Pytorch复现U-Net, R2U-Net, Attention U-Net, Attention R2U-Net

Pytorch复现U-Net, R2U-Net, Attention U-Net, Attention R2U-Net

项目地址：pytorch Implementation of U-Net, R2U-Net, Attention U-Net, Attention R2U-Net

U-Net, R2U-Net, Attention U-Net, Attention R2U-Net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://arxiv.org/abs/1505.04597

Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

https://arxiv.org/abs/1802.06955

Attention U-Net: Learning Where to Look for the Pancreas

https://arxiv.org/abs/1804.03999

Attention R2U-Net : Just integration of two recent advanced works (R2U-Net + Attention U-Net)

网络结构图

U-Net

R2U-Net

Attention U-Net

Attention R2U-Net

评估

将模型在 ISIC 2018 dataset数据集上进行测试，数据集分为训练集、验证集、测试集，占比分别为70%，10%，20%。

图片数量分别为1815，259，520.

评估指标和结果如下图所示：