Published works in Medical Physics and Medical Image Analysis journals regarding the use of deep learning methods to distinguish between types of prostate cancer based on pathology data.
Research Experience
Director of the Laboratory for Integrative Personalized Medicine (PIMed) at Stanford University School of Medicine, Department of Radiology, Division of Integrative Biomedical Imaging Informatics; collaborates closely with the Urologic Cancer Innovation Lab at Stanford for work related to prostate cancer.
Background
Research interests include the development of analytic methods for biomedical data integration, with a particular focus on radiology-pathology fusion to facilitate radiology image labeling. Recent research has been centered around applying deep learning methods to detect and differentiate aggressive from indolent prostate cancers on MRI using pathology information.
Miscellany
Latest news and updates can be found by following @StanfordPimed or @DrMi on Twitter.