Research on vessel segmentation and extraction based on 2-D Gabor features and U-Net

Mao Shi

doi:10.1117/12.2660079

6 December 2022 Research on vessel segmentation and extraction based on 2-D Gabor features and U-Net

Mao Shi

Proceedings Volume 12458, International Conference on Biomedical and Intelligent Systems (IC-BIS 2022); 1245842 (2022) https://doi.org/10.1117/12.2660079
Event: International Conference on Biomedical and Intelligent Systems, 2022, Chengdu, China

Abstract

This paper proposed a vessel segmentation method based on Gabor features and U-Net. According to the eigenvectors of Hessian matrix of each pixel in the image, the vessel direction of each point was obtained to set the direction of Gabor filter, and the Gabor features of different vessel width at each point were extracted to establish the 6-D vectors of each point. By reducing the dimension of the 6-D vector, the 2-D vector of each point was obtained and fused with the original image G channel. U-Net was used to classify the fused image to segment vessels. The experimental results of this method in DRIVE dataset showed that this method had a good effect on the detection of small vessels and vessels at the intersection.

Citation Download Citation

Mao Shi "Research on vessel segmentation and extraction based on 2-D Gabor features and U-Net", Proc. SPIE 12458, International Conference on Biomedical and Intelligent Systems (IC-BIS 2022), 1245842 (6 December 2022); https://doi.org/10.1117/12.2660079

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