Lesion Segmentation On Anatomical Tracings Of
Metriken
Dice
IoU
Precision
Recall
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | Dice | IoU | Precision | Recall | Paper Title | Repository |
|---|---|---|---|---|---|---|
| SegNet | 0.2767 | 0.1911 | 0.3938 | 0.2532 | SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation | |
| X-Net | 0.4867 | 0.3723 | 0.6000 | 0.4752 | X-Net: Brain Stroke Lesion Segmentation Based on Depthwise Separable Convolution and Long-range Dependencies | |
| MGA-Net | - | 0.3803 | 0.6773 | 0.4525 | Mutual gain adaptive network for segmenting brain stroke lesions | - |
| ResUNet | 0.4702 | 0.3549 | 0.5941 | 0.4537 | Road Extraction by Deep Residual U-Net |
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