{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T17:49:41Z","timestamp":1790704181481,"version":"4.1.0"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T00:00:00Z","timestamp":1776124800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T00:00:00Z","timestamp":1781049600000},"content-version":"vor","delay-in-days":57,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Data"],"DOI":"10.1038\/s41597-026-07184-5","type":"journal-article","created":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T05:56:56Z","timestamp":1776146216000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Multiple Sclerosis MRI Dataset with Tri-Mask Annotations for Lesion Segmentation"],"prefix":"10.1038","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-2029-3245","authenticated-orcid":false,"given":"Mahdi Bashiri","family":"Bawil","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4670-0531","authenticated-orcid":false,"given":"Mousa","family":"Shamsi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7150-114X","authenticated-orcid":false,"given":"Aydin","family":"Ghalehasadi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9435-8158","authenticated-orcid":false,"given":"Ali Fahmi","family":"Jafargholkhanloo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9397-0484","authenticated-orcid":false,"given":"Abolhassan Shakeri","family":"Bavil","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,4,14]]},"reference":[{"key":"7184_CR1","doi-asserted-by":"publisher","unstructured":"Filippi, M. et al. Multiple sclerosis. Nature Reviews Disease Primers 4(1), https:\/\/doi.org\/10.1038\/s41572-018-0041-4 (2018).","DOI":"10.1038\/s41572-018-0041-4"},{"issue":"no. 2","key":"7184_CR2","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1016\/s1474-4422(17)30470-2","volume":"17","author":"AJ Thompson","year":"2018","unstructured":"Thompson, A. J. et al. Diagnosis of Multiple sclerosis: 2017 Revisions of the McDonald Criteria. The Lancet Neurology 17(2), 162\u2013173, https:\/\/doi.org\/10.1016\/s1474-4422(17)30470-2 (2018).","journal-title":"The Lancet Neurology"},{"key":"7184_CR3","doi-asserted-by":"publisher","first-page":"105435","DOI":"10.1016\/j.msard.2024.105435","volume":"83","author":"B Yamout","year":"2024","unstructured":"Yamout, B. et al. Consensus recommendations for diagnosis and treatment of Multiple Sclerosis: 2023 revision of the MENACTRIMS guidelines. Multiple Sclerosis and Related Disorders 83, 105435\u2013105435, https:\/\/doi.org\/10.1016\/j.msard.2024.105435 (2024).","journal-title":"Multiple Sclerosis and Related Disorders"},{"issue":"no. 3","key":"7184_CR4","doi-asserted-by":"publisher","first-page":"255","DOI":"10.55697\/tnd.2025.500","volume":"31","author":"HC Manazo\u011flu","year":"2025","unstructured":"Manazo\u011flu, H. C. & K\u00fcrt\u00fcnc\u00fc, M. Redefining multiple sclerosis: 2024 McDonald diagnostic criteria. Turkish Journal Of Neurology 31(3), 255\u2013269, https:\/\/doi.org\/10.55697\/tnd.2025.500 (2025).","journal-title":"Turkish Journal Of Neurology"},{"key":"7184_CR5","doi-asserted-by":"publisher","DOI":"10.1038\/s41582-025-01140-4","author":"AJ Solomon","year":"2025","unstructured":"Solomon, A. J. & Brodersen, J. B. The 2024 revisions of the McDonald criteria pose risk of multiple sclerosis overdiagnosis. Nature Reviews Neurology https:\/\/doi.org\/10.1038\/s41582-025-01140-4 (2025).","journal-title":"Nature Reviews Neurology"},{"issue":"no. 1","key":"7184_CR6","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1016\/s1474-4422(22)00289-7","volume":"22","author":"T