{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T16:53:58Z","timestamp":1785430438610,"version":"3.56.0"},"reference-count":31,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T00:00:00Z","timestamp":1781740800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62271149"],"award-info":[{"award-number":["62271149"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"award":["62271149"],"award-info":[{"award-number":["62271149"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Science and Technology Project of Fujian Province","award":["2024J01353"],"award-info":[{"award-number":["2024J01353"]}]},{"name":"Science and Technology Project of Fujian Province","award":["2025Y0008"],"award-info":[{"award-number":["2025Y0008"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background: Myocardial scar segmentation from late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) images plays an important role in cardiac disease assessment and prognosis evaluation. However, accurate scar annotation is labor-intensive and requires substantial clinical expertise because scar regions are typically small, irregularly shaped, and characterized by ambiguous boundaries. Although scribble supervision provides a more practical alternative to dense annotation by substantially reducing labeling costs, the extreme sparsity of scribbles and the high similarity between scar tissue and surrounding myocardium make accurate weakly supervised segmentation challenging. Methods: To address these challenges, we propose SSMSNet, a novel scribble-supervised framework for myocardial scar segmentation. Specifically, a weakly supervised anatomical segmentation network is first employed to provide reliable myocardial structural priors and suppress irrelevant background interference. Subsequently, a local distance prior map is dynamically generated from scribble annotations, and a corresponding loss is introduced to enhance structural awareness and improve training stability. Meanwhile, by leveraging the spatial correlation between the myocardium and scar regions, teacher\u2013student consistency supervision progressively recovers more complete scar structures from sparse annotations. Furthermore, a detail-aware feature enhancement module strengthens low-level representations through contextual interactions and attention mechanisms, improving the perception of scars with ambiguous boundaries. Results: Extensive experiments conducted on two public cardiac pathology datasets demonstrate that the proposed framework consistently outperforms state-of-the-art scribble-supervised methods and achieves competitive performance compared with fully supervised methods. Conclusions: The proposed SSMSNet effectively alleviates the limitations imposed by scribble annotations by integrating anatomical guidance, local distance priors, and consistency learning. These findings suggest that the framework provides an effective and annotation-efficient solution for myocardial scar segmentation in LGE CMR images.<\/jats:p>","DOI":"10.3390\/diagnostics16121895","type":"journal-article","created":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T10:25:34Z","timestamp":1781778334000},"page":"1895","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SSMSNet: Scribble-Supervised Myocardial Scar Segmentation in Late Gadolinium Enhancement Images"],"prefix":"10.3390","volume":"16","author":[{"given":"Xuewen","family":"Liao","sequence":"first","affiliation":[{"name":"Shengli Clinical Medical College of Fujian Medical University, Fuzhou 350013, China"},{"name":"Department of Cardiology, Shengli Clinical Medical College of Fujian Medical University, Fuzhou University Affiliated Provincial Hospital, Fujian Provincial Hospital, No. 134 East Street, Gulou District, Fuzhou 350001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kangwen","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xingtao","family":"Lin","sequence":"additional","affiliation":[{"name":"College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5271-6295","authenticated-orcid":false,"given":"Lin","family":"Pan","sequence":"additional","affiliation":[{"name":"College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yazhou","family":"Lin","sequence":"additional","affiliation":[{"name":"Shengli Clinical Medical College of Fujian Medical University, Fuzhou 350013, China"},{"name":"Department of Cardiology, Shengli Clinical Medical College of Fujian Medical University, Fuzhou University Affiliated Provincial Hospital, Fujian Provincial Hospital, No. 134 East Street, Gulou District, Fuzhou 350001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6068-8287","authenticated-orcid":false,"given":"Mingjing","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8848-5748","authenticated-orcid":false,"given":"Jiancheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shengli Clinical Medical College of Fujian Medical University, Fuzhou 350013, China"},{"name":"Department of Cardiology, Shengli Clinical Medical College of Fujian Medical University, Fuzhou University Affiliated Provincial Hospital, Fujian Provincial Hospital, No. 134 East Street, Gulou District, Fuzhou 350001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1208","DOI":"10.1111\/j.1540-8167.2010.01798.x","article-title":"Predictors of atrial fibrillation recurrence after radiofrequency catheter ablation: A systematic review","volume":"21","author":"Balk","year":"2010","journal-title":"J. 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