Deep angiogram: trivializing retinal vessel segmentation

Dewei Hu; Xing Yao; Jiacheng Wang; Yuankai K. Tao; Ipek Oguz

doi:10.1117/12.2654214

3 April 2023 Deep angiogram: trivializing retinal vessel segmentation

Dewei Hu, Xing Yao, Jiacheng Wang, Yuankai K. Tao, Ipek Oguz

Proceedings Volume 12464, Medical Imaging 2023: Image Processing; 124642U (2023) https://doi.org/10.1117/12.2654214
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

Among the research efforts to segment the retinal vasculature from fundus images, deep learning models consistently achieve superior performance. However, this data-driven approach is very sensitive to domain shifts. For fundus images, such data distribution changes can easily be caused by variations in illumination conditions as well as the presence of disease-related features such as hemorrhages and drusen. Since the source domain may not include all possible types of pathological cases, a model that can robustly recognize vessels on unseen domains is desirable but remains elusive, despite many proposed segmentation networks of ever-increasing complexity. In this work, we propose a contrastive variational auto-encoder that can filter out irrelevant features and synthesize a latent image, named deep angiogram, representing only the retinal vessels. Then segmentation can be readily accomplished by thresholding the deep angiogram. The generalizability of the synthetic network is improved by the contrastive loss that makes the model less sensitive to variations of image contrast and noisy features. Compared to baseline deep segmentation networks, our model achieves higher segmentation performance via simple thresholding. Our experiments show that the model can generate stable angiograms on different target domains, providing excellent visualization of vessels and a non-invasive, safe alternative to fluorescein angiography.

Citation Download Citation

Dewei Hu, Xing Yao, Jiacheng Wang, Yuankai K. Tao, and Ipek Oguz "Deep angiogram: trivializing retinal vessel segmentation", Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124642U (3 April 2023); https://doi.org/10.1117/12.2654214

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