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. | ✓ |
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