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VISUAL SALIENCY BASED BRIGHT LESION DETECTION AND DISCRIMINATION IN RETINAL IMAGESAuthors: ujjwal,Sai Deepak,Arunava Chakravarty,Jayanthi Sivaswamy Conference: IEEE 10th International Symposium on Biomedical Imaging : From Nano to Macro, 07-11 April. 2013, San Franciso,CA,USA. Date: 2013-04-07 Report no: IIIT/TR/2013/65 AbstractAbnormality detection is the first step performed by doctors during evaluation of medical images in image based diagno- sis, followed by disease-specific evaluation of abnormalities. Perception studies have shown that experts primarily focus on abnormal structures during visual examination for diagnosis. One way to model this behavior in automated image analy- sis is through visual saliency computation. In this paper, we investigate the potential role of visual saliency for computer aided diagnosis algorithm design. We propose a framework for detecting abnormalities that uses visual saliency compu- tation for sparse representation of the image data that pre- serves the essential features of a normal image. The proposed method is evaluated for the task of bright lesion detection and classification in color retinal images which is of significance in disease screening. An evaluation of the proposed approach on 5 publicly available datasets yielded area under ROC curve of 0.88 to 0.98 for the detection task and accuracies ranging from 0.93 to 0.96 for lesion discrimination. These results es- tablish visual saliency as an alternate avenue for automated abnormality detection. Full paper: pdf Centre for Visual Information Technology |
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