{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,17]],"date-time":"2026-05-17T11:06:31Z","timestamp":1779015991697,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":19,"publisher":"ACM","funder":[{"name":"Guangxi Science and Technology Major Program","award":["GuikeAA23073007"],"award-info":[{"award-number":["GuikeAA23073007"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,27]]},"DOI":"10.1145\/3794209.3794210","type":"proceedings-article","created":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T04:18:59Z","timestamp":1778559539000},"page":"1-6","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["HD-MMHA-Net:A Hybrid Domain Masked Multi-Head Attention network for liver segmentation from 3D Medical Image"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-7240-6239","authenticated-orcid":false,"given":"Xionghao","family":"Yao","sequence":"first","affiliation":[{"name":"Zhongshan Institute,University of Electronic Science and Technology of China, Zhongshan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1757-302X","authenticated-orcid":false,"given":"Xueyi","family":"Gong","sequence":"additional","affiliation":[{"name":"Zhongshan People's Hospital, Zhongshan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9541-6790","authenticated-orcid":false,"given":"Ziyi","family":"Chen","sequence":"additional","affiliation":[{"name":"South China Agricultural University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2099-2687","authenticated-orcid":false,"given":"Yiqin","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Shanghai for Science and Technology, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4605-7534","authenticated-orcid":false,"given":"Cheng","family":"Peng","sequence":"additional","affiliation":[{"name":"Zhongshan Institute,University of Electronic Science and Technology of China, Zhongshan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0421-655X","authenticated-orcid":false,"given":"Dong","family":"Wang","sequence":"additional","affiliation":[{"name":"South China Agricultural University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,5,11]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"crossref","unstructured":"Omar\u00a0Ibrahim Alirr. 2020. Deep learning and level set approach for liver and tumor segmentation from CT scans. Journal of Applied Clinical Medical Physics 21 10 (2020) 200\u2013209.","DOI":"10.1002\/acm2.13003"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"crossref","unstructured":"Deepshikha Bhati Fnu Neha and Md Amiruzzaman. 2024. A survey on explainable artificial intelligence (xai) techniques for visualizing deep learning models in medical imaging. Journal of Imaging 10 10 (2024) 239.","DOI":"10.3390\/jimaging10100239"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"crossref","unstructured":"Patrick Bilic Patrick Christ Hongwei\u00a0Bran Li Eugene Vorontsov Avi Ben-Cohen Georgios Kaissis Adi Szeskin Colin Jacobs Gabriel Efrain\u00a0Humpire Mamani Gabriel Chartrand et\u00a0al. 2023. The liver tumor segmentation benchmark (lits). Medical image analysis 84 (2023) 102680.","DOI":"10.1016\/j.media.2022.102680"},{"key":"e_1_3_3_1_5_2","first-page":"205","volume-title":"European conference on computer vision","author":"Cao Hu","year":"2022","unstructured":"Hu Cao, Yueyue Wang, Joy Chen, Dongsheng Jiang, Xiaopeng Zhang, Qi Tian, and Manning Wang. 2022. Swin-unet: Unet-like pure transformer for medical image segmentation. In European conference on computer vision. Springer, 205\u2013218."},{"key":"e_1_3_3_1_6_2","unstructured":"Jieneng Chen Yongyi Lu Qihang Yu Xiangde Luo Ehsan Adeli Yan Wang Le Lu Alan\u00a0L Yuille and Yuyin Zhou. 2021. Transunet: Transformers make strong encoders for medical image segmentation. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2102.04306 (2021)."},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"publisher","unstructured":"Jieneng Chen Jieru Mei Xianhang Li Yongyi Lu Qihang Yu Qingyue Wei Xiangde Luo Yutong Xie Ehsan Adeli Yan Wang Matthew\u00a0P. Lungren Shaoting Zhang Lei Xing Le Lu Alan Yuille and Yuyin Zhou. 2024. TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformers. Medical Image Analysis 97 (2024) 103280. 10.1016\/j.media.2024.103280","DOI":"10.1016\/j.media.2024.103280"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87199-4_6"},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"crossref","unstructured":"Ross Girshick Jeff Donahue Trevor Darrell and Jitendra Malik. 2015. Region-based convolutional networks for accurate object detection and segmentation. IEEE transactions on pattern analysis and machine intelligence 38 1 (2015) 142\u2013158.","DOI":"10.1109\/TPAMI.2015.2437384"},{"key":"e_1_3_3_1_10_2","unstructured":"Larry\u00a0R Medsker Lakhmi Jain et\u00a0al. 2001. Recurrent neural networks. Design and applications 5 64-67 (2001) 2."},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.79"},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1117\/12.3071689"},{"key":"e_1_3_3_1_13_2","unstructured":"Fnu Neha Deepshikha Bhati Deepak\u00a0Kumar Shukla Sonavi\u00a0Makarand Dalvi Nikolaos Mantzou and Safa Shubbar. 2024. U-net in medical image segmentation: A review of its applications across modalities. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2412.02242 (2024)."},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW63382.2024.00503"},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"crossref","unstructured":"Harriet Rumgay Melina Arnold Jacques Ferlay Olufunmilayo Lesi Citadel\u00a0J Cabasag J\u00e9r\u00f4me Vignat Mathieu Laversanne Katherine\u00a0A McGlynn and Isabelle Soerjomataram. 2022. Global burden of primary liver cancer in 2020 and predictions to 2040. Journal of hepatology 77 6 (2022) 1598\u20131606.","DOI":"10.1016\/j.jhep.2022.08.021"},{"key":"e_1_3_3_1_17_2","unstructured":"Christian Rupprecht Elizabeth Huaroc Maximilian Baust and Nassir Navab. 2016. Deep active contours. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/1607.05074 (2016)."},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"crossref","unstructured":"Hamid\u00a0Reza Saeidnia Faezeh Firuzpour Marcin Kozak and Hooman\u00a0Soleymani Majd. 2025. Advancing cancer diagnosis and treatment: integrating image analysis and AI algorithms for enhanced clinical practice. Artificial Intelligence Review 58 4 (2025) 105.","DOI":"10.1007\/s10462-025-11117-w"},{"key":"e_1_3_3_1_19_2","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan\u00a0N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_3_1_20_2","unstructured":"Enze Xie Wenhai Wang Zhiding Yu Anima Anandkumar Jose\u00a0M Alvarez and Ping Luo. 2021. SegFormer: Simple and efficient design for semantic segmentation with transformers. Advances in neural information processing systems 34 (2021) 12077\u201312090."}],"event":{"name":"ICBBE 2025: 2025 12th International Conference on Biomedical and Bioinformatics Engineering","location":"Tokyo Japan","acronym":"ICBBE 2025"},"container-title":["Proceedings of the 2025 12th International Conference on Biomedical and Bioinformatics Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3794209.3794210","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,17]],"date-time":"2026-05-17T10:18:27Z","timestamp":1779013107000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3794209.3794210"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,27]]},"references-count":19,"alternative-id":["10.1145\/3794209.3794210","10.1145\/3794209"],"URL":"https:\/\/doi.org\/10.1145\/3794209.3794210","relation":{},"subject":[],"published":{"date-parts":[[2025,11,27]]},"assertion":[{"value":"2026-05-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}