Hi @Nic-Ma et al,
In sliding_window_inference, what strategy is followed to find ROI from the input image?
Is ROI is selected from the foreground voxel area only? or Is the ROI selected randomly?
I have trained a model using foreground voxels (CropForeground) only. I want to do inference without cropping/resizing the validation image. How can I achieve it using sliding_window_inference class, doing inference on the foreground voxels without losing dimension/spacing/spatial location of the input image?
Looking forward to hearing from you.
Hi @Nic-Ma et al,
In sliding_window_inference, what strategy is followed to find ROI from the input image?
Is ROI is selected from the foreground voxel area only? or Is the ROI selected randomly?
I have trained a model using foreground voxels (CropForeground) only. I want to do inference without cropping/resizing the validation image. How can I achieve it using sliding_window_inference class, doing inference on the foreground voxels without losing dimension/spacing/spatial location of the input image?
Looking forward to hearing from you.