of cancer. Unfortunately, its incidence rates have been increasing all over the world. One of the techniques used by dermatologists to diagnose melanomas is an imaging modality called dermoscopy. The skin lesion is inspected using a magnification device and a light source. This technique makes it possible for the dermatologist to observe subcutaneous structures that would be invisible otherwise. However, the use of dermoscopy is not straightforward, requiring years of practice. Moreover, the diagnosis is many times subjective and challenging to reproduce.

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6

Ford, Ralph M. (Ralph Michael) 1965. "Computer-aided analysis of medical infrared images." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/276986.

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Thermography is a useful tool for analyzing spinal nerve root irritation, but interpretation of digital infrared images is often qualitative and subjective. A new quantitative, computer-aided method for analyzing thermograms, utilizing the human dermatome map, is presented. Image processing and pattern recognition principles needed to accomplish this goal are discussed. Algorithms for segmentation, boundary detection and interpretation of thermograms are presented. An interactive, user-friendly program to perform this analysis has been developed. Due to the relatively large number of images in

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7

MAZZEO, JOHN, and JOHN MAZZEO. "AN EVALUATION OF THE LEVEL OF SKILL REQUIRED OF OPERATORS OF A COMPUTER-ASSISTED RADIOLOGIC TOTAL LUNG CAPACITY MEASUREMENT SYSTEM (RELIABILITY, VALIDITY)." Diss., The University of Arizona, 1985. http://hdl.handle.net/10150/188124.

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This research was conducted to obtain information regarding the feasibility of using non-medical personnel to obtain measurements of radiologic total lung capacity (TLC). Operators from each of four groups (general undergraduates, nursing students, medical students, radiologists) differing in the amount of medical training and/or experience reading x-rays, performed each of two tasks. The first task was the measurement of radiologic TLC for a set of twenty x-rays. The second task consisted of tracing the outline of the anatomical structures that must be identified in the execution of the radio

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8

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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9

Kan, Pei Chen. "Computer aided design of home medical alert system." Connect to resource, 2008. http://hdl.handle.net/1811/35644.

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10

Oda, Masahiro, Takayuki Kitasaka, Kensaku Mori, and Yasuhito Suenaga. "DEVELOPMENT OF A COMPUTER AIDED DIAGNOSIS SYSTEM FOR COLORECTAL CANCER BASED ON NAVIGATION DIAGNOSIS." INTELLIGENT MEDIA INTEGRATION NAGOYA UNIVERSITY / COE, 2006. http://hdl.handle.net/2237/10473.

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11

Gu, Yiqun. "A Bayesian system for computer-aided diagnosis without assuming conditional independence." Thesis, Heriot-Watt University, 1992. http://hdl.handle.net/10399/1485.

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12

Livieratos-Petratos, George N. "Neural networks for computer aided diagnosis of pulmonary images in nuclear medicine." Thesis, University of Southampton, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295017.

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13

Donnelley, Martin, and martin donnelley@gmail com. "Computer Aided Long-Bone Segmentation and Fracture Detection." Flinders University. Engineering, 2008. http://catalogue.flinders.edu.au./local/adt/public/adt-SFU20080115.222927.

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Medical imaging has advanced at a tremendous rate since x-rays were discovered in 1895. Today, x-ray machines produce extremely high-quality images for radiologists to interpret. However, the methods of interpretation have only recently begun to be augmented by advances in computer technology. Computer aided diagnosis (CAD) systems that guide healthcare professionals to making the correct diagnosis are slowly becoming more prevalent throughout the medical field. Bone fractures are a relatively common occurrence. In most developed countries the number of fractures associated with age-related b

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14

Tao, Yimo. "Multi-Level Learning Approaches for Medical Image Understanding and Computer-aided Detection and Diagnosis." Thesis, Virginia Tech, 2010. http://hdl.handle.net/10919/42292.

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With the rapid development of computer and information technologies, medical imaging has become one of the major sources of information for therapy and research in medicine, biology and other fields. Along with the advancement of medical imaging techniques, computer-aided detection and diagnosis (CAD/CADx) has recently emerged to become one of the major research subjects within the area of diagnostic radiology and medical image analysis. This thesis presents two multi-level learning-based approaches for medical image understanding with applications of CAD/CADx. The so-called "multi-level learn

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Wen, Yiding. "Detecting microcalcifications in digitised mammograms by a computer aided diagnostic system." Thesis, The University of Sydney, 1999. https://hdl.handle.net/2123/27591.

