quickNAT_pytorch
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ai-med
PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty
Hi, Could you please provide information about the datasets used to train the models provided under https://github.com/ai-med/quickNAT_pytorch/tree/master/saved_models?
Hello, The readme states: > Before deploying our model you need to standardize the MRI scans. Use the following command from FreeSurfer mri_convert --conform The above command standardizes the alignment...
Hi, What is the folder structure of the data? I need to know this to incorporate my own data. Thanks.
Hi, I try to use QuickNAT to train my data but feel a bit confused about the usage and some arguments. Should we convert our data to h5 files first?...
It would be great if the trained weights could be removed from the repo and downloaded separately from a server. Cloning takes about 5 minutes for me.
When i set device to "cpu" in settings_eval.ini, just to test cpu performance, i get: > Traceback (most recent call last): > File "run.py", line 187, in > evaluate_bulk(settings_eval['EVAL_BULK']) >...
