{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T20:01:46Z","timestamp":1780603306361,"version":"3.54.1"},"reference-count":62,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Biomedical Signal Processing and Control"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.bspc.2026.110665","type":"journal-article","created":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T01:21:56Z","timestamp":1779412916000},"page":"110665","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["MedHyperMamba: A multi-capable Mamba with multimodal registration, denoising and novel hypergraph scanning for MRI brain tumor segmentation"],"prefix":"10.1016","volume":"124","author":[{"given":"Yiming","family":"Yang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2468-3881","authenticated-orcid":false,"given":"Lingyu","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7935-7173","authenticated-orcid":false,"given":"Rong","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ci","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"8","key":"10.1016\/j.bspc.2026.110665_b1","doi-asserted-by":"crossref","first-page":"1231","DOI":"10.1093\/neuonc\/noab106","article-title":"The 2021 WHO classification of tumors of the central nervous system: a summary","volume":"23","author":"Louis","year":"2021","journal-title":"Neuro-Oncol."},{"issue":"10412","key":"10.1016\/j.bspc.2026.110665_b2","doi-asserted-by":"crossref","first-page":"1564","DOI":"10.1016\/S0140-6736(23)01054-1","article-title":"Primary brain tumours in adults","volume":"402","author":"Van den Bent","year":"2023","journal-title":"Lancet"},{"issue":"20","key":"10.1016\/j.bspc.2026.110665_b3","doi-asserted-by":"crossref","first-page":"14611","DOI":"10.1007\/s00521-021-05841-x","article-title":"Deep neural network correlation learning mechanism for CT brain tumor detection","volume":"35","author":"Wo\u017aniak","year":"2023","journal-title":"Neural Comput. Appl."},{"key":"10.1016\/j.bspc.2026.110665_b4","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.bspc.2026.110665_b5","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"107","article-title":"Mmformer: Multimodal medical transformer for incomplete multimodal learning of brain tumor segmentation","author":"Zhang","year":"2022"},{"key":"10.1016\/j.bspc.2026.110665_b6","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"333","article-title":"Eoformer: Edge-oriented transformer for brain tumor segmentation","author":"She","year":"2023"},{"key":"10.1016\/j.bspc.2026.110665_b7","unstructured":"Albert Gu, Tri Dao, Mamba: Linear-time sequence modeling with selective state spaces, in: First Conference on Language Modeling, 2024."},{"key":"10.1016\/j.bspc.2026.110665_b8","first-page":"572","article-title":"Combining recurrent, convolutional, and continuous-time models with linear state space layers","volume":"34","author":"Gu","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.bspc.2026.110665_b9","series-title":"Global and local mamba network for multi-modality medical image super-resolution","author":"Ji","year":"2025"},{"key":"10.1016\/j.bspc.2026.110665_b10","series-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","first-page":"19077","article-title":"Segman: Omni-scale context modeling with state space models and local attention for semantic segmentation","author":"Fu","year":"2025"},{"issue":"3","key":"10.1016\/j.bspc.2026.110665_b11","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1007\/s11263-026-02776-5","article-title":"Physical regularization loss: Integrating physical knowledge to image segmentation","volume":"134","author":"Ding","year":"2026","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.bspc.2026.110665_b12","doi-asserted-by":"crossref","DOI":"10.1109\/TMI.2025.3579213","article-title":"Rethinking brain tumor segmentation from the frequency domain perspective","author":"Shao","year":"2025","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.bspc.2026.110665_b13","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2024.106809","article-title":"A dual-domain framework for multimodal medical image registration: Optimizing phase consistency with LPC-GIMI","volume":"99","author":"Chen","year":"2025","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.bspc.2026.110665_b14","first-page":"1889","article-title":"Famnet: Frequency-aware matching network for cross-domain few-shot medical image segmentation","volume":"vol. 39","author":"Bo","year":"2025"},{"key":"10.1016\/j.bspc.2026.110665_b15","first-page":"4428","article-title":"A unified degradation-robust approach to SSL and UDA for 3D medical images","volume":"vol. 39","author":"Kumari","year":"2025"},{"key":"10.1016\/j.bspc.2026.110665_b16","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2025.107505","article-title":"MSDMAT-BTS: Multi-scale diffusion model and attention mechanism for brain tumor segmentation","volume":"104","author":"Gao","year":"2025","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.bspc.2026.110665_b17","article-title":"M2GCNet: Multi-modal graph convolution network for precise brain tumor segmentation across multiple MRI sequences","author":"Zhou","year":"2024","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.bspc.2026.110665_b18","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"23","article-title":"A novel adaptive hypergraph neural network for enhancing medical image segmentation","author":"Chai","year":"2024"},{"key":"10.1016\/j.bspc.2026.110665_b19","doi-asserted-by":"crossref","unstructured":"Wanting Zhang, Zhenhui Ding, Guilian Chen, Huisi Wu, Jing Qin, RA-BUSSeg: Relation-aware Semi-supervised Breast Ultrasound Image Segmentation via Adjacent Propagation and Cross-layer Alignment, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2025, pp. 