Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
565-05-006 ISMRM Abstract

Improving automatic segmentation of 7T MRI ex-vivo human traumatic spinal cord injury: A deep learning approach

Primary: Neuro - Spinal Cord
Secondary: Analysis Methods - Segmentation and Detection
565-05-006 · Segmentation for Body Applications · Wednesday, 13 May, 4:00 PM–4:55 PM · Digital Posters Row F
Keywords: Machine Learning/Artificial Intelligence Segmentation Spinal Cord Toolbox Spinal cord injury Artificial Intelligence (AI)
Accepted
Kyle Vavasour1, Nikolai I Lesack1,2,3, Sarah R Morris1,2,3, Andrew Yung1,3,4, Kirsten Bale3,4, Andrew Bauman4, Piotr Kozlowski1,2,3,4, Zahra Samadi-Bahrami1,5, Caron Fournier1,5, Pushwant S Mattu6, Kevin Dong1, Femke Streijger1, G. R. Wayne Moore1,5,7, Adam Velenosi1, Veronica Hirsch-Reinshagen1,5,6, Brian K Kwon1,8, Cornelia Laule 1,2,3,5,9
1International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, Canada
2Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
3Department of Radiology, University of British Columbia, Vancouver, Canada
4UBC MRI Research Centre, Vancouver, Canada
5Pathology & Laboratory Medicine, University of British Columbia, Vancouver, Canada
6Vancouver General Hospital, Vancouver, Canada
7Medicine, University of British Columbia, Vancouver, Canada
8Department of Orthopaedics, University of British Columbia, Vancouver, Canada
9University of British Columbia, Vancouver, Canada
Presenting Author: Cornelia Laule

Synopsis

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References

1. [1] Ding W, Hu S, Wang P, et al. “Spinal Cord Injury: The Global Incidence, Prevalence, and Disability From the Global Burden of Disease Study” Spine vol. 47, no. 21, 2022. doi:10.1097/BRS.0000000000004417. [doi]
2. [2] Agha Tabari K, Swami SS, Kasagga A, Assefa AK, Amin MN, Hashish R, Yu AK. The Role of MRI in Evaluating Spinal Cord Injuries: Diagnostic Accuracy, Prognostic Value, and Clinical Decision-Making. Cureus. 2025 Jun 30;17(6):e87040. doi:10.7759/cureus.87040. [doi]
3. [3] Talbott JF, Ramachandran A, Gandhi S, Isikbay M, DiGiorgio A. MR Imaging in Cervical Spine Trauma: What You Need to Know in 2025! Magn Reson Imaging Clin N Am. 2025 May;33(2):233-245. doi:10.1016/j.mric.2025.01.009. [doi]
4. [4] De Leener B, Lévy S, Dupont SM, Fonov VS, Stikov N, Louis Collins D, Callot V, Cohen-Adad J. SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data. Neuroimage. 2017 Jan 15;145(Pt A):24-43. doi:10.1016/j.neuroimage.2016.10.009. [doi]
5. [5] Perone CS, Calabrese E, Cohen-Adad J. Spinal cord gray matter segmentation using deep dilated convolutions. Sci Rep. 2018 Apr 13;8(1):5966. doi:10.1038/s41598-018-24304-3. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/565-05-006