-
Notifications
You must be signed in to change notification settings - Fork 0
Open
Description
Description
This issue presents the workflow and method to manually correct the whole-spine T2w spinal cord segmentation (cross-ref with problematic GT in the dataset issue)
Running inference
👉 Link to code
1. Install contrast-agnostic M5' model:
sct_deepseg -install seg_sc_contrast_agnostic -custom-url https://github.com/sct-pipeline/contrast-agnostic-softseg-spinalcord/releases/download/v3/model_contrast_agnostic_20250115-2211.zip
2. Launch processing (Example command):
sct_run_batch -path-data ~/datasets/whole-spine/ -path-out ~/process_results/whole-spine-norm/processed_whole-spine-norm_2025-01-21_t1t2_v2.1 -script scripts/process_data_whole-spine.sh -jobs 15
Manual correction
1. Install manual_correction package
Example command:
python manual_correction.py -config /Users/sandrinebedard/processed_data/whole-spine-seg/qc_fail_whole-spine_t2w_Sandrine.yml -path-img /Users/sandrinebedard/processed_data/whole-spine-seg/data2corrrect_Sandrine
What to look for?
1. Top of the cord
Erase or correct (if the slice is above C1 vertebrae, okay to erase):
2. Go through all axial slices and correct obvious over/under segmentation
3. Lumbar enlargement
Correct over segmentation of the rootlets:
4. Conus medullaris
4.1. Find the tip of the conus medullaris on the sagittal and coronal slice
4.2. Validate that it is the mid-sagittal slice on the axial slice
4.3. Erase what is below this point
4.4. Correct for over segmentation of the tip of the conus medullaris to ensure cone shape across slices
Sending the data
You will see under data2correct_<your name>
a derivatives folder with a qc folder, send this to Sandrine
NathanMolinier
Metadata
Metadata
Labels
No labels