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David Carleton Reed, Sanket U Shah, Kris Zutis, Emanuele Trucco, Jean-Pierre Hubschman; Fully Automated Detection of Abnormal Capillaries in Ultra-Wide-Field Fluorescein Angiography of Branch Retinal Vein Occlusion. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):5265.
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© ARVO (1962-2015); The Authors (2016-present)
Our objective was to develop a prototype fully automated detector for capillary abnormalities in ultra-wide-field fluorescein angiograms (UWFA) of branch retinal vein occlusion (BRVO).
Four new UWFAs of BRVO were obtained. For each case, three annotations of abnormal capillaries were created by two independent clinicians. Intra- and inter-grader agreement was measured. Composite annotations were created for algorithm validation. An automated algorithm for detection of abnormal capillaries in BRVO was prospectively tested against these composite annotations.
Near-perfect intra-grader agreement (Fleiss’ kappa range 0.81 - 0.92) and substantial inter-grader agreement (Cohen’s kappa range 0.73 - 0.84) was found among human annotations. Substantial agreement was found between composite annotations and the output of the fully automated detector (Cohen’s kappa for Case 1: 0.59, Case 2: 0.72, Case 3: 0.58, Case 4: 0.69).
Our fully automated algorithm showed good agreement with human expert annotations.
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