A webinar organized by IEEE Sapporo Section YP will be held on October 16, 2020.
Date: 10:25-11:55 am (JST) October 16, 2020
Location: Online (Zoom)
Emerging Networks and Systems Laboratory (ENeS), Muroran Institute of Technology
IEEE Sapporo Section Young Professionals (YP)
IEEE Muroran Institute of Technology Student Branch
Please click the link right before the webinar on October 16.
Topic: Intelligent Resource Management for 5G and Future Communications
Speaker: Prof. Xin Zhu, The University of Aizu
Medical images provide essential and valuable information for the diagnosis and therapy of diseases in evidence-based clinical medicine. With the popularity of cancer and infectious diseases, huge amounts of medical images have been produced in clinical medicine. The interpretation of medical images has been a heavy burden for physicians, and the analysis accuracy heavily depends on physicians’ experiences. Computer-aided diagnosis of medical images are being widely studied with the introduction of artificial intelligence, especially, the notorious deep learning. In this lecture, we will introduce the implementation of artificial intelligence in medical image analysis in a comprehensive perspective. The main contents are as follows. 1. Background knowledge of clinical medicine and medical imaging; 2. Brief introduction about typical medical image modalities including X-ray, CT, MRI, ultrasonics, PET, and endoscopy; 3. Traditional image processing for medical images; 4. Recent studies on endoscopy images for the detection and analysis of colorectal polyps and cancer. Finally, we will introduce the limitation and future of AI in medical image analysis.
Prof. Xin Zhu obtained his Ph.D.’s degree in computer science and engineering from the University of Aizu in Aizu-Wakamatsu, Fukushima, Japan in 2006. He served as a postdoc researcher at Biomedical Information Technology Lab, the University of Aizu in 2006-2009. He became an associate professor at the same lab in 2009. Currently, he is a senior associate professor at Biomedical Information Engineering Lab, and a research leader in the Center for Advanced Information Science and Technology, the University of Aizu. His research interests include biomedical signal processing, cardiac modeling and simulation, biomedical image processing and analysis, and healthcare. Currently, his main research projects include computer modeling and simulation of implantable cardiac device, unconstrained sleep monitoring and analysis, computeraided diagnosis of colorectal tumors using colonoscopy images/videos, computer-aided diagnosis of uterus tumor using ultrasonic imaging and hysteroscopy, and computer-aided diagnosis using MRI/CT images. He won the Second Prize of Young Researcher Paper Competition of IEEE EMBC Japan Chapter, the Most Excellent Abstract Award of Implantable Cardiac Device Winter Conference, Excellent Organization Award of IEEE iCAST2015, and the most excellent paper award in IEEE iCAST2017. He has participated and led major projects funded by Japanese Ministry of Education and Fukushima prefecture. He co-organized several international conferences and served as program chairs and program committee members for international conferences. He is serving as associate editors of Journal of Biolectromagnetism, and Information Processing Transaction. He also collaborated with Softbank Innovation Corp., Nihon Kohden Corp., Fujifilm Corp., Boston Scientific Japan Corp., Medtronic Japan Corp., EKG Technology Corp., and Asahi.