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Abstract #89885 Published in IGR 21-3
Automatic Glaucoma Detection from Stereo Fundus Images
Ong EP; Cheng J; Wong DWK; Tay ELT; Teo HY; Grace Loo R; Yip LWLAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 2020; 2020: 1540-1543
This paper proposes a new method for automatic detection of glaucoma from stereo pair of fundus images. The basis for detecting glaucoma is using the optic cup-to-disc area ratio, where the surface area of the optic cup is segmented from the disparity map estimated from the stereo fundus image pair. More specifically, we first estimate the disparity map from the stereo image pair. Then, the optic disc is segmented from one of the stereo image. Based upon the location of the optic disc, we perform an active contour segmentation on the disparity map to segment the optic cup. Thereafter, we can compute the optic cup-to-disc area ratio by dividing the area (i.e. the total number of pixels) of the segmented optic cup region to that of the segmented optic disc region. Our experimental results using the available test dataset shows the efficacy of our proposed approach.
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Classification:
6.8.2 Posterior segment (Part of: 6 Clinical examination methods > 6.8 Photography)
6.9.5 Other (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis)
