A new retinal vessel segmentation algorithm based on saliency-guided level set

Xiyin Wu; Qianru Wu; Junjie Peng

doi:10.1117/12.3036859

13 July 2024 A new retinal vessel segmentation algorithm based on saliency-guided level set

Xiyin Wu, Qianru Wu, Junjie Peng

Proceedings Volume 13208, Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024); 1320825 (2024) https://doi.org/10.1117/12.3036859
Event: 3rd International Conference on Biomedical and Intelligent Systems (IC-BIS 2024), 2024, Nanchang, China

Abstract

Optical Coherence Tomography Angiography (OCTA) provides an innovative method for obtaining information on the depth of retinal vascular blood flow. However, the accuracy and efficiency of OCTA vessel segmentation limits its clinical application. To address this problem, we explore a novel model to generate vascular saliency maps based on random walks, thereby improving the accuracy and stability of segmentation. On this basis, three salient features are innovatively used to generate seed points, which are combined with random walks to generate a saliency map and incorporated into a level set image segmentation model to propose a saliency-guided retinal vessel segmentation algorithm to solve the application problems effectively. The results of experiments conducted on OCTA-DB image datasets demonstrate that the proposed algorithm is capable of markedly enhancing the precision of vessel segmentation.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiyin Wu, Qianru Wu, and Junjie Peng "A new retinal vessel segmentation algorithm based on saliency-guided level set", Proc. SPIE 13208, Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024), 1320825 (13 July 2024); https://doi.org/10.1117/12.3036859

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