Medical Image Data Analytics Platform

Medical Image Data Analytics Platform

  • Medical Image Data Analytics Platform
    ART/210CP
    20160201 - 20170731
    11930

    Dr Xiaohua WU
    1.Develop a pathology image data analytics platform including: (a) a distributed pathology image data storage and management system (b) a parallel computing engine and function library for pathology image analytics (c) a development interface supporting large data visualization and statistics 2.Develop a standard recommendation for web-based digital pathology information exchange in tele-diagnosis including: (a) an annotation and markup data model (b) a cross platform image viewer 3.Develop two computer-aided diagnosis applications through the medical image data analytics platform, with measurable performance benchmark comparison to existing systems
    Dr Che-I, Justin Chuang Mr Yee Lim Chan Miss Yee Wai, Mandy Yim Mr Ka Yuk Lee Dr Lu Wang Mr Hangqiang Huang Mr Pan Lit Wong Dr Yan Nei, Ivy Law Dr Cheung Ming, Denny Lai Mr Yat Cheung, Louis Ngai Mr Fuchun, Fred Li Mr Chun Chung Lo Mr Xiaodong Yu Mr Chi Ming, Tony Leung Mr Chi Chung, David Leung Miss Hua Yang Mr Shengpeng, Tony Wu Miss Yin Yee, Brenda Chan Mr Chi Chung, Jackie Chau Mr Kwok Hung, Billy Leung Mr Sai Hung, Teddy Chu Mr Rihong, Billy Chen Mr Hanbin Jian
    Aircraft Medical [Sponsor] KingMed Diagnostics KingMed Diagnostics (Technology Licensing) [Sponsor]

    With current medical imaging technology advancement, service providers more rely on various imaging modalities to make clinical decisions routinely. Currently 80% of medical data are images and they are increasing 20-40% annually, such a large data volume poses both challenges and opportunities to healthcare service providers. Challenges are how to manage the image data in a scalable way and use them to create value instead of just storing them, and opportunities are knowledge generation for higher quality diagnostic service and more efficient clinical workflow through intelligent image analytics. In this project, we aim to develop a medical image analytics platform which will leverage on advanced computation technologies to address the medical imaging big data problem, particularly on next generation medical image data mining and computer aided diagnosis development. This analytics platform, with scalable medical image database, distributed parallel computing engine, and powerful application development environment, will support both efficient management of medical image big data and agile development of computer aided diagnosis applications.