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However, for MMIF tasks, it is thought that this structure cuts off the internal connections between source images, resulting in information redundancy and degradation of fusion performance. To this end, this paper proposes a novel unsupervised network, termed CEFusion. Different from existing architecture, a cross\u2010encoder is designed by exploiting the complementary properties between the original image to refine source features through feature interaction and reuse. Furthermore, to force the network to learn complementary information between source images and generate the fused image with high contrast and rich textures, a hybrid loss is proposed consisting of weighted fidelity and gradient losses. 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Experimental results demonstrate the superiority of the method over the state\u2010of\u2010the\u2010art in terms of subjective visual effect and quantitative metrics in various datasets.<\/jats:p>","DOI":"10.1049\/ipr2.12549","type":"journal-article","created":{"date-parts":[[2022,6,9]],"date-time":"2022-06-09T23:44:16Z","timestamp":1654818256000},"page":"3177-3189","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["CEFusion: Multi\u2010Modal medical image fusion via cross encoder"],"prefix":"10.1049","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2236-525X","authenticated-orcid":false,"given":"Ya","family":"Zhu","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering Yunnan University  Kunming 650500 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xue","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering Yunnan University  Kunming 650500 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luping","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering Yunnan University  Kunming 650500 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rencan","family":"Nie","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering Yunnan University  Kunming 650500 China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"265","published-online":{"date-parts":[[2022,6,9]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107087"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2018.2838778"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.07.160"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2020.2975405"},{"issue":"2","key":"e_1_2_9_6_1","first-page":"24","article-title":"Medical imaging market: Moving up","volume":"16","author":"Les C.B.","year":"2009","journal-title":"Biophotonics International"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2021.06.083"},{"key":"e_1_2_9_8_1","article-title":"Multimodal medical image fusion based on joint bilateral filter and local gradient energy","author":"Xl A.","year":"2021","journal-title":"Inf. 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