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Breast cancer is now one of the most common forms of cancer and the leading cause of mortality in women in the developed countries. Early detection of breast cancer is currently the way to reduce breast cancer mortality and enhance the cure rate. Mammogram screening is widely recognized as the most reliable method for early detection of lesions and clustered microcalcifications, which are the two prominent symptoms of breast cancer. This thesis presents an image processing procedure for the automatic detection of clustered microcalcifications in digitized mammograms. This method consi

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16

TRAVERSO, ALBERTO. "Development and application in clinical practice of Computer-aided Diagnosis systems for the early detection of lung cancer." Doctoral thesis, Politecnico di Torino, 2017. http://hdl.handle.net/11583/2686725.

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Lung cancer is the main cause of cancer-related deaths both in Europe and United States, because often it is diagnosed at late stages of the disease, when the survival rate is very low if compared to first asymptomatic stage. Lung cancer screening using annual low-dose Computed Tomography (CT) reduces lung cancer 5-year mortality by about 20% in comparison to annual screening with chest radiography. However, the detection of pulmonary nodules in low-dose chest CT scans is a very difficult task for radiologists, because of the large number (300/500) of slices to be analyzed. In order to suppor

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17

Casiraghi, E. "A computer aided diagnosis system for lung nodules detection in postero anterior chest radiographs." Doctoral thesis, Università degli Studi di Milano, 2004. http://hdl.handle.net/2434/451239.

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This thesis describes a Computer Aided System aimed at lung nodules detection. The fully automatized method developed to search for nodules is composed by four steps. They are the segmentation of the lung field, the enhancement of the image, the extraction of the candidate regions, and the selection between them of the regions with the highest chance to be True Positives. The steps of segmentation, enhancement and candidates extraction are based on multi-scale analysis. The common assumption underlying their development is that the signal representing the details to be detected by each

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18

Saleem, Afsah. "Machine learning for computer-aided diagnostics from complex medical images." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2025. https://ro.ecu.edu.au/theses/2927.

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Machine learning has significantly transformed medical image analysis in the current age of artificial intelligence offering vast potential in improving disease diagnosis and management. Cardiovascular diseases (CVDs) are among the leading cause of global mortality, emphasizing the need for early detection for effective intervention and prevention. Abdominal Aortic Calcification (AAC) is an early indicator and contributor to Atherosclerotic Cardiovascular Diseases (ASCVDs) and is commonly assessed through imaging modalities such as computed tomography (CT), X-rays, and Dual-energy X-ray Absorp

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19

Guan, Hao. "Deep Representation Learning for Neuroimaging-based Diagnosis of Neurological Disorders." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/29366.

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Developing deep learning algorithms that extract rich representations could facilitate accurate diagnosis and offer insights into underlying disease mechanism. In this thesis, we explore deep representation learning for neuroimaging-based diagnosis of neurological disorders. Specifically, we investigate three approaches of learning rich representations: efficient representation learning, knowledge transfer, and disentangled representation learning. For efficient representation learning, a network augmented with attention mechanism and parallel structure is proposed. The network learns from

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El, Azami Meriem. "Computer aided diagnosis of epilepsy lesions based on multivariate and multimodality data analysis." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI087/document.

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Environ 150.000 personnes souffrent en France d'une épilepsie partielle réfractaire à tous les médicaments. La chirurgie, qui constitue aujourd’hui le meilleur recours thérapeutique nécessite un bilan préopératoire complexe. L'analyse de données d'imagerie telles que l’imagerie par résonance magnétique (IRM) anatomique et la tomographie d’émission de positons (TEP) au FDG (fluorodéoxyglucose) tend à prendre une place croissante dans ce protocole, et pourrait à terme limiter de recourir à l’électroencéphalographie intracérébrale (SEEG), procédure très invasive mais qui constitue encore la techn

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Asl, Babak Ghafary. "A Computer Aided Detection System for Cerebral Microbleeds in Brain MRI." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-6053.

