Spinal nerve rootlets segmentation¶
SCT provides a deep learning model for the segmentation of spinal nerve rootlets from T2-weighted and MP2RAGE images.
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 and was available via via sct_deepseg -task seg_spinal_rootlets_t2w
.
This model was trained on 3D T2-weighted and MP2RAGE images (UNIT1, INV1, INV2) 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 -qc ~/qc_singleSubj
- Input arguments:
rootlets
: Task to perform. In our case, we use therootlets
task.-i
: Input T2w image-qc
: Directory for Quality Control reporting. QC reports allow us to evaluate the segmentation slice-by-slice
- Output files/folders:
t2_seg.nii.gz
: 3D level-specific segmentation (i.e., 2: C2 rootlet, 3: C3 rootlet, etc.) of the dorsal and ventral spinal nerve rootletst2_seg.json
: JSON file containing details about the segmentation model
Details: