{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:35:33Z","timestamp":1761176133605,"version":"build-2065373602"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>Seismic fault image segmentation is crucial for interpreting subsurface geological structures, supporting geologists in resource exploration and structural analysis. However, current deep learning models struggle with single-architecture limitations and the distinctive characteristics of seismic faults, which are distinguished by elongated structures with uneven spatial distributions. To address these challenges, we propose TopSUMseg, a novel Topology-Aware Swin Transformer-Mamba framework for 3D seismic fault image segmentation. Our framework combines Swin Transformer\u2019s local feature extraction with Mamba\u2019s efficient sequence modeling, and boosts 3D spatial modeling in Mamba with a newly designed Global-Local Attention module (GLA). Additionally, we design a Topology-Aware Structural Constraint (TASC) to align predictions with ground-truth structures in the feature space, promoting the modeling of complex fault geometries. Experiments on Thebe, the largest public seismic dataset, demonstrate that TopSUMseg achieves state-of-the-art performance with OIS and ODS scores of 0.879 and 0.875, respectively. Trained entirely from scratch, TopSUMseg nonetheless achieves superior performance compared to extensively pre-trained counterparts. In addition, TopSUMseg maintains a significantly lower parameter count while achieving a favorable trade-off between segmentation performance and time complexity, making it a practical and generalizable solution for real-world seismic fault interpretation.<\/jats:p>","DOI":"10.3233\/faia250865","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:44:27Z","timestamp":1761126267000},"source":"Crossref","is-referenced-by-count":0,"title":["TopSUMseg: A Topology-Aware Swin Transformer-Mamba Framework for 3D Seismic Fault Image Segmentation"],"prefix":"10.3233","author":[{"given":"Ran","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Information and Computational Sciences, School of Mathematical Sciences, Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyang","family":"Deng","sequence":"additional","affiliation":[{"name":"Department of Information and Computational Sciences, School of Mathematical Sciences, Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zeren","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Information and Computational Sciences, School of Mathematical Sciences, Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruohua","family":"Shi","sequence":"additional","affiliation":[{"name":"National Engineering Research Center of Visual Technology, School of Computer Science, Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinwen","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Information and Computational Sciences, School of Mathematical Sciences, Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA250865","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:44:28Z","timestamp":1761126268000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA250865"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia250865","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}