This repository contains scripts for the manual correction of spinal cord labels.
Currently supported labels are:
- spinal cord segmentation
- gray matter segmentation
- lesion segmentation (e.g., MS or SCI lesions)
- disc labels
- compression labels
- ponto-medullary junction (PMJ) label
- rootlets segmentation
- centerline
Note
We greatly appreciate feedback and suggestions for improvement. Feel free to open an issue and report bugs, suggest new features or ask questions.
- Spinal Cord Toolbox (SCT)
- FSLeyes or ITK-SNAP
- Python 3.8
Download the repository:
git clone https://github.com/spinalcordtoolbox/manual-correction.git
cd manual-correction
Create a virtual environment and install the required packages:
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
Alternatively, you can use existing SCT's conda environment:
source ${SCT_DIR}/python/etc/profile.d/conda.sh
conda activate venv_sct
Important
All scripts currently assume BIDS-compliant data. For more information about the BIDS standard, please visit http://bids.neuroimaging.io.
This script loops across subjects listed in the YAML file and opens a viewer to correct the labels (segmentations, disc labels, etc.).
python manual_correction.py -path-img <INPUT_PATH> -config <CONFIG_FILE>
INPUT_PATH
: Path to the BIDS-compliant folder with data to be corrected.CONFIG_FILE
: YAML file that lists images to be corrected. This YAML file can be generated by SCT's QC HTML report or created manually.
For full help, please run: python manual_correction.py -h
.
If the manual correction is done by someone else than the person doing the processing, this script packages the processed images and existing labels (segmentation, disc labels, etc.) and creates a single ZIP file that can conveniently be sent to collaborators.
python package_for_correction.py -path-in <INPUT_PATH> -config <CONFIG_FILE>
INPUT_PATH
: Path to the BIDS-compliant folder with data to be packaged.CONFIG_FILE
: YAML file that lists images to be packaged. This YAML file can be generated by SCT's QC HTML report or created manually.
For full help, please run: python package_for_correction.py -h
.
This script copies manually corrected labels (segmentations, disc labels, etc.) from your local derivatives/labels
folder to the already existing dataset's derivatives/labels
folder.
python copy_files_to_derivatives.py -path-in <INPUT_PATH> -path-out <OUTPUT_PATH>
INPUT_PATH
: Path to the BIDS-compliant folder with manually corrected labels.OUTPUT_PATH
: Path to the BIDS-compliant folder where manually corrected files will be copied.
For full help, please run: python copy_files_to_derivatives.py -h
.
See wiki