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National news Time: the 2011-03-28   source:   【big | medium | small】  【print

Prof. You Jia, from Hong Kong Polytechnic University, Visits XIOPM

 Professor You Jia from Hong Kong Polytechnic University visited Xi’an Institute of Optics and Precision Mechanics (XIOPM), CAS, invited by Optical Image Analysis and Learning Center (OPTIMAL) of XIOPM, on March 25, 2011. He made an academic report entitled "Computer-Aided Non-Invasive Monitoring System of Diabetes Based on Multi-Level Image Analysis of Retinal" and nearly 50 people attended the meeting including research staffs from XIOPM and Xidian University.

Dr. You Jia is a professor at Department of Computing, a chairman of Academic Committee and a Chinese Liaison Officer at Hong Kong Polytechnic University. He has been teaching at The University of South Australia and Griffith University. Dr. You Jia is mainly engaged in the research of computer-aided medical monitoring systems, image processing, pattern recognition, multimedia systems and applications, data mining, etc. He led the Oak Medical Innovation Team to develop a new generation of computer-aided non-invasive monitoring system of diabetes based on multi-level image analysis of retinal, which will participate the 39 International Invention Exhibition held in Geneva, Switzerland, 6-10 April 2011, on behalf of Hong Kong Polytechnic University.

Professor You Jia made a detailed exposition of R&D background, principles and purposes of the project---"Computer-Aided Non-Invasive Monitoring System of Diabetes Based on Multi-Level Image Analysis of Retinal" in the report. The project is the unique utilization of the latest technology of optical and image processing and analysis and the development of intelligent medical diagnosis and monitoring system based on high-performance fundus camera, which is the implementation of intelligent, automatic and objective medical diagnosis. The intelligent medical diagnosis and monitoring system of retinopathy developed by the project uses a special lighting design and positioning design for the human eye, the technical performance of which is superior to the existing foreign series of fundus camera. The project’s software system provides the proprietary and optimized multi-level hierarchical dynamic image feature extraction, synthesis, classification and identification techniques and algorithms to achieve the automatic analysis of retinal images and the effective disease diagnosis and monitoring, which is the international initiative both in theory and clinical validation.

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