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Detail publikačního výsledku
KREJČÍ, K.; CHMELÍK, J.; BÉDARD, S.; EIPPERT, F.; HORN, U.; COHEN-ADAD, J., VALOŠEK, J.
Originální název
Automatic multi-contrast spinal nerve rootlets segmentation to study spinal-vertebral level correspondence
Anglický název
Druh
Abstrakt
Originální abstrakt
MRI images allow identification of spinal nerve rootlets and intervertebral discs (IVDs), which can be used to determine spinal and vertebral levels, respectively [1, 2]. Spinal rootlets are relevant for functional MRI group analyses [3, 4] and neuromodulation therapy [5]; however, their applicability is impacted by considerable variability in spinal and vertebral levels across individuals [2, 6]. A method for automatic rootlet segmentation was proposed [1], but it is limited to a single contrast and dorsal rootlets only. In this work, we developed a model to segment dorsal and ventral C2–T1 rootlets from MP2RAGE and T2w MRI data. Then the model was used to explore the correspondence between spinal and vertebral levels.
Anglický abstrakt
Klíčová slova
Spinal nerve rootlets, Spinal Cord, Segmentation, Deep learning
Klíčová slova v angličtině
Autoři
Vydáno
29.09.2025
Nakladatel
Magn Reson Mater Phy
Kniha
Book of Abstracts ESMRMB 2025 Online 41st Annual Scientific Meeting 8–11 October 2025.
Strany od
455
Strany do
457
Strany počet
3
BibTex
@misc{BUT199809, author="Kateřina {Krejčí} and Jiří {Chmelík} and {} and {} and {} and {} and {}", title="Automatic multi-contrast spinal nerve rootlets segmentation to study spinal-vertebral level correspondence", booktitle="Book of Abstracts ESMRMB 2025 Online 41st Annual Scientific Meeting 8–11 October 2025.", year="2025", pages="3", publisher="Magn Reson Mater Phy", doi="10.1007/s10334-025-01278-8", note="Abstract" }