An improved method for retinal vessel segmentation in U-Net-Reference-Cited by-同舟云学术

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An improved method for retinal vessel segmentation in U-Net

Published:2024-03-05 Issue: Volume: Page:
ISSN:1573-7721
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Li Chunyang^ORCID,Li Zhigang^ORCID,Yu Fusheng,Liu Weikang

Funder

Liaoning Provincial Education Department's Service Local Project

Scientific Research Fund of Liaoning Provincial Education Department

Shandong Key Laboratory of Intelligent Buildings Technology

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11042-024-18757-0.pdf

Reference35 articles.

1. Javidi M, Pourreza H-R, Harati A (2017) Vessel segmentation and microaneurysm detection using discriminative dictionary learning and sparse representation. Comput Methods Programs Biomed 139:93–108

2. Wan T, Feng H, Tong C, Li D, Qin Z (2018) Automated identification and grading of coronary artery stenoses with X-ray angiography. Comput Methods Programs Biomed 167:13–22

3. Yang Y, Huang S, Rao N (2008) An automatic hybrid method for retinal blood vessel extraction. Int J Appl Math Comput Sci 18:399–407

4. Baker ML, Hand PJ, Wang JJ, Wong TY (2008) Retinal signs and stroke: revisiting the link between the eye and brain. Stroke 39:1371–1379

5. Zhao Y, Rada L, Chen K, Harding SP, Zheng Y (2015) Automated vessel segmentation using infinite perimeter active contour model with hybrid region information with application to retinal images. IEEE Trans Med Imaging 34:1797–1807

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