Glaucoma is a chronic eye disease that leads to vision loss. As it cannot be cured, detecting the disease in time is important.Current tests using intraocular pressure (IOP) are not sensitive enough for population based glaucoma screening. Optic nerve head assessment in retinal fundus images is both more promising and superior. This Matlab design proposes optic disc and optic cup segmentation using superpixel classification for glaucoma screening. There are three methods to detect glaucoma: 1) assessment of raised intraocular pressure (IOP), 2) assessment of abnormal visual field, 3) assessment of damaged optic nerve head. This project focuses on superpixel classification for glaucoma screening. In optic disc segmentation, histograms, and center surround statistics are used to classify each superpixel as disc or non-disc. A self-assessment reliability score is computed to evaluate the quality of the automated optic disc segmentation. For optic cup segmentation, in addition to the histograms and center surround statistics, the location information is also included in the feature space to boost the performance. The segmented optic disc and optic cup are then used to compute the cup to disc ratio for glaucoma screening.

Superpixel based optic disc segmentation

Reference Paper: Superpixel Classification Based Optic Disc and Optic Cup Segmentation for Glaucoma Screening
Author’s Name: Jun Cheng, Jiang Liu, Yanwu Xu, Fengshou Yin, Damon Wing Kee Wong, Ngan-Meng Tan, Dacheng Tao, Ching-Yu Cheng, Tin Aung, and Tien Yin Wong
Source: IEEE
Year: 2013

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SIMULATION VIDEO DEMO                                                                                                                                     

You can DOWNLOAD dataset and sample Matlab Code with reference paper.