Spinal nerve rootlets segmentation

SCT provides a deep learning model for the segmentation of spinal nerve rootlets from T2-weighted and MP2RAGE contrasts (T1w-INV1, T1w-INV2, and UNIT1). The model is available in SCT v7.0 and higher via sct_deepseg rootlets. In the previous SCT versions (SCT v6.2 and higher), the model segmented only T2-weighted images and was available via via sct_deepseg -task seg_spinal_rootlets_t2w.

This model was trained on 3D T2-weighted and MP2RAGE contrasts (T1w-INV1, T1w-INV2, and UNIT1) and provides level-specific semantic segmentation (i.e., 2: C2 rootlet, 3: C3 rootlet, etc.) of the dorsal and ventral spinal nerve rootlets C2-T1.

Run the following command to segment the spinal nerve rootlets from the input image:

sct_deepseg rootlets -i t2.nii.gz -o t2_rootlets.nii.gz -qc ~/qc_singleSubj
Input arguments:

  • rootlets : Task to perform. In our case, we use the rootlets task.

  • -i : Input T2w image

  • -o : Output file name for the rootlets segmentation

  • -qc : Directory for Quality Control reporting. QC reports allow us to evaluate the segmentation slice-by-slice

Output files/folders:

  • t2_rootlets.nii.gz : 3D level-specific segmentation (i.e., 2: C2 rootlet, 3: C3 rootlet, etc.) of the dorsal and ventral spinal nerve rootlets

  • t2_rootlets.json : JSON file containing details about the segmentation model

Details: