Computer Aided Diagnosis and Out-of-Distribution Detection in Glaucoma Screening Using Color Fundus Photography

• URL: http://arxiv.org/abs/2202.11944v1
• Date: Thu, 24 Feb 2022 08:00:04 GMT
• Title: Computer Aided Diagnosis and Out-of-Distribution Detection in Glaucoma Screening Using Color Fundus Photography
• Authors: Satoshi Kondo, Satoshi Kasai, Kosuke Hirasawa
• Abstract summary: This report describes our method submitted to the AIROGS challenge. Our method employs convolutional neural networks to classify input images to "referable glaucoma" or "no referable glaucoma"
• Score: 0.10312968200748115
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Artificial Intelligence for RObust Glaucoma Screening (AIROGS) Challenge is held for developing solutions for glaucoma screening from color fundus photography that are robust to real-world scenarios. This report describes our method submitted to the AIROGS challenge. Our method employs convolutional neural networks to classify input images to "referable glaucoma" or "no referable glaucoma". In addition, we introduce an inference-time out-of-distribution (OOD) detection method to identify ungradable images. Our OOD detection is based on an energy-based method combined with activation rectification.

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