U-Net model for glomeruli segmentation in H&E stained Whole Slide Images.
Segment glomeruli in a kidney H&E stained WSI using a pre-trained U-Net model.
This generates a glomeruli segmentation mask that is stored in zarr format.
The segmentation mask is stored inside a group called class.
python segment.py -m /path/to/checkpoint -i /path/to/zarr/files -o /ouput/directory
If this is run on a machine with GPUs, the size of the processed chunks can be modified to make the segmentation more efficient. This is limited by the GPU's memory.
python segment.py -m /path/to/checkpoint -i /path/to/zarr/files -o /ouput/directory -cs 2048
By default, only the class (Glomeruli/Background) are stored in the output file.
The option -sp can be used to store the prediction probabilities.
These will be stored in a separate group called probs.
python segment.py -m /path/to/checkpoint -i /path/to/zarr/files -o /ouput/directory -sp