title: Contextual detection of ischemic regions in ultra-wide-field-of-view retinal fluorescein angiograms.
abstract: 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.
authors.affiliation: School of Computing, University of Dundee, UK. e.trucco@hw.ac.uk
authors.forename: E
authors.initials: E
authors.lastname: Trucco
authors.forename: C R
authors.initials: CR
authors.lastname: Buchanan
authors.forename: T
authors.initials: T
authors.lastname: Aslam
authors.forename: B
authors.initials: B
authors.lastname: Dhillon
mesh_terms: D000465:Algorithms; D003930:Diabetic Retinopathy / Q000175:diagnosis*; D005451:Fluorescein Angiography / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007511:Ischemia / Q000175:diagnosis*; D012171:Retinal Vessels / Q000473:pathology