Kuhlmann","year":"2023","unstructured":"Kuhlmann, T. et al. Multiple sclerosis progression: time for a new mechanism-driven framework. The Lancet Neurology 22(1), 78\u201388, https:\/\/doi.org\/10.1016\/s1474-4422(22)00289-7 (2023).","journal-title":"The Lancet Neurology"},{"issue":"no. 12","key":"7184_CR7","doi-asserted-by":"publisher","first-page":"882","DOI":"10.1007\/s002340050860","volume":"41","author":"PD Molyneux","year":"1999","unstructured":"Molyneux, P. D. et al. Visual analysis of serial T2-weighted MRI in multiple sclerosis: intra- and interobserver reproducibility. Neuroradiology 41(12), 882\u2013888, https:\/\/doi.org\/10.1007\/s002340050860 (1999).","journal-title":"Neuroradiology"},{"key":"7184_CR8","doi-asserted-by":"publisher","first-page":"104697","DOI":"10.1016\/j.compbiomed.2021.104697","volume":"136","author":"A Shoeibi","year":"2021","unstructured":"Shoeibi, A. et al. Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review. Computers in Biology and Medicine 136, 104697, https:\/\/doi.org\/10.1016\/j.compbiomed.2021.104697 (2021).","journal-title":"Computers in Biology and Medicine"},{"issue":"no. 7","key":"7184_CR9","doi-asserted-by":"publisher","first-page":"1858","DOI":"10.1093\/brain\/awz144","volume":"142","author":"M Filippi","year":"2019","unstructured":"Filippi, M. et al. Assessment of lesions on magnetic resonance imaging in multiple sclerosis: practical guidelines. Brain 142(7), 1858\u20131875, https:\/\/doi.org\/10.1093\/brain\/awz144 (2019).","journal-title":"Brain"},{"issue":"no. 100978","key":"7184_CR10","doi-asserted-by":"publisher","first-page":"100978","DOI":"10.1016\/j.lanepe.2024.100978","volume":"44","author":"MA Rocca","year":"2024","unstructured":"Rocca, M. A. et al. Current and future role of MRI in the diagnosis and prognosis of multiple sclerosis. The Lancet Regional Health - Europe 44(100978), 100978\u2013100978, https:\/\/doi.org\/10.1016\/j.lanepe.2024.100978 (2024).","journal-title":"The Lancet Regional Health - Europe"},{"key":"7184_CR11","doi-asserted-by":"publisher","first-page":"1058","DOI":"10.1212\/01.con.0000433283.00221.37","volume":"19","author":"EC Klawiter","year":"2013","unstructured":"Klawiter, E. C. Current and New Directions in MRI in Multiple Sclerosis. CONTINUUM: Lifelong Learning in Neurology 19, 1058\u20131073, https:\/\/doi.org\/10.1212\/01.con.0000433283.00221.37 (2013).","journal-title":"CONTINUUM: Lifelong Learning in Neurology"},{"key":"7184_CR12","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1016\/j.neuroimage.2016.12.064","volume":"148","author":"A Carass","year":"2017","unstructured":"Carass, A. et al. Longitudinal multiple sclerosis lesion segmentation: Resource and challenge. NeuroImage 148, 77\u2013102, https:\/\/doi.org\/10.1016\/j.neuroimage.2016.12.064 (2017).","journal-title":"NeuroImage"},{"key":"7184_CR13","doi-asserted-by":"publisher","first-page":"118589","DOI":"10.1016\/j.neuroimage.2021.118589","volume":"244","author":"O Commowick","year":"2021","unstructured":"Commowick, O. et al. Multiple sclerosis lesions segmentation from multiple experts: The MICCAI 2016 challenge dataset. NeuroImage 244, 118589, https:\/\/doi.org\/10.1016\/j.neuroimage.2021.118589 (2021).","journal-title":"NeuroImage"},{"issue":"no. 8","key":"7184_CR14","doi-asserted-by":"publisher","first-page":"822","DOI":"10.1016\/s1474-4422(13)70124-8","volume":"12","author":"JM Wardlaw","year":"2013","unstructured":"Wardlaw, J. M. et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. The Lancet Neurology 12(8), 822\u2013838, https:\/\/doi.org\/10.1016\/s1474-4422(13)70124-8 (2013).","journal-title":"The Lancet Neurology"},{"issue":"no. jul26 1","key":"7184_CR15","doi-asserted-by":"publisher","first-page":"c3666","DOI":"10.1136\/bmj.c3666","volume":"341","author":"S Debette","year":"2010","unstructured":"Debette, S. & Markus, H. S. