GAMMA Challenge
Introduced by Wu et al. in GAMMA Challenge:Glaucoma grAding from Multi-Modality imAges
GAMMA releases the world's first multi-modal dataset for glaucoma grading, which was provided by the Sun Yat-sen Ophthalmic Center of Sun Yat-sen University in Guangzhou, China. The dataset consists of 2D fundus images and 3D optical coherence tomography (OCT) images of 300 patients. The dataset was annotated with glaucoma grade in every sample, and macular fovea coordinates as well as optic disc/cup segmentation mask in the fundus image.
We invite the medical image analysis community to participate by developing and testing existing and novel automated classification and segmentation methods.
GAMMA challenge consists of THREE Tasks:
Grading glaucoma using multi-modality data
Segmentation of optic disc and cup in fundus images
Localization of fovea macula in fundus image
Papers
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