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Computer-assisted Surgery using Deep Learning and Virtual Reality Techniques
Date:2018/7/17     Browse:30

Speaker:     Prof. Qin Jing. PolyU HK

Time:          14:00—15:00, July 17 

Location:    Room 1A-200, SIST Building

Host:          Prof. Xiaopei Liu

Abstract:

State-of-the-art information technologies continue to promote the development of surgical technology towards automation, intelligence and personalization. Dr. Qin and his collaborators have more than 10 years of experience in developing intelligent computer-assisted surgery systems using various machine learning and virtual reality technologies. In this talk, Dr. Qin will first introduce their recent works in using deep learning models for automated segmentation of medical images, including automated segmentation of liver CT images, automated segmentation of brain MR images, automated segmentation of cardiac MR images, automated segmentation of prostate MR images, and automated segmentation of 3D prenatal ultrasound images, etc.; these segmentation techniques lay a solid foundation for the construction of intelligent surgical training and planning systems. Subsequently, Dr. Qin will introduce several virtual reality based surgical training and planning systems developed in recent years, including orthopedic operations, ultrasound-guided interventions, radiology vascular interventions, cholecystectomy, plastic surgery and robotic surgery.

Bio: 

Dr. QIN, Jing is currently an assistant professor in the Centre for Smart Health, School of Nursing, The Hong Kong Polytechnic University. He received his PhD degree in Computer Science and Engineering from the Chinese University of Hong Kong in 2009. Dr. Qin received the Champion in The 3rd Hong Kong Innovation Day and Innovation Awards Competition, Medical Image Analysis-MICCAI’17 Best Paper Award, the Best Paper Award in Medical Image Computing in International Conference on Medical Imaging and Augmented Reality 2016, the Hong Kong Medical and Health Device Industries Association Student Research Award in 2009 and Global Scholarship Program for Research Excellence (CNOOC Grants) from CUHK in 2008. He and his collaborators were nominated for outstanding paper award in International Simulation and Gaming Association 40th Annual Conference in 2009. Dr. Qin’s research interests include medical image processing, virtual/augmented reality for healthcare and medicine training, deep learning, visualization and human-computer interaction and health informatics.

SIST-Seminar 18066