EPSRC Reference: |
GR/N08810/01 |
Title: |
VITAL: VISUAL TRACKING FOR ACTIVE LEARNING |
Principal Investigator: |
Yang, Professor G |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Computing |
Organisation: |
Imperial College London |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
01 September 2000 |
Ends: |
29 February 2004 |
Value (£): |
220,139
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EPSRC Research Topic Classifications: |
Artificial Intelligence |
Image & Vision Computing |
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EPSRC Industrial Sector Classifications: |
No relevance to Underpinning Sectors |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
Although computerised decision support has been increasingly applied to assist diagnosis in medical imaging, to data there has been no generic way of designing such systems. Each application is treated as a new problem, and requires extensive interaction between radiologists and computer scientists in order to identify characteristic visual features. The process is hampered by the fact that visual features are difficult to describe and assimilation of near-subliminal information is cryptic. These drawbacks call for the development of a general framework for a natural and systematic way of gathering knowledge from domain experts. The goal of this research is to investigate the hypothesis that information about fixation points and the dynamics of saccadic eye movement of experienced observers will prove effective in deriving a new framework for knowledge gathering in medical imaging. The proposed method does not rely on explicit listing of visual features and allows incorporation of implicit domain knowledge that is subconsciously applied but can not be easily elaborated using conventional approaches. By approaching the problem from how visual search is carried out by experienced observers, it will also open new possibilities for computer based training and the development of self-learning diagnostic decision support systems.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.imperial.ac.uk |