We report a novel prototype algorithm using contextual knowledge to locate ischemic regions in ultra-wide-field-of-view retinal fluorescein angiograms. We use high-resolution images acquired by an Optos ultra-wide-field-of-view (more than 200 degrees) scanning laser ophthalmoscope. We leverage the simultaneous occurrence of ischemia with a number of other signs, detected automatically, typical for the state of progress of the condition in a diabetic patient The specific nature of ischemic and non-ischemic regions is determined with an AdaBoost learning algorithm. Preliminary results demonstrate above 80% pixel classification accuracy against manual annotations. © 2007 IEEE.
|Title of host publication||29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07|
|Number of pages||4|
|Publication status||Published - 2007|
|Event||29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society - Lyon, France|
Duration: 23 Aug 2007 → 26 Aug 2007
|Conference||29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society|
|Period||23/08/07 → 26/08/07|