BCR-UNet: Bi-directional ConvLSTM residual U-Net for retinal blood vessel segmentation

• Published in: Frontiers in public health Vol. 10; p. 1056226
• Main Authors: Yi, Yugen, Guo, Changlu, Hu, Yangtao, Zhou, Wei, Wang, Wenle
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 22.11.2022
• Subjects: Bi-directional ConvLSTM; Humans; Neural Networks, Computer; Public Health; residual convolution; retinal blood vessels; Retinal Vessels - diagnostic imaging; segmentation; U-Net; Bi-directional ConvLSTM; segmentation; residual convolution; retinal blood vessels; U-Net

High precision segmentation of retinal blood vessels from retinal images is a significant step for doctors to diagnose many diseases such as glaucoma and cardiovascular diseases. However, at the peripheral region of vessels, previous U-Net-based segmentation methods failed to significantly preserve...