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Advances in MR technology have improved the potential for visualization of small lesions in brain images. This has resulted in the opportunity to detect cerebral microbleeds (CMBs), small hemorrhages in the brain that are known to be associated with risk of ischemic stroke and intracerebral bleeding. Currently, no computerized method is available for fully- or semi-automated detection of CMBs. In this paper, we propose a CAD system for the detection of CMBs to speed up visual analysis in population-based studies. Our method consists of three steps: (i) skull-stripping (ii) initial candidate se

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22

Lee, Min-Zhao. "Computer-Aided Diagnosis in Radiology: Medical Image Analysis for the Scoring of Chest Radiographs in Cystic Fibrosis." Thesis, The University of Sydney, 2015. http://hdl.handle.net/2123/14101.

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Cystic fibrosis (CF) is one of the most common life-threatening genetic disorders worldwide and in Australia, causing considerable morbidity and mortality. Multiple organs are affected, including lungs in which a typical pattern of changes occurs, with progressive inflammatory thickening of the airways and destruction of alveoli. Clinicians assess disease severity using a combined score that includes radiological imaging. The Shwachman-Kulczycki scoring system used in Australia classifies chest radiographs (CXRs) into five categories. Determination of the score is still performed entirely by

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23

Zheng, Xing. "Ultrasound image processing and transmission for medical diagnosis /." View Abstract or Full-Text, 2003. http://library.ust.hk/cgi/db/thesis.pl?COMP%202003%20ZHENGX.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003.<br>Includes bibliographical references (leaves 66-69). Also available in electronic version. Access restricted to campus users.

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24

Chi, Chih-Lin Street William N. "Medical decision support systems based on machine learning." Iowa City : University of Iowa, 2009. http://ir.uiowa.edu/etd/283.

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25

Al-Kabir, Zul Waker Mohammad, and N/A. "A Knowledge Based System for Diagnosis of Lung Diseases from Chest X-Ray Images." University of Canberra. Information Sciences & Engineering, 2007. http://erl.canberra.edu.au./public/adt-AUC20070823.160921.

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The thesis develops a model (that includes a conceptual framework and an implementation) for analysing and classifying traditional X-ray images (MACXI) according to the severity of diseases as a Computer-Aided-Diagnosis tool with three initial objectives. � The first objective was to interpret X-ray images by transferring expert knowledge into a knowledge base (CXKB): to help medical staff to concentrate only on the interest areas of the images. � The second objective was to analyse and classify X-ray images according to the severity of diseases through the knowledge base equipped with an imag

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26

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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Adewole, Adeyemi Charles. "Investigation of methodologies for fault detection and diagnosis in electric power system protection." Thesis, Cape Peninsula University of Technology, 2012. http://hdl.handle.net/20.500.11838/1273.

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Thesis Submitted in fulfilment of the requirements for the degree Master of Technology: Electrical Engineering in the Faculty of Engineering at the Cape Peninsula University of Technology, 2012<br>The widespread deregulation and restructuring of electric power utilities throughout the world and the surge in competition amongst utility companies has brought about the desire for improved economic efficiency of electric utilities and the provision of better service to energy consumers. These end users are usually connected to the distribution network. Thus, there is a growing research interest in

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28

Zhou, Jing 1959. "LOVERD--a logic design verification and diagnosis system via test generation." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/291686.

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The development of cost-effective circuits is primarily a matter of economy. To achieve it, design errors and circuit flaws must be eliminated during the design process. To this end, considerable effort must be put into all phases of the design cycle. Effective CAD tools are essential for the production of high-performance digital systems. This thesis describes a CAD tool called LOVERD, which consists of ATPG, fault simulation, design verification and diagnosis. It uses test patterns, developed to detect single stuck-at faults in the gate-level implementation, to compare the results of the fun

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Luo, Hui. "Knowledge-based image understanding and classification systems for medical image databases." Buffalo, N.Y. : Dept. of Computer Science, State University of New York at Buffalo, 2001. http://www.cse.buffalo.edu/tech%2Dreports/2001%2D07.prn.Z.

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Padilla, Cerezo Berizohar. "Computer-Aided Diagnoses (CAD) System: An Artificial Neural Network Approach to MRI Analysis and Diagnosis of Alzheimer’s Disease (AD)." DigitalCommons@CalPoly, 2017. https://digitalcommons.calpoly.edu/theses/1837.

