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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/5740

Title: Development of an Algorithm for Object Detection in Medical Images using Image Segmentation and Deep Learning Techniques
Keywords: Atherosclerosis, Intravascular Ultrasound (IVUS), Watershed Algorithm, Deep Learning and Region of interest (ROI)
Researcher: Rai Shiv Shankar
Guide(s): Shaveta Bhatia
Registration Date: 24/12/2015
Abstract: Heart attack is mainly caused due to atherosclerosis. It is a coronary artery disease (CAD) and it is a leading cause of death worldwide. It occurs when the coronary artery that supplies blood and oxygen to the heart and different parts of the body becomes blocked or narrowed due to deposition of proteins, cholesterol and other fatty deposits in the inner wall of the coronary artery. This results in a heart attack or damage to the heart tissue. Existing techniques for detection of plaque are Magnetic Resonance Imaging (MRI), Electron Beam Computed Tomography (EBCT) and Angiography, among these existing techniques Angiography is widely used at present to detect and cure heart attack. The currently available techniques are expensive, beyond the reach of normal people, not easily available in remote areas and cannot detect deeply embedded plaque with accuracy at early stages. The plaque is only detected by these techniques when blockage in artery is more than70%. newline
Language: English
Appears in Department:Department of Computer Applications

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