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ai-med / quickNAT_pytorch

PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty

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Question about `mri_convert`

sravan953 opened this issue · comments

commented

Hello,

The readme states:

Before deploying our model you need to standardize the MRI scans. Use the following command from FreeSurfer
mri_convert --conform <input_volume.nii> <out_volume.nii>
The above command standardizes the alignment for QuickNAT, re-samples to isotrophic resolution (256x256x256) with some contrast enhamcement. It takes about one second per volume.

Assuming FreeSurfer is not available, could you please elaborate on the pre-processing steps?

  1. What exactly does it mean to standardize alignment?
  2. Is the contrast enhancement necessary?
commented

Obviously, QuickNAT is implemented with Freesurfer. so I think you must use Freesurfer's mri_convert function.

commented

Furthermore, This paper is NOT focused on MRI image's preprocessing.