Bridge-Net: Context-involved U-net with patch-based loss weight mapping for retinal blood vessel segmentation
作者：
Highlights：
• We present a novel automatic method for the segmentation of retinal blood vessels.
• We propose Bridge-net by joint learning context-involved and non-context features.
• We develop a patch-based loss weight mapping to correct the imbalance of the image.
• We evaluate the effectiveness of the proposed method on four public datasets.
• The results have verified the effectiveness and stability of the proposed method.
摘要
•We present a novel automatic method for the segmentation of retinal blood vessels.•We propose Bridge-net by joint learning context-involved and non-context features.•We develop a patch-based loss weight mapping to correct the imbalance of the image.•We evaluate the effectiveness of the proposed method on four public datasets.•The results have verified the effectiveness and stability of the proposed method.
论文关键词：Retinal blood vessels,Segmentation,Context information,Deep neural networks,Patch-based loss weight mapping
论文评审过程：Received 26 April 2021, Revised 5 September 2021, Accepted 7 January 2022, Available online 29 January 2022, Version of Record 3 February 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.116526
