The Medical Image Analysis Laboratory Super-Resolution ToolKit (MIALSRTK) consists of a set of C++ and Python processing and workflow tools necessary to perform motion-robust super-resolution fetal MRI reconstruction in the BIDS Apps framework.
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Add option to specify custom trained model for brain extraction #25
[ ] Addition of new arguments --custom_ckpt_brain_localisation and --custom_ckpt_brain_localisation in pymialsrtk/parser.py(where the parser of the BIDS App is defined) to specify custom paths (prefixes) to the files of trained networks. As we are using a container image, these files should be mounted and accessible inside it. I would suggest to use to code/ folder to put these files which is already mounted.
[ ] Modification of docker/bidsapp/run.py and/or pymialsrtk/pipelines/anatomical/srr.py such that in_ckpt_loc for localization and in_ckpt_seg for segmentation are set to the custom paths (prefixes) specified by the new BIDS App arguments.
This new feature can be accomplished by:
[ ] Addition of new arguments
--custom_ckpt_brain_localisation
and--custom_ckpt_brain_localisation
inpymialsrtk/parser.py
(where the parser of the BIDS App is defined) to specify custom paths (prefixes) to the files of trained networks. As we are using a container image, these files should be mounted and accessible inside it. I would suggest to use to code/ folder to put these files which is already mounted.[ ] Modification of
docker/bidsapp/run.py
and/orpymialsrtk/pipelines/anatomical/srr.py
such thatin_ckpt_loc
for localization andin_ckpt_seg
for segmentation are set to the custom paths (prefixes) specified by the new BIDS App arguments.