{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T02:24:10Z","timestamp":1774405450713,"version":"3.50.1"},"reference-count":37,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T00:00:00Z","timestamp":1757462400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Basic Scientific Research Project of Liaoning Provincial Department of Education","award":["LJKMZ20220497"],"award-info":[{"award-number":["LJKMZ20220497"]}]},{"name":"Shenyang University of Technology","award":["LJKMZ20220497"],"award-info":[{"award-number":["LJKMZ20220497"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Accurate glomerular segmentation in renal pathological images is a key challenge for chronic kidney disease diagnosis and assessment. Due to the high visual similarity between pathological glomeruli and surrounding tissues in color, texture, and morphology, significant \u201ccamouflage phenomena\u201d exist, leading to boundary identification difficulties. To address this problem, we propose BM-UNet, a novel segmentation framework that embeds boundary guidance mechanisms into a Mamba architecture with a symmetric encoder\u2013decoder design. The framework enhances feature transmission through explicit boundary detection, incorporating four core modules designed for key challenges in pathological image segmentation. The Multi-scale Adaptive Fusion (MAF) module processes irregular tissue morphology, the Hybrid Boundary Detection (HBD) module handles boundary feature extraction, the Boundary-guided Attention (BGA) module achieves boundary-aware feature refinement, and the Mamba-based Fused Decoder Block (MFDB) completes boundary-preserving reconstruction. By introducing explicit boundary supervision mechanisms, the framework achieves significant segmentation accuracy improvements while maintaining linear computational complexity. Validation on the KPIs2024 glomerular dataset and HuBMAP renal tissue samples demonstrates that BM-UNet achieves a 92.4\u201395.3% mean Intersection over Union across different CKD pathological conditions, with a 4.57% improvement over the Mamba baseline and a processing speed of 113.7 FPS.<\/jats:p>","DOI":"10.3390\/sym17091506","type":"journal-article","created":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T12:04:55Z","timestamp":1757505895000},"page":"1506","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Symmetric Boundary-Enhanced U-Net with Mamba Architecture for Glomerular Segmentation in Renal Pathological Images"],"prefix":"10.3390","volume":"17","author":[{"given":"Shengnan","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Software, Shenyang University of Technology, Shenyang 110870, China"},{"name":"Shenyang Key Laboratory of Intelligent Technology of Advanced Industrial Equipment Manufacturing, Shenyang 110870, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5571-7104","authenticated-orcid":false,"given":"Xinming","family":"Cui","sequence":"additional","affiliation":[{"name":"School of Software, Shenyang University of Technology, Shenyang 110870, China"},{"name":"Shenyang Key Laboratory of Intelligent Technology of Advanced Industrial Equipment Manufacturing, Shenyang 110870, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangkun","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Software, Shenyang University of Technology, Shenyang 110870, China"},{"name":"Shenyang Key Laboratory of Intelligent Technology of Advanced Industrial Equipment Manufacturing, Shenyang 110870, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ronghui","family":"Tian","sequence":"additional","affiliation":[{"name":"School of Software, Shenyang University of Technology, Shenyang 110870, China"},{"name":"Shenyang Key Laboratory of Intelligent Technology of Advanced Industrial Equipment Manufacturing, Shenyang 110870, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.kisu.2021.11.003","article-title":"Epidemiology of chronic kidney disease: An update 2022","volume":"12","author":"Kovesdy","year":"2022","journal-title":"Kidney Int. 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