Title: Deep Learning Based Framework for Cardiac Imaging
Abstract: Myocardial ischemia or coronary artery disease can be identified and located by analyzing the movement and deformation of the heart. Therefore, in order to accurately and non-invasively diagnose the location and extent of ischemic or infarcted myocardium, it is of great practical significance to quantitatively determine the motion/deformation parameters of myocardial tissue. In this talk, I will focus on the new approach based on machine/deep learning for cardiac motion analysis.
Dr. Pengcheng Shi is the Associate Dean for Research and Scholarship at Rochester Institute of Technology’s B. Thomas Golisano College of Computing and Information Sciences, where he has also been a professor and director of the Ph.D. program. Dr. Shi has been teaching courses in research methods and machine learning, conducting research in biomedical imaging and image computing, and mentoring graduate students.