Citing SCT

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.

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