References

If you use SCT in your research or as part of your developments, please always cite the main reference. If you use specific tools such as sct_deepseg_sc or the PAM50 template, please also cite the specific articles listed in specific references. You could also see some of the applications of SCT by other groups in applications.

Main reference

@article{DeLeener201724,
title = "SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord \{MRI\} data ",
journal = "NeuroImage ",
volume = "145, Part A",
number = "",
pages = "24 - 43",
year = "2017",
note = "",
issn = "1053-8119",
doi = "https://doi.org/10.1016/j.neuroimage.2016.10.009",
url = "http://www.sciencedirect.com/science/article/pii/S1053811916305560",
author = "Benjamin De Leener and Simon Lévy and Sara M. Dupont and Vladimir S. Fonov and Nikola Stikov and D. Louis Collins and Virginie Callot and Julien Cohen-Adad",
keywords = "Spinal cord",
keywords = "MRI",
keywords = "Software",
keywords = "Template",
keywords = "Atlas",
keywords = "Open-source ",
}

Specific references

Command line tools

The table below provides individual references for novel methods used in SCT’s Command-Line Tools.

Note

If you are using white matter/grey matter segmentation tools (sct_deepseg_gm/sct_deepseg) and registration tools (sct_register_to_template/sct_register_multimodal) together as part of a pipeline, please also consider this reference:

Dupont SM, De Leener B, Taso M, Le Troter A, Stikov N, Callot V, Cohen-Adad J. Fully-integrated framework for the segmentation and registration of the spinal cord white and gray matter. Neuroimage 2017

Command line script

References

sct_deepseg_gm

Perone et al. Spinal cord gray matter segmentation using deep dilated convolutions. Sci Rep 2018

sct_deepseg_lesion

Gros et al. Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks. Neuroimage 2019

sct_deepseg_sc

Gros et al. Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks. Neuroimage 2019

sct_get_centerline

Gros et al. Automatic spinal cord localization, robust to MRI contrasts using global curve optimization. Med Image Anal 2018

sct_label_vertebrae

Ullmann et al. Automatic labeling of vertebral levels using a robust template-based approach. Int J Biomed Imaging 2014

sct_propseg

De Leener et al. Robust, accurate and fast automatic segmentation of the spinal cord. Neuroimage 2014

sct_propseg -CSF

De Leener et al. Automatic segmentation of the spinal cord and spinal canal coupled with vertebral labeling. IEEE Transactions on Medical Imaging 2015

sct_register_multimodal

De Leener B, Fonov VS, Louis Collins D, Callot V, Stikov N, Cohen-Adad J. PAM50: Unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space. Neuroimage 2017.

sct_register_multimodal --param algo=slicereg

Cohen-Adad et al. Slice-by-slice regularized registration for spinal cord MRI: SliceReg. Proc ISMRM 2015

sct_register_to_template

De Leener B, Fonov VS, Louis Collins D, Callot V, Stikov N, Cohen-Adad J. PAM50: Unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space. Neuroimage 2017.

sct_register_to_template --param algo=slicereg

Cohen-Adad et al. Slice-by-slice regularized registration for spinal cord MRI: SliceReg. Proc ISMRM 2015

sct_straighten_spinalcord

De Leener B et al. Topologically-preserving straightening of spinal cord MRI. J Magn Reson Imaging 2017

Applications

The following studies (in chronological order) have used SCT: