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Detection of Coronary Atherosclerosis Variants on the Basis of Coronographic Video Sequences

ФИО студента: Pavel Ilin

Руководитель: Maria Poptsova

Кампус/факультет: Faculty of Computer Science

Программа: Software Engineering (Bachelor)

Год защиты: 2020

Coronary atherosclerosis disease (CAD) is a health condition associated with decreased blood flow caused by buildup of plaque inside the coronary artery walls. Different types of CAD require different ways of treatment and can end up with different outcomes. Coronary angiography is a procedure to determine how the blood flows through coronary arteries by using a liquid radiocontrast agent and illumination with X-rays. This research aims to develop and compare different algorithms of patient classification based on video sequences of their coronary angiography. Such algorithms can be used in order to develop individual treatment for patients and provide prognosis insights. The paper contains 29 pages, 4 chapters, 11 figures, 5 tables 23 reference, 1 application Keywords: coronary atherosclerosis, X-ray coronary angiography, convolutional neural networks

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