Leo Grady (Heartflow Inc.)
Calvin Lab 116
Graph Theory for Image Analysis and Medicine
Personalized modeling of patient anatomy and physiology promises to offer breakthrough diagnostic and therapeutic value to the medical community. In particular, the use of personalized biophysical modeling of blood flow provides important insight into disease severity and treatment effectiveness. However, effective patient modeling requires robust and precise segmentation of patient anatomy from 3D images. Graph theory has provided an extraordinary and mature set of tools for performing image segmentation, but key challenges remain. In this talk, I will discuss effective methods of image segmentation using graph theory as well as open questions and challenges.