Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/334851
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dc.coverage.spatialPerformance analysis of extracting blood vessel blockages from coronary angiogram images using soft computing classification techniques
dc.date.accessioned2021-08-05T11:02:41Z-
dc.date.available2021-08-05T11:02:41Z-
dc.identifier.urihttp://hdl.handle.net/10603/334851-
dc.description.abstractIn the approach of new medical imaging technologies, it is possible to explore the anatomical and functional structure of the human heart. Coronary Artery Disease (CAD) is a significant cause of death worldwide. There are numerous tests available for recognition of CAD at present. Quantitative Coronary Angiography (QCA) is the highest level imaging strategy for diagnosing CAD and evaluating the level of stenos is. There are many causes for the heart disease. One of the primary reason is, due to the narrow blood vessel blockage of an artery. Angiography is a specific X-ray imaging technique minimally non invasive procedure used to diagnose coronary artery disease. Extracting the maximum possible information from an image obtained is essential. However, image processing models based on scan sections or radiographic views may not wholly provide diagnostic details at an early stage. These limitations necessitate the development of new analysis techniques that will improve diagnostic ability. The main aim of the thesis is connected with the removal of artifacts and measurement of the length of coronary artery vessel blockage in X-ray coronary angiography images which makes an essential and fundamental component of a computer-aided system intended for the early identification of CAD. This thesis aims to explore the methods such as pre-processing, enhancement, segmentation, a classification of coronary artery vessel blockage and non-vessel blockage in the coronary artery or the assessment of the length of the vessel blockage newline
dc.format.extentxxv,172p.
dc.languageEnglish
dc.relationp.163-171
dc.rightsuniversity
dc.titlePerformance analysis of extracting blood vessel blockages from coronary angiogram images using soft computing classification techniques
dc.title.alternative
dc.creator.researcherRajesh Kumar, P
dc.subject.keywordVessel blockage
dc.subject.keywordCoronary Artery Disease
dc.subject.keywordSoft computing
dc.description.note
dc.contributor.guideMurugesan, K
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2020
dc.date.awarded2020
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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03_vivaproceedings.pdf1.1 MBAdobe PDFView/Open
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05_abstracts.pdf301.37 kBAdobe PDFView/Open
06_acknowledgements.pdf190.27 kBAdobe PDFView/Open
07_contents.pdf191.61 kBAdobe PDFView/Open
08_listoffigures.pdf197.72 kBAdobe PDFView/Open
09_listoftables.pdf179.85 kBAdobe PDFView/Open
10_listofabbreviations.pdf306.89 kBAdobe PDFView/Open
11_chapter1.pdf814.58 kBAdobe PDFView/Open
12_chapter2.pdf425.25 kBAdobe PDFView/Open
13_chapter3.pdf1.2 MBAdobe PDFView/Open
14_chapter4.pdf1.44 MBAdobe PDFView/Open
15_chapter5.pdf1.23 MBAdobe PDFView/Open
16_chapter6.pdf506.5 kBAdobe PDFView/Open
17_conclusion.pdf190.83 kBAdobe PDFView/Open
18_references.pdf441.92 kBAdobe PDFView/Open
19_listofpublications.pdf301.65 kBAdobe PDFView/Open
80_recommendation.pdf261.24 kBAdobe PDFView/Open


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