-
Notifications
You must be signed in to change notification settings - Fork 0
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
dcm-zurich
BIDSification
#217
Conversation
Note: this works only this SCT branch: spinalcordtoolbox/spinalcordtoolbox#4052
…et to the output dataset
…ded, just copy the file
It is added just to allow easy GitHub review.
@jcohenadad Could you please review if README.md is fine? |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Awesome! thanks
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Everything looks good!
Thank you for your feedback! |
Overview
This PR discusses the BIDSification of
dcm-zurich
dataset.Sample of the input dataset (located on joplin in
~/duke/projects/dcm-normalization/data_zurich_2023-02-22/Nifti_proCSM/Nifti_proCSM
):Sample of the output BIDS dataset (located on joplin in
~/extrassd1/janvalosek/dcm-zurich
):README.md is provided within this PR to allow easy review.
Stitching
Most subjects (n=121) have two T2tra images. One covers the upper cervical SC (top FOV), second covers the lower cervical SC (bottom FOV). I stitched these two images using
sct_match -stitch
:data-management/scripts/curate_dcm-zurich.py
Lines 278 to 279 in 0c01dac
I also stored the original non-stitched images under
sourcedata
folder (point 2 of "storage of derived datasets").I checked the QC (
~/extrassd1/janvalosek/dcm-zurich/qc
) for 121 subjects where the stitching was applied, and it looks fine.Checks
bids-validator
is reasonably happy. The upload of the dataset to git-annex will be discussed in a separate issue, as usual.Below are some checks that the number of subjects between the input and output datasets is the same.
The number of subjects in the input dataset:
The number of subjects in the output dataset:
The number of subjects in the output dataset under
sourcedata
(i.e. subjects with two T2w axial images --> stitching was done, and the original non-stitched images are stored undersourcedata
):There are also:
121 + 17 + 2 = 140 (i.e. the number of subjects is the same between the input and the output datasets)