Project Title:
Medical Image Data Analytics Platform
Project Reference:
ART/210CP
Project Period:
20160201 - 20170731
Funds Approved (HK$’000):
11930
Project Coordinator:
Dr Xiaohua WU
Deputy Project Coordinator:
/
Deliverable:
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
Research Group:
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
Sponsor:
Aircraft Medical [Sponsor]
KingMed Diagnostics
KingMed Diagnostics (Technology Licensing) [Sponsor]
Description:
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.
