{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T06:19:37Z","timestamp":1775888377705,"version":"3.50.1"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Dipartimento di Ingegneria \"Enzo Ferrari\""},{"DOI":"10.13039\/100009104","name":"Universit? Degli Studi di Modena e Reggio Emila","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100009104","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003407","name":"Ministero dell?Istruzione, dell?Universit? e della Ricerca","doi-asserted-by":"publisher","award":["PNC0000007"],"award-info":[{"award-number":["PNC0000007"]}],"id":[{"id":"10.13039\/501100003407","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010661","name":"Horizon 2020 Framework Programme","doi-asserted-by":"publisher","award":["965193"],"award-info":[{"award-number":["965193"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/access.2025.3570461","type":"journal-article","created":{"date-parts":[[2025,5,15]],"date-time":"2025-05-15T17:33:41Z","timestamp":1747330421000},"page":"89748-89759","source":"Crossref","is-referenced-by-count":5,"title":["Taming Mambas for 3D Medical Image Segmentation"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1046-332X","authenticated-orcid":false,"given":"Luca","family":"Lumetti","sequence":"first","affiliation":[{"name":"Department of Engineering “Enzo Ferrari,”, University of Modena and Reggio Emilia, Modena, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-5749-6007","authenticated-orcid":false,"given":"Vittorio","family":"Pipoli","sequence":"additional","affiliation":[{"name":"Department of Engineering “Enzo Ferrari,”, University of Modena and Reggio Emilia, Modena, Italy"}]},{"given":"Kevin","family":"Marchesini","sequence":"additional","affiliation":[{"name":"Department of Engineering “Enzo Ferrari,”, University of Modena and Reggio Emilia, Modena, Italy"}]},{"given":"Elisa","family":"Ficarra","sequence":"additional","affiliation":[{"name":"Department of Engineering “Enzo Ferrari,”, University of Modena and Reggio Emilia, Modena, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4792-2358","authenticated-orcid":false,"given":"Costantino","family":"Grana","sequence":"additional","affiliation":[{"name":"Department of Engineering “Enzo Ferrari,”, University of Modena and Reggio Emilia, Modena, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5299-6351","authenticated-orcid":false,"given":"Federico","family":"Bolelli","sequence":"additional","affiliation":[{"name":"Department of Engineering “Enzo Ferrari,”, University of Modena and Reggio Emilia, Modena, Italy"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-020-09854-1"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2024.3523096"},{"key":"ref3","first-page":"1","article-title":"Segmenting maxillofacial structures in CBCT volume","volume-title":"Proc. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit. (CVPR)","author":"Bolelli"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.7303\/SYN3193805"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2010.11929"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref9","article-title":"A data-scalable transformer for medical image segmentation: Architecture, model efficiency, and benchmark","author":"Gao","year":"2022","journal-title":"arXiv:2203.00131"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2102.04306"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-25066-8_9"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00181"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-08999-2_22"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3408629"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-78104-9_8"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.naacl-main.319"},{"key":"ref17","first-page":"857","article-title":"Squeeze and learn: Compressing long sequences with Fourier transformers for gene expression prediction","volume-title":"Proc. 20th Int. Conf. Intell. Comput. (ICIC)","author":"Pipoli"},{"key":"ref18","article-title":"Linformer: Self-attention with linear complexity","author":"Wang","year":"2020","journal-title":"arXiv:2006.04768"},{"key":"ref19","first-page":"1","article-title":"Rethinking attention with performers","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Choromanski"},{"key":"ref20","article-title":"Longformer: The long-document transformer","author":"Beltagy","year":"2020","journal-title":"arXiv:2004.05150"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.01.012"},{"key":"ref22","article-title":"Efficiently modeling long sequences with structured state spaces","author":"Gu","year":"2021","journal-title":"arXiv:2111.00396"},{"key":"ref23","article-title":"Mamba: Linear-time sequence modeling with selective state spaces","author":"Gu","year":"2023","journal-title":"arXiv:2312.00752"},{"key":"ref24","first-page":"1474","article-title":"HiPPO: Recurrent memory with optimal polynomial projections","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Gu"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-30695-9"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2837502"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2020.01.013"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.21037\/qims-19-1090"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.79"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-020-01008-z"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.5040\/9781501365072.13350"},{"key":"ref32","article-title":"Combining recurrent, convolutional, and continuous-time models with linear state-space layers","author":"Gu","year":"2021","journal-title":"arXiv:2110.13985"},{"key":"ref33","first-page":"2397","article-title":"Pythia: A suite for analyzing large language models across training and scaling","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Biderman"},{"key":"ref34","volume-title":"GPT-J-6B: A 6 Billion Parameter Autoregressive Language Model","author":"Wang","year":"2021"},{"key":"ref35","article-title":"OPT: Open pre-trained transformer language models","author":"Zhang","year":"2022","journal-title":"arXiv:2205.01068"},{"key":"ref36","first-page":"1","article-title":"Hyena hierarchy: Towards larger convolutional language models","volume-title":"Proc. 40th Int. Conf. Mach. Learn.","author":"Poli"},{"key":"ref37","first-page":"103031","article-title":"VMamba: Visual state space model","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Liu"},{"key":"ref38","article-title":"NnMamba: 3D biomedical image segmentation, classification and landmark detection with state space model","author":"Gong","year":"2024","journal-title":"arXiv:2402.03526"},{"key":"ref39","article-title":"Mamba-UNet: UNet-like pure visual mamba for medical image segmentation","author":"Wang","year":"2024","journal-title":"arXiv:2402.05079"},{"key":"ref40","article-title":"VM-UNet: Vision mamba UNet for medical image segmentation","author":"Ruan","year":"2024","journal-title":"arXiv:2402.02491"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72111-3_54"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.3390\/app14135683"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI60581.2025.10981167"},{"key":"ref44","article-title":"U-mamba: Enhancing long-range dependency for biomedical image segmentation","author":"Ma","year":"2024","journal-title":"arXiv:2401.04722"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3293771"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2024.3398728"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-99-8543-2_4"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87199-4_16"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-43901-8_39"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87193-2_11"},{"key":"ref51","article-title":"MISSFormer: An effective medical image segmentation transformer","author":"Huang","year":"2021","journal-title":"arXiv:2109.07162"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-023-02151-z"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10820123\/11005448.pdf?arnumber=11005448","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,29]],"date-time":"2025-05-29T17:32:30Z","timestamp":1748539950000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11005448\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":52,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3570461","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}