Open NathanMolinier opened 11 months ago
find ~+ -type f -name *_label*.nii.gz | grep -v MTS | sort > ../../config_data/spinegeneric_vert.txt
By running this into a BIDS compliant repository, we are gathering all the paths to relevant ground truth images that contain _label
in their name.
Note: By directly gathering ground truth instead of images, we are avoiding complication with label suffixes (i.e. for discs labels we have numerous suffixes currently used:
_labels-disc
,_labels-disc-manual
,_labels-manual
)
The created text
file should look like this
/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu01/anat/sub-amu01_T1w_labels-disc-manual.nii.gz
/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu01/anat/sub-amu01_T2w_labels-disc-manual.nii.gz
/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu02/anat/sub-amu02_T1w_labels-disc-manual.nii.gz
/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu02/anat/sub-amu02_T2w_labels-disc-manual.nii.gz
/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu03/anat/sub-amu03_T1w_labels-disc-manual.nii.gz
/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu03/anat/sub-amu03_T2w_labels-disc-manual.nii.gz
/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu04/anat/sub-amu04_T1w_labels-disc-manual.nii.gz
/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu04/anat/sub-amu04_T2w_labels-disc-manual.nii.gz
/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu05/anat/sub-amu05_T1w_labels-disc-manual.nii.gz
/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu05/anat/sub-amu05_T2w_labels-disc-manual.nii.gz
/home/data/datasets/data-multi-subject/derivatives/labels/sub-balgrist01/anat/sub-balgrist01_T1w_labels-disc-manual.nii.gz
/home/data/datasets/data-multi-subject/derivatives/labels/sub-balgrist01/anat/sub-balgrist01_T2w_labels-disc-manual.nii.gz
init_data_config.py
(see https://github.com/spinalcordtoolbox/disc-labeling-hourglass/pull/26)python src/dlh/data_management/init_data_config.py --txt CONFIG_DATA --type LABEL --split-validation SPLIT_VAL --split-test SPLIT_TEST
With
LABEL
to specify that the text file only contains ground truth and not imagesNote: The sum of the percentages should be equal to 1
The created json
file should look like this
{
"TYPE": "LABEL",
"CONTRASTS": "t1_t2",
"TRAINING": [
"/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu01/anat/sub-amu01_T1w_labels-disc-manual.nii.gz",
"/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu01/anat/sub-amu01_T2w_labels-disc-manual.nii.gz",
"/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu02/anat/sub-amu02_T1w_labels-disc-manual.nii.gz",
"/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu02/anat/sub-amu02_T2w_labels-disc-manual.nii.gz",
"/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu03/anat/sub-amu03_T1w_labels-disc-manual.nii.gz",
"/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu03/anat/sub-amu03_T2w_labels-disc-manual.nii.gz",
"/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu04/anat/sub-amu04_T1w_labels-disc-manual.nii.gz"
],
"VALIDATION": [
"/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu04/anat/sub-amu04_T2w_labels-disc-manual.nii.gz",
"/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu05/anat/sub-amu05_T1w_labels-disc-manual.nii.gz",
],
"TESTING": [
"/home/data/datasets/data-multi-subject/derivatives/labels/sub-amu05/anat/sub-amu05_T2w_labels-disc-manual.nii.gz",
"/home/data/datasets/data-multi-subject/derivatives/labels/sub-balgrist01/anat/sub-balgrist01_T1w_labels-disc-manual.nii.gz",
"/home/data/datasets/data-multi-subject/derivatives/labels/sub-balgrist01/anat/sub-balgrist01_T2w_labels-disc-manual.nii.gz"
]
}
Description
Instead of having a step to gather the data for training, we should use as input a
json
file with all the paths to all the images. Using such method will be beneficial :acq_sag