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Retinal Vessels Segmentation Based on Dilated Multi-Scale Convolutional Neural Network
In the proposed D-Net, the dilation convolution is used in the backbone network to obtain a larger receptive field without losing spatial resolution, so as to reduce the loss of feature information and to reduce the difficulty of tiny thin vessels segmentation.
Retinal Vessel Segmentation Based on Conditional Deep Convolutional Generative Adversarial Networks
However, existing methods have various problems in the segmentation of the retinal vessels, such as insufficient segmentation of retinal vessels, weak anti-noise interference ability, and sensitivity to lesions, etc.
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