![\"\"](\"https:\/\/labsites.rochester.edu\/gsharma\/wp-content\/uploads\/2020\/04\/pipeline_overview.png\")
<\/p>\nLi Ding, Mohammad H. Bawany, Ajay E. Kuriyan, Rajeev S. Ramchandran, Charles C. Wykoff, and Gaurav Sharma, “A Novel Deep Learning Pipeline for Retinal Vessel Detection In Fluorescein Angiography”, IEEE Transactions on Image Processing, vol. 29, no. 1, pp. 6561\u20136573, 2020<\/p>\n
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While recent advances in deep learning have significantly advanced the state of the art for vessel detection in color fundus (CF) images, the success for detecting vessels in fluorescein angiography (FA) has been stymied due to the lack of labeled ground truth datasets. We propose a novel pipeline to detect retinal vessels in FA images using deep neural networks (DNNs) that reduce the effort required for generating labeled ground truth data by combining two key components: cross-modality transfer and human-in-the-loop learning.<\/p>\n
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![\"\"](\"https:\/\/labsites.rochester.edu\/gsharma\/wp-content\/uploads\/2020\/04\/recovery_fa19_overview.png\")
Example of labeled ground truth vessel map from the RECOVERY-FA19 dataset. Enlarged views of cyan rectangles are shown on the right (top: original view; middle: contrast-enhanced view; bottom: labeled ground truth).<\/p><\/div>\n
![\"\"](\"https:\/\/labsites.rochester.edu\/gsharma\/wp-content\/uploads\/2020\/05\/Quant_RECOVERY-FA19-1024x376.png\")
(a) ROC, (b) PR, and (c) CAL curves for different methods on the RECOVERY-FA19 dataset. The gray curves in (b) represent the isolines of Dice coefficients. The small circular dots on the curves in (a) and (b) identify the corresponding values of the threshold.<\/p><\/div>\n
![\"\"](\"https:\/\/labsites.rochester.edu\/gsharma\/wp-content\/uploads\/2020\/05\/Qual_RECOVERY-FA19.png\")
Qualitative comparison of results obtained with different algorithms for images from the RECOVERY-FA19 dataset. For each full image, two contrast-enhanced enlarged views of the selected regions (shown by cyan rectangles) are also included.<\/p><\/div>\n
Publication<\/strong><\/span><\/p>\n