Biomedical Image Segmentation Models (BISM)
Project description
bism - Biomedical Image Segmentation Models
This is a collection of generic PyTorch model constructors usefull for biomedical segmentation tasks.
Something akin to the timm package for 2D image tasks.
When at all possible, each model will offer a 2D or 3D implementation, however we will not provide pre-trained model files.
Current Models
| Model | 2D | 3D | Scriptable |
|---|---|---|---|
| UNet | ✓ | ✓ | ✓ |
| UNeXT | ✓ | ✓ | ✓ |
| Recurrent UNet | ✓ | ✓ | ✓ |
| Residual UNet | |||
| Unet++ | ✓ | ✓ | ✓ |
| CPnet | ✓ | ✓ | ✓ |
Current Generic Blocks
| BLOCK NAME | 2D | 3D |
|---|---|---|
| UNeXT Block | ✓ | ✓ |
| ConcatConv | ✓ | ✓ |
| Recurrent UNet BLock | ✓ | ✓ |
| Residual UNet BLock | ✓ | ✓ |
| DropPath | ✓ | ✓ |
| LayerNorm | ✓ | ✓ |
| UpSample | ✓ | ✓ |
| ViT Block |
Segmentation Implementation
| APPROACH | 2D | 3D |
|---|---|---|
| Cellpose | ||
| Affinities | ✓ | |
| Local Shape Desc. | ✓ |
Release history Release notifications | RSS feed
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