Evaluation indicator.
Version 1Retinal blood vessels are of different sizes and shapes, and even contain very fine capillaries with complex structural morphology, making accurate segmentation a difficult task. To address the above problems, we propose an improved retinal segmentation method DMSU-Net++ (Double Multiscale U-Net++) based on U-Net++. The method innovatively introduces a multiscale feature extraction module WTSAFM, which realises multiscale feature extraction via wavelet transform, and can capture image informatio
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Retinal blood vessels are of different sizes and shapes, and even contain very fine capillaries with complex structural morphology, making accurate segmentation a difficult task. To address the above problems, we propose an improved retinal segmentation method DMSU-Net++ (Double Multiscale U-Net++) based on U-Net++. The method innovatively introduces a multiscale feature extraction module WTSAFM, which realises multiscale feature extraction via wavelet transform, and can capture image informatio