From: 2.5D MFFAU-Net: a convolutional neural network for kidney segmentation
Authors | methods | Kidney Dice/SD | Mass Dice/SD | Tumor Dice/SD | Cyst Dice/SD |
---|---|---|---|---|---|
This paper | 2.5D MFFAU-Net | 0.973/0.941 | 0.887/0.788 | 0.873/0.769 | 0.765/0.678 |
Shen et al. [24]. | COTRNet | 0.923/0.885 | 0.553/0.369 | 0.506/0.355 | \ |
Adam et al. [25]. | 3D U-ResNet | 0.951/0.904 | 0.798/0.648 | 0.781/0.627 | \ |
Zhao et al. [26]. | nnU-Net | 0.975/0.949 | 0.885/0.787 | 0.869/0.769 | \ |
Zang et al. [33]. | 3D U-Net | 0.970/0.937 | 0.851/0.720 | 0.819/0.700 | \ |
Chen et al. [34]. | ResSENormUnet + DenseTransUnet | 0.943/ \ | \ | 0.778/ \ | 0.710/ \ |
Li et al. [35]. | 3D deep learning | 0.960/ \ | \ | 0.815/ \ | 0.450/ \ |
George [36]. | 3D U-Net | 0.975/0.945 | \ | 0.871/0.761 | 0.881/0.773 |