David G Ellis

Hello @sitandon! >Another question is leveraging other libraries like skimage and torchio. How resize/transform in skimage/ torchio approach is different from scaling affine first and then using resample_img from nilearn...

@sitandon, I like to think of the affine as the window and orientation through which we are looking at the data. When changing the spacing we want the corners of...

Maybe the issue is aligning the corners. The following visualization is helpful for seeing how align_corners works: https://discuss.pytorch.org/t/what-we-should-use-align-corners-false/22663/9

If you haven't already, checkout BraTS example notebook for an explanation of the different arguments: https://github.com/ellisdg/3DUnetCNN/blob/master/examples/brats2020/create_config_lowmem.ipynb Some arguments you may consider changing: - "desired_shape" - "setup_label_hierarchy" should be false since...

Those are 3D renderings that I made as an example of skull completion using the AutoImplant dataset. You should have a training log file that you can look at to...

It sounds like you found a solution. What was the issue? I'm glad to hear this repository has been useful for you. David

> 1. when I change the number of folds to 1 e.g. in the > brats2020.json file the reader goes back to the default of 5 because it claims not...

You can generate predictions using predict.py and then create a notebook or script to load the images with nibabel/numpy and generate metrics against the ground truth. Monai has some metrics...

The filenames in the configuration file are split up into different "groups", typically: "training", "validation", and sometimes "test". If you are using the BRATS 2020 example, I think you should...

What was the training command that you ran?