2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDBIO-2.1
Paper Title CONSISTENT POSTERIOR DISTRIBUTIONS UNDER VESSEL-MIXING: A REGULARIZATION FOR CROSS-DOMAIN RETINAL ARTERY/VEIN CLASSIFICATION
Authors Chenxin Li, Yunlong Zhang, Zhehan Liang, Wenao Ma, Yue Huang, Xinghao Ding, Xiamen University, China
SessionBIO-2: Biomedical Signal Processing 2
LocationArea D
Session Time:Tuesday, 21 September, 08:00 - 09:30
Presentation Time:Tuesday, 21 September, 08:00 - 09:30
Presentation Poster
Topic Biomedical Signal Processing: Medical image analysis
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Retinal artery/vein (A/V) classification is a critical technique for diagnosing diabetes and cardiovascular diseases. Although deep learning based methods achieve impressive results in A/V classification, the performance usually degrades when directly apply the models that trained on one dataset to another set, due to the domain shift, e.g., caused by the variations in imaging protocols. In this paper, we propose a novel method to improve cross-domain generalization for pixel-wise retinal A/V classification. That is, vessel-mixing based consistency regularization, which regularizes the models to give consistent posterior distributions for vessel-mixing samples. The proposed method achieves the state-of-the-art performance on extensive experiments for cross-domain A/V classification, which is even close to the performance of fully supervised learning on target domain in some cases.