21689\u201321698.","DOI":"10.1109\/ICCV51701.2025.02014"},{"key":"10.1016\/j.bspc.2026.110665_b20","article-title":"Hypergraph-driven anomaly detection in dynamic noisy graphs","author":"Liu","year":"2025","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"10.1016\/j.bspc.2026.110665_b21","series-title":"Vl-mamba: Exploring state space models for multimodal learning. arxiv 2024","author":"Qiao","year":"2024"},{"key":"10.1016\/j.bspc.2026.110665_b22","series-title":"European Conference on Computer Vision","first-page":"148","article-title":"Zigma: A dit-style zigzag mamba diffusion model","author":"Hu","year":"2024"},{"key":"10.1016\/j.bspc.2026.110665_b23","first-page":"103031","article-title":"Vmamba: Visual state space model","volume":"37","author":"Liu","year":"2024","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.bspc.2026.110665_b24","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.bspc.2026.110665_b25","series-title":"Transunet: Transformers make strong encoders for medical image segmentation","author":"Chen","year":"2021"},{"issue":"9","key":"10.1016\/j.bspc.2026.110665_b26","doi-asserted-by":"crossref","first-page":"2740","DOI":"10.1109\/TMI.2023.3264433","article-title":"MISSU: 3D medical image segmentation via self-distilling TransUNet","volume":"42","author":"Wang","year":"2023","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"7","key":"10.1016\/j.bspc.2026.110665_b27","doi-asserted-by":"crossref","first-page":"2495","DOI":"10.1109\/TMI.2024.3368531","article-title":"Shape-scale co-awareness network for 3D brain tumor segmentation","volume":"43","author":"Zhou","year":"2024","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.bspc.2026.110665_b28","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.121574","article-title":"TranSiam: Aggregating multi-modal visual features with locality for medical image segmentation","volume":"237","author":"Li","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.bspc.2026.110665_b29","doi-asserted-by":"crossref","first-page":"7222","DOI":"10.1109\/TIP.2025.3623259","article-title":"Probability map-guided network for 3d volumetric medical image segmentation","volume":"34","author":"Zhu","year":"2025","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"10.1016\/j.bspc.2026.110665_b30","doi-asserted-by":"crossref","first-page":"7948","DOI":"10.1038\/s41467-022-35655-x","article-title":"A pH-responsive T1-T2 dual-modal MRI contrast agent for cancer imaging","volume":"13","author":"Lu","year":"2022","journal-title":"Nat. Commun."},{"key":"10.1016\/j.bspc.2026.110665_b31","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110282","article-title":"Multi-modal brain tumor segmentation via disentangled representation learning and region-aware contrastive learning","volume":"149","author":"Zhou","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.bspc.2026.110665_b32","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111926","article-title":"Hyper-BTS: Brain tumor segmentation based on hypergraph guidance","volume":"169","author":"Guo","year":"2026","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.bspc.2026.110665_b33","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111544","article-title":"Multi-modal hypergraph contrastive learning for medical image segmentation","volume":"165","author":"Jing","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.bspc.2026.110665_b34","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2025.108925","article-title":"Multi-scale attention and hypergraph neural network based deep learning framework for prostate cancer classification and segmentation","volume":"113","author":"Palanisamy","year":"2026","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.bspc.2026.110665_b35","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2025.108568","article-title":"HHGCN: Hybrid hypergraph convolutional and graph convolutional network for prognostic prediction of intracerebral hemorrhage","volume":"112","author":"Duan","year":"2026","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.bspc.2026.110665_b36","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.127032","article-title":"Adaptive dual-path spatial-frequency network for medical microstructure segmentation","volume":"275","author":"Xie","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.bspc.2026.110665_b37","series-title":"2025 IEEE\/CVF Winter Conference on Applications of Computer Vision","first-page":"9176","article-title":"Frequency-domain refinement of vision transformers for robust medical image segmentation under degradation","author":"Karimijarbigloo","year":"2025"},{"key":"10.1016\/j.bspc.2026.110665_b38","series-title":"U-mamba: Enhancing long-range dependency for biomedical image segmentation","author":"Ma","year":"2024"},{"key":"10.1016\/j.bspc.2026.110665_b39","series-title":"Mamba-unet: Unet-like pure visual mamba for medical image segmentation","author":"Wang","year":"2024"},{"key":"10.1016\/j.bspc.2026.110665_b40","article-title":"Vm-unet: Vision mamba unet for medical image segmentation","author":"Ruan","year":"2024","journal-title":"ACM Trans. Multimed. Comput. Commun. Appl."