Segmentation and Classification of Intravascular Ultrasound Images for Plaque Detection using Machine Learning Techniques

Abstract

Cardiovascular Diseases (CVDs) are the leading causes of death in most newlinedeveloped nations. In many cases, CVDs are related to Coronary Artery (CA) newlinedisease: a condition caused by the accumulation of fatty lesions called plaques on newlinethe vessels that nourish the heart with blood. Overtime, the deposited plaques newlinewithin the CA start to limit the blood flow to the heart muscles and this condition newlineis called ischemia. This deposition may be chronic, causing only the narrowing of newlineblood vessels and restricting the supply or in some cases acute, leading to the newlinesudden rupture of plaque and the formation of thrombus. The diagnosis and newlinetreatment of the disease require visualizing the blood vessels and the level of newlineplaque deposition. In recent decades, the Intravascular Ultrasound (IVUS) newlineimaging modality has captured considerable attention in the diagnosis of CVDs. newlineIVUS is a catheter-based imaging technique that provides a cross-sectional view newlineof the blood vessels in real-time and reveals more information about the plaque newlinedeposited. newlineGenerally, the CA consists of three distinct regions. The media forms the newlineactual wall of the artery. The intima is the layer of endothelial cells that make newlinedirect contact with the blood that flows. Finally, the luminal region is the actual newlineopen channel for blood flow. In a normal artery, the intima layer is very thin. newlineWhereas in a diseased artery, the intima is thickened by plaque deposition. The newlineinformation regarding the degree of vessel obstruction and the shape of the plaque newlinedeposited is obtained through the segmentation of the IVUS image. There are newlinexviii newlineseveral factors that reduce the accuracy of segmentation and ultimately cause newlinedifficulty in the interpretation of the disease level. newlineThe proposed work aims to detect the presence of plaque in IVUS images. newlineThe entire research work is subdivided into three stages: Pre-processing, newlineSegmentation and Classification. newlineSpeckle noise suppression is an essential pre-processing step because the newlinepresence of a speckle pattern in IVUS image may disturb the featu