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Automatic labeling of vertebral levels using a robust template-based approach

E. Ullmann, J. F. Pelletier Paquette, William Thong, Julien Cohen-Adad

Article (2014)

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Context. MRI of the spinal cord provides a variety of biomarkers sensitive to white matter integrity and neuronal function. Current processing methods are based on manual labeling of vertebral levels, which is time consuming and prone to user bias. Although several methods for automatic labeling have been published; they are not robust towards image contrast or towards susceptibility-related artifacts. Methods. Intervertebral disks are detected from the 3D analysis of the intensity profile along the spine. The robustness of the disk detection is improved by using a template of vertebral distance, which was generated from a training dataset. The developed method has been validated using T1- and T2-weighted contrasts in ten healthy subjects and one patient with spinal cord injury. Results. Accuracy of vertebral labeling was 100%. Mean absolute error was 2.1 +/- 1.7 mm for T2-weighted images and 2.3 +/- 1.6 mm for T1-weighted images. The vertebrae of the spinal cord injured patient were correctly labeled, despite the presence of artifacts caused by metallic implants. Discussion. We proposed a template-based method for robust labeling of vertebral levels along the whole spinal cord for T1- and T2-weighted contrasts. The method is freely available as part of the spinal cord toolbox.
Subjects: 2500 Electrical and electronic engineering > 2500 Electrical and electronic engineering
2500 Electrical and electronic engineering > 2518 Instrumentation and measurements
2800 Artificial intelligence > 2800 Artificial intelligence (Computer vision, see 2603)
Department: Department of Electrical Engineering
Funders: SMRRT (Canadian Institute of Health Research), National MS Society, Fonds de Recherche du Québec - Santé (FRQS), Quebec Bioimaging Network (QBIN), CRSNG/NSERC
Grant number: FG1892A1/1
PolyPublie URL: https://publications.polymtl.ca/5156/
Journal Title: International Journal of Biomedical Imaging (vol. 2014)
Publisher: Hindawi Publishing Corporation
DOI: 10.1155/2014/719520
Official URL: https://doi.org/10.1155/2014%2f719520
Date Deposited: 08 Apr 2022 11:13
Last Modified: 13 May 2023 05:31
Cite in APA 7: Ullmann, E., Pelletier Paquette, J. F., Thong, W., & Cohen-Adad, J. (2014). Automatic labeling of vertebral levels using a robust template-based approach. International Journal of Biomedical Imaging, 2014, 719520. https://doi.org/10.1155/2014%2f719520


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