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http://hdl.handle.net/10603/454290
Title: | Delineation of blood vessels in coronary artery region for classification of different types of plaques |
Researcher: | Indumathy D |
Guide(s): | Sudha S |
Keywords: | Coronary Artery Diesease Plaques Propensity Score matching |
University: | Anna University |
Completed Date: | 2021 |
Abstract: | Medical is a fast-developing department, and is aiming to reach unreachable heights in the fields of Research and medical worldwide medical achievements range from the sectors of various organs to diagnosing diseases and faults. For all these achievements, coronary artery plaque identification is the most needed and irreplaceable technique. Iimportant factors that cause coronary artery disease are smoking, cholesterol, drinking, food changing, fast food, an unhealthy environment, weight, diabetes, high blood pressure, etc. Coronary artery disease develops when the major blood vessels that supply heart become damaged or diseased. newlineCholesterol-containing deposits (plaques) in coronary arteries and inflammation are usually to blame for coronary artery disease. The coronary arteries supply blood, oxygen and nutrients to your heart. A buildup of plaque can narrow these arteries, decreasing blood flow to heart. Eventually, the reduced blood flow may cause chest pain (angina), shortness of breath, or other coronary artery disease signs and symptoms. A complete blockage can cause a heart attack. Because coronary artery disease often develops over decades, this might not notice a problem until people have a significant blockage or a heart attack. To get a best classified output, the CT segmented images using boosting ensembled classifier has introduced and supports. The proposed boosting ensembled technique of coronary area classification is done by two steps: initial step is decomposing the corresponding imageries into different frequency ranges which permits the separation of the frequency components into certain sub-bands and then it detects the asymmetric edges using Symmetric Measures Technique. newline |
Pagination: | xiv,114p. |
URI: | http://hdl.handle.net/10603/454290 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 25.2 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 4.34 MB | Adobe PDF | View/Open | |
03_content.pdf | 347.06 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 217.31 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 585.6 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 581.2 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 1.45 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 1.25 MB | Adobe PDF | View/Open | |
09_annexures.pdf | 191.16 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 142.18 kB | Adobe PDF | View/Open |
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