A Detailed Systematic Review on Retinal Image Segmentation Methods
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology
Link
https://link.springer.com/content/pdf/10.1007/s10278-022-00640-9.pdf
Reference123 articles.
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2. Zhang B, Zhang L, Zhang L, Karray F: Retinal vessel extraction by matched filter with first-order derivative of Gaussian. Comput Biol Med 40(4):438-445, 2010. https://doi.org/10.1016/j.compbiomed.2010.02.008
3. Biswal B, Pooja T, Subrahmanyam NB: Robust retinal blood vessel segmentation using line detectors with multiple masks. IET Image Process 12(3):389-399, 2017. https://doi.org/10.1049/iet-ipr.2017.0329
4. Marín D, Aquino A, Gegundez-Arias ME, Bravo Caro JM: A new supervised method for blood vessel segmentation in retinal images by using gray-level and moment invariants-based features. IEEE Trans Med Imaging 30(1):146-158, 2010. https://doi.org/10.1109/TMI.2010.2064333
5. Wu Y, Xia Y, Song Y, Zhang Y, Cai W: NFN+: A novel network followed network for retinal vessel segmentation. Neural Netw, 2020. https://doi.org/10.1016/j.neunet.2020.02.018
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