Automatic segmentation of the spinal cord nerve rootlets

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15110%2F24%3A73626512" target="_blank" >RIV/61989592:15110/24:73626512 - isvavai.cz</a>
Result on the web
<a href="https://direct.mit.edu/imag/article/doi/10.1162/imag_a_00218/122601/Automatic-segmentation-of-the-spinal-cord-nerve" target="_blank" >https://direct.mit.edu/imag/article/doi/10.1162/imag_a_00218/122601/Automatic-segmentation-of-the-spinal-cord-nerve</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1162/imag_a_00218" target="_blank" >10.1162/imag_a_00218</a>

Result language
angličtina
Original language name
Automatic segmentation of the spinal cord nerve rootlets
Original language description
Precise identification of spinal nerve rootlets is relevant to delineate spinal levels for the study of functional activity in the spinal cord. The goal of this study was to develop an automatic method for the semantic segmentation of spinal nerve rootlets from T2-weighted magnetic resonance imaging (MRI) scans. Images from two open-access 3T MRIdatasets were used to train a 3D multi-class convolutional neural network using an active learning approach to segment C2-C8 dorsal nerve rootlets. Each output class corresponds o a spinal level. The method was tested on 3T T2-weighted images from three datasets unseen during training to assess inter-site, inter-session, and inter-resolutionvariability. The test Dice score was 0.67 ± 0.16 (mean ± standard deviation across testing images and rootlets levels), suggesting a good performance. The method also demonstrated low inter-vendor and inter-site variability (coefficient of variation ≤ 1.41%), as well as low inter-session variability (coefficient of variation ≤ 1.30%), indicating stable predictions across different MRI vendors, sites, and sessions. The proposed methodology is open-source and readily available in the Spinal Cord Toolbox (SCT) v6.2 and higher.
Czech name
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Czech description
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Project
<a href="/en/project/NU22-04-00024" target="_blank" >NU22-04-00024: Quantitative magnetic resonance imaging parameters as predictors of outcome of non-myelopathic degenerative cervical cord compression: a longitudinal study</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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