Prof. Kenji SuzukiTokyo Institute of Technology, Japan
AI-aided Diagnostic Systems and Virtual AI Imaging in Medicine
Deep leaning becomes one of the most active areas of research in many imaging fields, including medical imaging. My group has been actively studying on deep learning in medical imaging in the past 25 years, including ones of the earliest deep-learning models for image processing, semantic segmentation, object enhancement, and classification of patterns in medical imaging. In this talk, AI-aided diagnostic systems ("AI doctor") and deep-learning-based imaging for diagnosis ("Virtual AI imaging") are introduced, including 1) intelligent AI systems for cancer detection and diagnosis in medical images, and 2) virtual AI imaging systems for separation of bones from soft tissue in chest radiographs and those for radiation dose reduction in CT and mammography. Some of them have been commercialized via FDA approval in the U.S., including the first FDA-approved deep-learning product.
Kenji Suzuki, Ph.D. is a Professor (Tenured) & Director of Biomedical AI Research Unit, Institute of Innovative Research, Tokyo Institute of Technology, Japan. Prior faculty experiences include Assistant Professor at University of Chicago and Associate Professor at Illinois Institute of Technology. He published more than 340 papers (including 115 peer-reviewed journal papers). He has been actively researching on deep learning in medical imaging and AI-aided diagnosis in the past 25 years, especially his early deep-learning model was proposed in early 1990s. His papers were cited 14,000 times, and his h-index is 54. He is inventor on 36 patents (including ones of earliest deep-learning patents), which were licensed to several companies and commercialized (via FDA approval). He published 14 books and edited 12 journal special issues. He has been awarded numerous grants including NIH, NEDO, and JST grants, totaling a dozen M dollars. He served as Editors of 40 leading international journals including Pattern Recognition. He chaired 100 international conferences and gave 130 keynote/invited talks. He received 21 awards, including 3 Best Paper Awards in leading journals and MEXT Award for Science and Technology.
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