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|dc.identifier.citation||Pattern Recognition Letters, 2017, Vol., , pp.-||en_US|
|dc.description.abstract||Retinal cysts have pathological significance in several eye disorders. Detecting and quantifying such cysts from optical coherence tomography (OCT) scans is time-consuming and needs expertise. This paper proposes an automatic intra-retinal cyst segmentation method using marker-controlled watershed transform on OCT B-scans. Markers are obtained using k-means clustering and used as sources for topographical based watershed transform for final segmentation. The proposed method was evaluated both quantitatively and qualitatively on OPTIMA cyst challenge dataset against ground truth obtained from two graders. Experimental results show that the proposed method outperformed the other recently proposed methods. The proposed algorithm achieved a mean recall rate of 0.67 while preserving precision rate of 0.78, and gave a higher correlation rate of 0.95 with ground truth obtained from two graders. 2017 Elsevier B.V.||en_US|
|dc.title||Marker controlled watershed transform for intra-retinal cysts segmentation from optical coherence tomography B-scans||en_US|
|Appears in Collections:||1. Journal Articles|
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