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Alzheimer’s disease (AD) is a chronic and progressive, irreversible syndrome that deteriorates the cognitive functions. Official death certificates of 2013 reported 84,767 deaths from Alzheimer’s disease, making it the 6th leading cause of death in the United States. The rate of AD is estimated to double by 2050. The neurodegeneration of AD occurs decades before symptoms of dementia are evident. Therefore, having an efficient methodology for the early and proper diagnosis can lead to more effective treatments. Neuroimaging techniques such as magnetic resonance imaging (MRI) can detect changes

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Gao, Feng. "Complex medical event detection using temporal constraint reasoning." Thesis, University of Aberdeen, 2010. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=153271.

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The Neonatal Intensive Care Unit (NICU) is a hospital ward specializing in looking after premature and ill newborn babies. Working in such a busy and complex environment is not easy and sophisticated equipment is used to help the daily work of the medical staff . Computers are used to analyse the large amount of monitored data and extract hidden information, e.g. to detect interesting events. Unfortunately, one group of important events lacks features that are recognizable by computers. This group includes the actions taken by the medical sta , for example two actions related to the respirator

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Hirschauer, Thomas Joseph. "Electrophysiological and Computational Approaches to the Investigation and Diagnosis of Motor System Dysfunction." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1437606805.

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Ahmady, Phoulady Hady. "Adaptive Region-Based Approaches for Cellular Segmentation of Bright-Field Microscopy Images." Scholar Commons, 2017. http://scholarcommons.usf.edu/etd/6794.

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Microscopy image processing is an emerging and quickly growing field in medical imaging research area. Recent advancements in technology including higher computation power, larger and cheaper storage modules, and more efficient and faster data acquisition devices such as whole-slide imaging scanners contributed to the recent microscopy image processing research advancement. Most of the methods in this research area either focus on automatically process images and make it easier for pathologists to direct their focus on the important regions in the image, or they aim to

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Loizillon, Sophie. "Deep learning for automatic quality control and computer-aided diagnosis in neuroimaging using a large-scale clinical data warehouse." Electronic Thesis or Diss., Sorbonne université, 2024. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2024SORUS258.pdf.

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La prise en charge des patients dans les hôpitaux génère quotidiennement des données de santé essentielles pour que les médecins assurent les meilleurs soins possibles aux patients. Au cours de la dernière décennie, l'émergence des entrepôts de données de santé (EDS) a révolutionné l'exploitation des données de routine clinique à des fins de recherche. En rassemblant les données médicales issues du soin courant (dossiers médicaux électroniques, imagerie, tests de pathologie et de laboratoireldots), les EDS offrent une opportunité unique pour la recherche. L'accès à ces vastes ensembles de donn

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Ghosh, Payel. "Medical Image Segmentation Using a Genetic Algorithm." PDXScholar, 2010. https://pdxscholar.library.pdx.edu/open_access_etds/25.

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Advances in medical imaging technology have led to the acquisition of large number of images in different modalities. On some of these images the boundaries of key organs need to be accurately identified for treatment planning and diagnosis. This is typically performed manually by a physician who uses prior knowledge of organ shapes and locations to demarcate the boundaries of organs. Such manual segmentation is subjective, time consuming and prone to inconsistency. Automating this task has been found to be very challenging due to poor tissue contrast and ill-defined organ/tissue boundaries. T

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Ginsburg, Shoshana. "Machine-Based Interpretation and Classification of Image-Derived Features: Applications in Digital Pathology and Multi-Parametric MRI of Prostate Cancer." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1459116552.

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Woods, Brent J. "Computer-Aided Detection of Malignant Lesions in Dynamic Contrast Enhanced MRI Breast and Prostate Cancer Datasets." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1218155270.

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38

Lankton, Shawn M. "Localized statistical models in computer vision." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31644.

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Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2010.<br>Committee Chair: Tannenbaum, Allen; Committee Member: Al Regib, Ghassan; Committee Member: Niethammer, Marc; Committee Member: Shamma, Jeff; Committee Member: Stillman, Arthur; Committee Member: Yezzi, Anthony. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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Horner, Vincent Zion. "Developing a consumer health informatics decision support system using formal concept analysis." Diss., Pretoria : [s.n.], 2007. http://upetd.up.ac.za/thesis/available/etd-05052008-112403/.

