Abhijit Thatte leads the big data and analytics initiatives at GE enabling unique insights for GE's Internet of Things solutions. He is passionate about creating innovative solutions in analytics to fulfill unmet market needs across several verticals such as Healthcare, Finance, Semiconductors, Aviation, Energy & Transportation. He has 15+ years of experience in various roles in Software industry.
Room: N-124 | Time: 4:00pm - 4:20pm
Hogkin's Lymphoma is one of the common tumors that can be treated effectively if diagnosed in early stages. The presence of Reed Sternberg cells is a strong indicator of Hodkin's Lymphoma. Searching for small number of Reed Sternberg cells in early stage Hogkin's Lymphoma tissue sample is similar to looking for a needle in a haystack. Computer can be trained to recognize Reed Sternberg cells using deep learning techniques to accurately identify Reed Sternberg cells in pathological images. This talk will present the architecture of a deep learning network to identify Reed Sternberg cells, discuss performance numbers and demonstrate examples of identification. The talk will also feature generality of the architecture approach to other types of image segmentation and object recognition for healthcare and other domains.