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ 341(jul26 1), c3666\u2013c3666, https:\/\/doi.org\/10.1136\/bmj.c3666 (2010).","journal-title":"BMJ"},{"key":"7184_CR16","doi-asserted-by":"publisher","unstructured":"Wardlaw, J. M., Vald\u00e9s Hern\u00e1ndez, M. C. & Mu\u00f1oz-Maniega, S. What are White Matter Hyperintensities Made of?, Journal of the American Heart Association 4(6), https:\/\/doi.org\/10.1161\/jaha.114.001140 (2015).","DOI":"10.1161\/jaha.114.001140"},{"key":"7184_CR17","doi-asserted-by":"publisher","unstructured":"Elliott, C. et al. Abnormalities in normal-appearing white matter from which multiple sclerosis lesions arise. Brain Communications 3(3), https:\/\/doi.org\/10.1093\/braincomms\/fcab176 (2021).","DOI":"10.1093\/braincomms\/fcab176"},{"key":"7184_CR18","doi-asserted-by":"publisher","unstructured":"Rafsanjany, K., Parnianpour, P., Wilman, A. H., Kalra, S. & Yang, Y.-H. Effects of MRI scanner manufacturers in classification tasks with deep learning models. Scientific Reports 13(1), https:\/\/doi.org\/10.1038\/s41598-023-43715-5 (2023).","DOI":"10.1038\/s41598-023-43715-5"},{"key":"7184_CR19","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume":"9351","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P. & Brox, T. U-Net: Convolutional Networks for Biomedical Image Segmentation. Lecture Notes in Computer Science 9351, 234\u2013241, https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28 (2015).","journal-title":"Lecture Notes in Computer Science"},{"key":"7184_CR20","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-030-00889-5_1","volume":"11045","author":"Z Zhou","year":"2018","unstructured":"Zhou, Z., Rahman Siddiquee, M. M., Tajbakhsh, N. & Liang, J. UNet++: A Nested U-Net Architecture for Medical Image Segmentation. Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support 11045, 3\u201311, https:\/\/doi.org\/10.1007\/978-3-030-00889-5_1 (2018).","journal-title":"Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support"},{"key":"7184_CR21","doi-asserted-by":"crossref","unstructured":"Hatamizadeh, A. et al. UNETR: Transformers for 3D Medical Image Segmentation, IEEE Xplore. https:\/\/ieeexplore.ieee.org\/document\/9706678 (2022).","DOI":"10.1109\/WACV51458.2022.00181"},{"key":"7184_CR22","doi-asserted-by":"publisher","unstructured":"Hatamizadeh, A. et al. Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images, Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries pp. 272\u2013284, https:\/\/doi.org\/10.1007\/978-3-031-08999-2_22 (2022).","DOI":"10.1007\/978-3-031-08999-2_22"},{"issue":"no. 1","key":"7184_CR23","doi-asserted-by":"publisher","first-page":"205521731984188","DOI":"10.1177\/2055217319841881","volume":"6","author":"BI Yamout","year":"2020","unstructured":"Yamout, B. I., Assaad, W., Tamim, H., Mrabet, S. & Goueider, R. Epidemiology and phenotypes of multiple sclerosis in the Middle East North Africa (MENA) region. Multiple Sclerosis Journal - Experimental, Translational and Clinical 6(1), 205521731984188, https:\/\/doi.org\/10.1177\/2055217319841881 (2020).","journal-title":"Multiple Sclerosis Journal - Experimental, Translational and Clinical"},{"key":"7184_CR24","doi-asserted-by":"publisher","first-page":"108139","DOI":"10.1016\/j.dib.2022.108139","volume":"42","author":"AM