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Havaei, Seyed Mohammad. "Machine learning methods for brain tumor segmentation." Thèse, Université de Sherbrooke, 2017. http://hdl.handle.net/11143/10260.

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Abstract : Malignant brain tumors are the second leading cause of cancer related deaths in children under 20. There are nearly 700,000 people in the U.S. living with a brain tumor and 17,000 people are likely to loose their lives due to primary malignant and central nervous system brain tumor every year. To identify whether a patient is diagnosed with brain tumor in a non-invasive way, an MRI scan of the brain is acquired followed by a manual examination of the scan by an expert who looks for lesions (i.e. cluster of cells which deviate from healthy tissue). For treatment purposes, the tumor

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Kuru, Kaya. "A Novel Report Generation Approach For Medical Applications: The Sisds Methodology And Its Applications." Phd thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/3/12611719/index.pdf.

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In medicine, reliable data are available only in a few areas and necessary information on prognostic implications is generally missing. In spite of the fact that a great amount of money has been invested to ease the process, an effective solution has yet to be found. Unfortunately, existing data collection approaches in medicine seem inadequate to provide accurate and high quality data, which is a prerequisite for building a robust and effective DDSS. In this thesis, many different medical reporting methodologies and systems which have been used up to now are evaluated<br>their strengths and d

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Quatrehomme, Auréline. "Caractérisation des lésions hépatiques focales sur des acquisitions scanner multiphasiques." Thesis, Montpellier 2, 2013. http://www.theses.fr/2013MON20207/document.

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L'évolution des techniques d'acquisition des imageries médicales et leur importance de plus en plus grande dans la prise en charge du patient (diagnostic, préparation d'intervention, suivi, etc.), font émerger de nouveaux besoins autour du traitement informatique des images. La reconnaissance du type de lésions hépatiques est un grand enjeu, notamment car le cancer du foie, létal et très répandu, est souvent diagnostiqué trop tard pour sauver le patient. C'est dans ce cadre qu'est né le projet de recherche de ce manuscrit, fruit d'une collaboration entre la société IMAIOS et le Laboratoire d'I

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Поворознюк, Анатолій Іванович, та Ганна Євгенівна Філатова. "Формалізація етапів діагностично-лікувальних заходів при проектуванні систем підтримки прийняття рішень в медицині". Thesis, Прикарпатський національний університет ім. Василя Стефаника, 2017. http://repository.kpi.kharkov.ua/handle/KhPI-Press/46344.

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Формалізовано етапи діагностичнолікувального процесу при проектуванні комп'ютерних систем підтримки прийняття рішень в медицині. Розроблено математичну модель процесу діагностики та лікарських дій з метою підвищення ефективності надання медичних послуг та мінімізації ризиків лікарських помилок.<br>The stages of the diagnostic and therapeutic process in the design of computer decision support systems in medicine are formalized. The mathematical model of the process of diagnostics and medical actions for the purpose of increasing the efficiency of providing medical services and minimizing the ri

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Kouvahe, Amélé Eyram Florence. "Etude du remodelage vasculaire pathologique : de la caractérisation macroscopique en imagerie TDM à l’analyse en microscopie numérique." Electronic Thesis or Diss., Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAS019.

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Cette recherche s’intéresse à l’étude du réseau vasculaire en général, dans plusieurs modalités d’imagerie et plusieurs configurations anatomo-pathologiques. Son objectif consiste à discriminer les structures vasculaires dans les données image et détecter et quantifier la présence de modifications morphologiques (remodelage) en lien avec une pathologie. L’originalité de l’approche développée consiste à exploiter un filtrage localement connexe (FLC) multidirectionnel adapté à la dimension de l’espace de données (2D ou 3D). Ce filtrage permet de sélectionner les structures curvilignes en contras

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Hamadeh, Mohamad Ali. "Une approche unifiée pour la segmentation et la mise en correspondance 3D/2D d'images multimodales : application à l'étude cinématique 3D de la colonne vertébrale." Grenoble INPG, 1997. http://www.theses.fr/1997INPG0035.

