Local characterization of neovascularization and identification of proliferative diabetic retinopathy in retinal fundus images

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• 作者：Garima Gupta^a ; ^{ee12s055@ee.iitm.ac.in} ; S. Kulasekaran^b ; Keerthi Ram^b ; ^{keerthi@htic.iitm.ac.in} ; Niranjan Joshi^b ; ^{jniranjan@gmail.com} ; Mohanasankar Sivaprakasam^a ; ^b ; ^{mohan@ee.iitm.ac.in} ; Rashmin Gandhi^c
• 关键词：Computer-assisted screening ; Texture ; Classification ; Evaluation
• 刊名：Computerized Medical Imaging and Graphics
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：55
• 期：Complete
• 页码：124-132
• 全文大小：1607 K
• 卷排序：55

文摘

Neovascularization (NV) is a characteristic of the onset of sight-threatening stage of DR, called proliferative DR (PDR). Identification of PDR requires modeling of these unregulated ill-formed vessels, and other associated signs of PDR. We present an approach that models the micro-pattern of local variations (using texture based analysis) and quantifies structural changes in vessel patterns in localized patches, to arrive at a score of neovascularity. The distribution of patch-level confidence scores is collated into an image-level decision of presence or absence of PDR. Evaluated on a dataset of 779 images combining public data and clinical data from local hospitals, the patch-level neovascularity prediction has a sensitivity of 92.4% at 92.6% specificity. For image-level PDR identification our method is shown to achieve sensitivity of 83.3% at a high specificity operating point of 96.1% specificity, and specificity of 83% at high sensitivity operating point of 92.2% sensitivity. Our approach could have potential application in DR grading where it can localize NVE regions and identify PDR images for immediate intervention.