Deep Learning in Medical Imaging-Opportunities and Challenges







Speaker: Jayashree Kalpathy-Cramer

Seminar Title: Deep Learning in Medical Imaging-Opportunities and Challenges

Date: September 27

Time: 4-5 pm

Location: SMPH/HSLC Room 1345

Abstract: Deep learning, facilitated by advances in hardware, software and algorithms, has emerged as a leading technology in computer vision and image analysis and is being applied to medical imaging with early successes in radiology, oncology, ophthalmology, pathology and others domains. In this talk, I will discuss recent applications of deep learning to specific clinical problems in these domains. We will then discuss some of the gaps and challenges with current deep learning techniques and suggest topics for further research. Finally, we will touch upon the translational aspects of these technologies.

Bio: Jayashree Kalpathy-Cramer is the Director of the QTIM lab and the Center for Machine Learning at the Athinoula A. Martinos Center  for Biomedical Imaging and an Associate Professor of Radiology at MGH/Harvard Medical School. She earned a B.Tech in Electrical Engineering from IIT, Bombay, India, an MS and PhD in Electrical Engineering from Rensselaer Polytechnic Institute and an MS in Biomedical Informatics from Oregon Health and Science University. Her areas of research interest include medical image analysis, machine learning and artificial intelligent for applications in radiology, oncology and ophthalmology. Recently, her lab has been actively working in the applications of deep learning to clinical problems in ophthalmology, oncology and radiology. She has authored over a 100 peer-reviewed publications and over 10 book chapters.