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GTC DC 2017

DC7126 - Deep Learning in Medical Imaging- applications in opthalmology, radiology and oncology

Session Speakers
  • Jayashree Kalpathy-Cramer - Director, QTIM lab, MGH/Harvard Medical School

    Dr. Jayashree Kalpathy-Cramer is a researcher working at the intersection of artificial intelligence and medical imaging. She is the co-director of the Quantitative Tumor Imaging at Martinos (QTIM) lab at the Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital and a PI affiliated with the Center for Clinical Data Science (CCDS). She has a Bachelor of Technology in Electrical Engineering (EE) from IIT Bombay, a Ph.D. in EE from Rensselaer Polytechnic Institute, and an M.S. in Biomedical Informatics from Oregon Health & Science University (OHSU). Her areas of research include quantitative imaging in cancer, image analysis for retinal imaging, cloud computing and machine learning.

Session Description

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. I will share out experiences addressing clinical questions in ophthalmology and radiology. In ophthalmology, we have created an automated system for classifying images for retinopathy of prematurity (ROP) using deep learning while in radiology, we have developed tools for the cancer diagnosis and assessment of response to therapy.


Additional Information
All
AI in Healthcare, Deep Learning and AI
Healthcare & Life Sciences
Talk
25 minutes
Session Schedule