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Dans cette these nous proposons une approche unifiee pour la mise en correspondance 3d/2d entre le modele surfacique 3d d'un objet et deux projections radiographiques 2d de cet objet. Il s'agit de trouver la transformation rigide 3d entre le modele de l'objet defini dans le referentiel r#m#o#d#e#l et les donnees radiographiques definies dans le referentiel du systeme d'imagerie radiographique r#s#e#n#s#o#r en tenant compte de la dualite entre mise en correspondance et segmentation dans un systeme de vision a base de modeles. Apres une presentation des diverses etapes de traitement necessaires

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Gonçalves, Vagner Mendonça. "Recuperação de vídeos médicos baseada em conteúdo utilizando extratores de características visuais e sonoras." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/100/100131/tde-20122016-111013/.

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A evolução dos dispositivos de armazenamento e das redes de computadores permitiram que os vídeos digitais assumissem um importante papel no desenvolvimento de sistemas de informação multimídia. Com a finalidade de aproveitar todo o potencial dos vídeos digitais no desenvolvimento desses sistemas, técnicas automatizadas eficientes para análise, interpretação e recuperação são necessárias. A recuperação de vídeos baseada em conteúdo (CBVR, do inglês content-based video retrieval) permite o processamento e a análise do conteúdo de vídeos digitais visando à extração de informações relevantes que

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Nuñovero, Daniela, Ernesto Rodríguez, Jimmy Armas, and Paola Gonzalez. "A Technological Solution to Identify the Level of Risk to Be Diagnosed with Type 2 Diabetes Mellitus Using Wearables." Repositorio Academico - UPC, 2021. http://hdl.handle.net/10757/653787.

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El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.<br>This paper proposes a technological solution using a predictive analysis model to identify and reduce the level of risk for type 2 diabetes mellitus (T2DM) through a wearable device. Our proposal is based on previous models that use the auto-classification algorithm together with the addition of new risk factors, which provide a greater contribution to the results of the presumptive diagnosis of the user who wants to check his level of risk. Th

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Felipe, Joaquim Cezar. "Desenvolvimento de métodos para extração, comparação e análise de características intrínsecas de imagens médicas, visando à recuperação perceptual por conteúdo." Universidade de São Paulo, 2005. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-12082006-000758/.

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A possibilidade de recuperar e comparar imagens usando as suas características visuais intrínsecas é um recurso valioso para responder a consultas por similaridade em imagens médicas. Desse modo, a agregação desses recursos aos Sistemas de Arquivamento e Comunicação de Imagens (Picture Archiving and Communication Systems - PACS) vêm potencializar a utilidade e importância destes no contexto de atividades tais como ensino e treinamento de novos radiologistas, estudos de casos e auxílio ao diagnóstico de forma geral, uma vez que as consultas por similaridade permitem que casos parecidos possam s

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Miranda, Gisele Helena Barboni. "Método para processamento e análise computacinal de imagens histopatológicas visando apoiar o diagnóstico de câncer de colo de útero." Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/95/95131/tde-24012012-154506/.

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A histopatologia é considerada um dos recursos diagnósticos mais importantes na prática médica e caracteriza-se pelo estudo das alterações estruturais e morfológicas das células e dos tecidos causadas por doenças. Atualmente, o principal método utilizado no diagnóstico histopatológico de imagens microscópicas, obtidas por meio de amostras em exames convencionais, é a avaliação visual do patologista, a qual se baseia na experiência do mesmo. O uso de técnicas de processamento computacional de imagens possibilita a identificação de elementos estruturais e a determinação de características ineren

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Chen, Beichen, and Amy Jinxin Chen. "PCA based dimensionality reduction of MRI images for training support vector machine to aid diagnosis of bipolar disorder." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259621.

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This study aims to investigate how dimensionality reduction of neuroimaging data prior to training support vector machines (SVMs) affects the classification accuracy of bipolar disorder. This study uses principal component analysis (PCA) for dimensionality reduction. An open source data set of 19 bipolar and 31 control structural magnetic resonance imaging (sMRI) samples was used, part of the UCLA Consortium for Neuropsychiatric Phenomics LA5c Study funded by the NIH Roadmap Initiative aiming to foster breakthroughs in the development of novel treatments for neuropsychiatric disorders. The ima

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