From: 2.5D MFFAU-Net: a convolutional neural network for kidney segmentation
Authors | methods | Kidney Dice | Tumor Dice |
---|---|---|---|
This paper | 2.5D MFFAU-Net | 0.975 | 0.872 |
Fabian et al. [20]. | 3D U-Net | 0.974 | 0.851 |
Kang et al. [21]. | 3D-CNN + ConvLSTM | 0.964 | 0.789 |
da Cruz et al. [22]. | AlexNet + 2D U-Net | 0.930 | \ |
Pandey et al. [23]. | active contour + deep learning | 0.976 | \ |
da Cruz et al. [28]. | 2.5D DeepLabv3+ | \ | 0.852 |
Causey et al. [29]. | Ensemble of U-Net | 0.949 | 0.601 |
Kittipongdaja et al. [30]. | 2.5D DenseU-Net | 0.960 | \ |
Türk et al. [31]. | Hybrid V-Net | 0.977 | 0.865 |
Türk et al. [32]. | Two-Stage Bottleneck Block | \ | 0.869 |