{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T17:30:35Z","timestamp":1786728635235,"version":"build-2736575974"},"reference-count":21,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"2","license":[{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Multiple sclerosis (MS) is one of the most common reasons of neurological disabilities in young adults. The disease occurs when the immune system attacks the central nervous system and destroys the myelin of nervous cells. This results in appearing several lesions in the magnetic resonance (MR) images of patients. Accurate determination of the amount and the place of lesions can help physicians to determine the severity and progress of the disease.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method:<\/jats:title>\n                    <jats:p>Due to the importance of this issue, this challenge has been dedicated to the segmentation and localization of lesions in MR images of patients with MS. The goal was to segment and localize the lesions in the flair MR images of patients as close as possible to the ground truth masks.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Several teams sent us their results for the segmentation and localization of lesions in MR images. Most of the teams preferred to use deep learning methods. The methods varied from a simple U-net structure to more complicated networks.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>The results show that deep learning methods can be useful for segmentation and localization of lesions in MR images. In this study, we briefly described the dataset and the methods of teams attending the competition.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.4103\/jmss.jmss_55_24","type":"journal-article","created":{"date-parts":[[2025,2,27]],"date-time":"2025-02-27T23:00:07Z","timestamp":1740697207000},"update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":2,"title":["Isfahan Artificial Intelligence Event 2023: Lesion Segmentation and Localization in Magnetic Resonance Images of Patients with Multiple Sclerosis"],"prefix":"10.4103","volume":"15","author":[{"given":"Fariba","family":"Davanian","sequence":"first","affiliation":[{"name":"Medical Image and Signal Processing Research Center, Department of Bioimaging, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran"},{"name":"Department of Neurology, Neuroscience Research Center, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran"},{"name":"Paramedical School, Isfahan University of Medical Sciences, Isfahan, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Iman","family":"Adibi","sequence":"additional","affiliation":[{"name":"Department of Neurology, Neuroscience Research Center, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahnoosh","family":"Tajmirriahi","sequence":"additional","affiliation":[{"name":"Medical Image and Signal Processing Research Center, Department of Bioelectrics and Biomedical Engineering, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maryam","family":"Monemian","sequence":"additional","affiliation":[{"name":"Medical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zahra","family":"Zojaji","sequence":"additional","affiliation":[{"name":"Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmadreza","family":"Montazerolghaem","sequence":"additional","affiliation":[{"name":"Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad Amin","family":"Asadinia","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, University of Isfahan, Isfahan, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seyed Mojtaba","family":"Mirghaderi","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seyed Amin Naji","family":"Esfahani","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, K. 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