Anriban Mukhopadhyay, PhD candidate in computer science, researches the use of biomedical image analysis, computer vision, pattern recognition and machine learning. He is particularly focused on both functional and structural cardiovascular imaging. For the past year, Mukhopadhyay has been working on the analysis of high-resolution multi-detector computed tomography (MDCT) and intra-vascular ultra-sound-virtual histology (IVUS-VH) images for detection and diagnosis of cardiovascular pathologies. He has designed active contour models for segmentation and 3D visualization of plaque accumulation in an IVUS-VH image sequence of a blood vessel. His recent work has dealt with the characterization of the endocardial surface structure of the left ventricle using high-resolution MDCT images for diagnosis of coronary artery disease. He plans to strengthen his background in the clinical aspects of cardiovascular anatomy, physiology and pathology to enhance his research problem of correlating the morphological analysis of the endocardial surface with functional analysis of CT perfusion data for detection of cardiac ischemia.