10.30 – 11.00 Hao Chen - Deep Learning for Large-scale Histopathology Image Analysis

Deep learning represents data with multiple levels of abstraction and has dramatically improved the state-of-the-art in many domains including speech recognition, visual object recognition and natural language processing. Despite its breakthroughs in above domains, its application to large-scale and high-throughout histology image analysis remains to be under-explored. This talk will share our recent studies on developing state-of-the-art deep learning methods including ScanNet, and weakly multi-instance supervised learning for fast and accurate large-scale histology image analysis, with an in-depth dive into several cancer applications.

CV Dr. Hao Chen is a post-doc fellow in The Chinese University of Hong Kong (CUHK). He founded Imsight Medical Technology, a leading AI medical imaging startup for histology image analysis. Previously he received the PhD from CUHK and obtained the award of HKPFS in 2013. He won the Best Paper Awards in MIAR 2016 and MIA-Elsevier 2017. His research interests include medical image analysis and deep learning. He has published more than 50 papers in top-tier conferences and journals. He serves as the reviewer for a dozen of premium conferences and journals including NIPS, MIA, TMI, NeuroImage, etc. The team he led has won 16 grand challenges on medical image computing, such as GlaS Contest@2015MICCAI, LUNA Challenge@2016ISBI, etc.