Muslim","year":"2022","unstructured":"Muslim, A. M. et al. Brain MRI dataset of multiple sclerosis with consensus manual lesion segmentation and patient meta information. Data in Brief 42, 108139, https:\/\/doi.org\/10.1016\/j.dib.2022.108139 (2022).","journal-title":"Data in Brief"},{"key":"7184_CR25","doi-asserted-by":"publisher","unstructured":"Guarnera, F. et al. MSLesSeg: baseline and benchmarking of a new Multiple Sclerosis Lesion Segmentation dataset. Scientific Data 12(1), https:\/\/doi.org\/10.1038\/s41597-025-05250-y (2025).","DOI":"10.1038\/s41597-025-05250-y"},{"issue":"no. 4","key":"7184_CR26","doi-asserted-by":"publisher","first-page":"232","DOI":"10.1159\/000431042","volume":"44","author":"P Heydarpour","year":"2015","unstructured":"Heydarpour, P., Khoshkish, S., Abtahi, S., Moradi-Lakeh, M. & Sahraian, M. A. Multiple Sclerosis Epidemiology in Middle East and North Africa: A Systematic Review and Meta-Analysis. Neuroepidemiology 44(4), 232\u2013244, https:\/\/doi.org\/10.1159\/000431042 (2015).","journal-title":"Neuroepidemiology"},{"issue":"no. 14","key":"7184_CR27","doi-asserted-by":"publisher","first-page":"1816","DOI":"10.1177\/1352458520970841","volume":"26","author":"C Walton","year":"2020","unstructured":"Walton, C. et al. Rising Prevalence of Multiple Sclerosis worldwide: Insights from the Atlas of MS, Third Edition. Multiple Sclerosis Journal 26(14), 1816\u20131821, https:\/\/doi.org\/10.1177\/1352458520970841 (2020).","journal-title":"Multiple Sclerosis Journal"},{"issue":"no. 2","key":"7184_CR28","doi-asserted-by":"publisher","first-page":"825","DOI":"10.1016\/s1053-8119(02)91132-8","volume":"17","author":"M Jenkinson","year":"2002","unstructured":"Jenkinson, M., Bannister, P., Brady, M. & Smith, S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage 17(2), 825\u2013841, https:\/\/doi.org\/10.1016\/s1053-8119(02)91132-8 (2002).","journal-title":"NeuroImage"},{"issue":"no. 3","key":"7184_CR29","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1002\/hbm.10062","volume":"17","author":"SM Smith","year":"2002","unstructured":"Smith, S. M. Fast robust automated brain extraction. Human Brain Mapping 17(3), 143\u2013155, https:\/\/doi.org\/10.1002\/hbm.10062 (2002).","journal-title":"Human Brain Mapping"},{"key":"7184_CR30","doi-asserted-by":"publisher","DOI":"10.6084\/m9.figshare.30393475","author":"MB Bawil","year":"2026","unstructured":"Bawil, M. B., Shamsi, M., Ghalehasadi, A., Jafargholkhanloo, A. F. & Bavil, A. S. A Multiple Sclerosis MRI Dataset with Tri-Mask Annotations for Lesion Segmentation. figshare. https:\/\/doi.org\/10.6084\/m9.figshare.30393475 (2026).","journal-title":"figshare."}],"container-title":["Scientific Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41597-026-07184-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41597-026-07184-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41597-026-07184-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T23:25:20Z","timestamp":1781047520000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41597-026-07184-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,14]]},"references-count":30,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["7184"],"URL":"https:\/\/doi.org\/10.1038\/s41597-026-07184-5","relation":{},"ISSN":["2052-4463"],"issn-type":[{"value":"2052-4463","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,14]]},"assertion":[{"value":"11 October 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 March 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"867"}}