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To measure tongue atrophy, an operator independent automatic segmentation of the tongue is crucial. The aim of this study was to apply convolutional neural network (CNN) to MRI data in order to determine the volume of the tongue.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>A single triplanar CNN of U-Net architecture trained on axial, coronal, and sagittal planes was used for the segmentation of the tongue in MRI scans of the head. The 3D volumes were processed slice-wise across the three orientations and the predictions were merged using different voting strategies. This approach was developed using MRI datasets from 20 patients with \u2018classical\u2019 spinal amyotrophic lateral sclerosis (ALS) and 20 healthy controls and, in a pilot study, applied to the tongue volume quantification to 19 controls and 19 ALS patients with the variant progressive bulbar palsy (PBP).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Consensus models with softmax averaging and majority voting achieved highest segmentation accuracy and outperformed predictions on single orientations and consensus models with union and unanimous voting. At the group level, reduction in tongue volume was not observed in classical spinal ALS, but was significant in the PBP group, as compared to controls.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>Utilizing single U-Net trained on three orthogonal orientations with consequent merging of respective orientations in an optimized consensus model reduces the number of erroneous detections and improves the segmentation of the tongue. The CNN-based automatic segmentation allows for accurate quantification of the tongue volumes in all subjects. The application to the ALS variant PBP showed significant reduction of the tongue volume in these patients and opens the way for unbiased future longitudinal studies in diseases affecting tongue volume.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s11548-024-03099-x","type":"journal-article","created":{"date-parts":[[2024,3,27]],"date-time":"2024-03-27T07:03:46Z","timestamp":1711523026000},"page":"1579-1587","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["AI-assisted automatic MRI-based tongue volume evaluation in motor neuron disease (MND)"],"prefix":"10.1007","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4187-5685","authenticated-orcid":false,"given":"Ina","family":"Vernikouskaya","sequence":"first","affiliation":[]},{"given":"Hans-Peter","family":"M\u00fcller","sequence":"additional","affiliation":[]},{"given":"Albert C.","family":"Ludolph","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7106-9270","authenticated-orcid":false,"given":"Jan","family":"Kassubek","sequence":"additional","affiliation":[]},{"given":"Volker","family":"Rasche","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,3,27]]},"reference":[{"issue":"10","key":"3099_CR1","doi-asserted-by":"publisher","first-page":"1918","DOI":"10.1111\/ene.14393","volume":"27","author":"P Masrori","year":"2020","unstructured":"Masrori P, Van Damme P (2020) Amyotrophic lateral sclerosis: a clinical review. 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The study including the recording and the analysis of MRI data has been approved by the Ethics Committee of the University of Ulm (references #19\/12 and #20\/12) in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Written informed consent was obtained from all individual participants included in the study. Previous studies on the analyses of MRI data have already been performed [].","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}