IterNet++: An improved model for retinal image segmentation by curvelet enhancing, guided filtering, offline hard‐sample mining, and test‐time augmenting
Abstract In clinical medicine, the segmentation of blood vessels in retinal images is essential for subsequent analysis in clinical diagnosis. However, retinal images are often noisy and their vascular structure is relatively tiny, which poses significant challenges for vessel segmentation. To impro...
Main Authors: | M. Zhu, K. Zeng, G. Lin, Y. Gong, T. Hao, K. Wattanachote, X. Luo |
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Format: | Article |
Language: | English |
Published: |
Wiley
2022-11-01
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Series: | IET Image Processing |
Online Access: | https://doi.org/10.1049/ipr2.12580 |
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