},{"key":"10.1016\/j.bspc.2026.110665_b41","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"615","article-title":"Swin-umamba: Mamba-based unet with imagenet-based pretraining","author":"Liu","year":"2024"},{"key":"10.1016\/j.bspc.2026.110665_b42","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.129447","article-title":"H-vmunet: High-order vision mamba unet for medical image segmentation","volume":"624","author":"Wu","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.bspc.2026.110665_b43","series-title":"Hc-mamba: Vision mamba with hybrid convolutional techniques for medical image segmentation","author":"Xu","year":"2024"},{"key":"10.1016\/j.bspc.2026.110665_b44","doi-asserted-by":"crossref","unstructured":"Leiye Liu, Miao Zhang, Jihao Yin, Tingwei Liu, Wei Ji, Yongri Piao, Huchuan Lu, Defmamba: Deformable visual state space model, in: Proceedings of the Computer Vision and Pattern Recognition Conference, 2025, pp. 8838\u20138847.","DOI":"10.1109\/CVPR52734.2025.00826"},{"key":"10.1016\/j.bspc.2026.110665_b45","series-title":"DAMamba: Vision state space model with dynamic adaptive scan","author":"Li","year":"2025"},{"key":"10.1016\/j.bspc.2026.110665_b46","article-title":"GraphMamba: Graph-driven spatial order-aware mamba for medical image segmentation","author":"Yu","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.bspc.2026.110665_b47","article-title":"Visually stabilized mamba U-shaped network with strong inductive bias for 3D brain tumor segmentation","author":"Zhu","year":"2025","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.bspc.2026.110665_b48","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.112676","article-title":"A lightweight vision mamba coding unet for medical image segmentation","volume":"162","author":"Li","year":"2025","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.bspc.2026.110665_b49","article-title":"MedMamba: Multi-scale deformable attention via state space models for robust medical image segmentation","volume":"112","author":"Wang","year":"2026","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.bspc.2026.110665_b50","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"98","article-title":"Brats-umamba: Adaptive mamba unet with dual-band frequency based feature enhancement for brain tumor segmentation","author":"Yao","year":"2025"},{"key":"10.1016\/j.bspc.2026.110665_b51","series-title":"The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification","author":"Baid","year":"2021"},{"key":"10.1016\/j.bspc.2026.110665_b52","series-title":"Diff-unet: A diffusion embedded network for volumetric segmentation","author":"Xing","year":"2023"},{"issue":"6","key":"10.1016\/j.bspc.2026.110665_b53","doi-asserted-by":"crossref","first-page":"1856","DOI":"10.1109\/TMI.2019.2959609","article-title":"Unet++: Redesigning skip connections to exploit multiscale features in image segmentation","volume":"39","author":"Zhou","year":"2019","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"4","key":"10.1016\/j.bspc.2026.110665_b54","doi-asserted-by":"crossref","first-page":"1836","DOI":"10.1109\/TMI.2025.3526604","article-title":"Asymmetric adaptive heterogeneous network for multi-modality medical image segmentation","volume":"44","author":"Zheng","year":"2025","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.bspc.2026.110665_b55","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.128835","article-title":"CFFormer: Cross CNN-transformer channel attention and spatial feature fusion for improved segmentation of heterogeneous medical images","volume":"295","author":"Li","year":"2026","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.bspc.2026.110665_b56","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2024.109353","article-title":"LATUP-Net: A lightweight 3D attention U-Net with parallel convolutions for brain tumor segmentation","volume":"184","author":"Alwadee","year":"2025","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.bspc.2026.110665_b57","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2025.109220","article-title":"Collaborative encoding attributed hybrid attention knowledge distillation for missing-modality brain tumor segmentation","volume":"113","author":"Zheng","year":"2026","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.bspc.2026.110665_b58","series-title":"MedVKAN: Efficient feature extraction with mamba and KAN for medical image segmentation","author":"Zhu","year":"2025"},{"key":"10.1016\/j.bspc.2026.110665_b59","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"225","article-title":"Im-fuse: A mamba-based fusion block for brain tumor segmentation with incomplete modalities","author":"Pipoli","year":"2025"},{"key":"10.1016\/j.bspc.2026.110665_b60","article-title":"Segmamba-v2: Long-range sequential modeling mamba for general 3d medical image segmentation","author":"Xing","year":"2025","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.bspc.2026.110665_b61","doi-asserted-by":"crossref","DOI":"10.1109\/JBHI.2026.3659853","article-title":"MEM-UNet: Morphology-enhanced 3D mamba unet for esophagus segmentation","author":"Lin","year":"2026","journal-title":"IEEE J. Biomed. Health Informatics"},{"key":"10.1016\/j.bspc.2026.110665_b62","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2022.102680","article-title":"The liver tumor segmentation benchmark (lits)","volume":"84","author":"Bilic","year":"2023","journal-title":"Med. Image Anal."}],"container-title":["Biomedical Signal Processing and Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S174680942601219X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S174680942601219X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T19:34:05Z","timestamp":1780601645000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S174680942601219X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":62,"alternative-id":["S174680942601219X"],"URL":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110665","relation":{},"ISSN":["1746-8094"],"issn-type":[{"value":"1746-8094","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"MedHyperMamba: A multi-capable Mamba with multimodal registration, denoising and novel hypergraph scanning for MRI brain tumor segmentation","name":"articletitle","label":"Article Title"},{"value":"Biomedical Signal Processing and Control","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110665","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"110665"}}