GAMMA Challenge:Glaucoma grAding from Multi-Modality imAges
Abstract
Color fundus photography and Optical Coherence Tomography (OCT) are the two most cost-effective tools for glaucoma screening. Both two modalities of images have prominent biomarkers to indicate glaucoma suspected. Clinically, it is often recommended to take both of the screenings for a more accurate and reliable diagnosis. However, although numerous algorithms are proposed based on fundus images or OCT volumes in computer-aided diagnosis, there are still few methods leveraging both of the modalities for the glaucoma assessment. Inspired by the success of Retinal Fundus Glaucoma Challenge (REFUGE) we held previously, we set up the Glaucoma grAding from Multi-Modality imAges (GAMMA) Challenge to encourage the development of fundus \& OCT-based glaucoma grading. The primary task of the challenge is to grade glaucoma from both the 2D fundus images and 3D OCT scanning volumes. As part of GAMMA, we have publicly released a glaucoma annotated dataset with both 2D fundus color photography and 3D OCT volumes, which is the first multi-modality dataset for glaucoma grading. In addition, an evaluation framework is also established to evaluate the performance of the submitted methods. During the challenge, 1272 results were submitted, and finally, top-10 teams were selected to the final stage. We analysis their results and summarize their methods in the paper. Since all these teams submitted their source code in the challenge, a detailed ablation study is also conducted to verify the effectiveness of the particular modules proposed. We find many of the proposed techniques are practical for the clinical diagnosis of glaucoma. As the first in-depth study of fundus \& OCT multi-modality glaucoma grading, we believe the GAMMA Challenge will be an essential starting point for future research.
Cite
@article{arxiv.2202.06511,
title = {GAMMA Challenge:Glaucoma grAding from Multi-Modality imAges},
author = {Junde Wu and Huihui Fang and Fei Li and Huazhu Fu and Fengbin Lin and Jiongcheng Li and Lexing Huang and Qinji Yu and Sifan Song and Xinxing Xu and Yanyu Xu and Wensai Wang and Lingxiao Wang and Shuai Lu and Huiqi Li and Shihua Huang and Zhichao Lu and Chubin Ou and Xifei Wei and Bingyuan Liu and Riadh Kobbi and Xiaoying Tang and Li Lin and Qiang Zhou and Qiang Hu and Hrvoje Bogunovic and José Ignacio Orlando and Xiulan Zhang and Yanwu Xu},
journal= {arXiv preprint arXiv:2202.06511},
year = {2022}
}