Image Segmentation of Coronary Artery Plaque Using Intuitionistic Fuzzy C-Means Algorithm

Every year, hundreds of thousands of people die because of Coronary Heart Disease (CHD) in all over the world. Coronary Artery Disease (CAD) as a cardiovascular illness causes blood vessels narrowing that supply blood and oxygen to the heart. Atherosclerosis is known as the deadliest type of heart disease, which is caused by soft or "vulnerable" plaque (VP) formation in the coronary arteries. Acute Coronary Syndrome (ACS) is recognized as the first coronary atherosclerosis indicator which identifies high-risk plaques. Intravascular ultrasound (IVUS) can be applied for characterization of plaque and segmentation of vessel's walls borders. Recently, Virtual Histology as a new approach based on spectral analysis of IVUS has been introduced. In this work, we applied a clustering method based on Intuitionistic Fuzzy C-means (IFCM) in order to automatic segmentation of Coronary Artery plaque using VH-IVUS images.