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8 November 2023 Retinal vessel segmentation via deep hierarchical semantic segmentation and closing operation
Yi He, Mingdi Bao, Xin Zhang, Lina Xing, Guohua Shi, Yiwei Chen
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Proceedings Volume 12923, Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023); 129231D (2023) https://doi.org/10.1117/12.3011488
Event: 3rd International Conference on Artificial Intelligence, Virtual Reality and Visualization (AIVRV 2023), 2023, Chongqing, China
Abstract
Our retinal vessel segmentation approach utilizes deep hierarchical semantic segmentation along with a closing operation. From fundus images, the retinal vessels are extracted using the supervised learning segmentation algorithm. Deep semantic segmentation that provides a hierarchical solution is adopted for rough retinal vessel segmentation. The rough segmentation results are then processed by a closing operation to refine the segmented retinal vessels. We performed experiments and comparisons with ground truths to evaluate the qualitative and quantitative effectiveness of our method. Our method effectively segments retinal vessels, as demonstrated by the experimental results.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Yi He, Mingdi Bao, Xin Zhang, Lina Xing, Guohua Shi, and Yiwei Chen "Retinal vessel segmentation via deep hierarchical semantic segmentation and closing operation", Proc. SPIE 12923, Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023), 129231D (8 November 2023); https://doi.org/10.1117/12.3011488
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KEYWORDS
Image segmentation
Machine learning
Image processing
Retinal diseases
Vascular diseases
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