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Intell."],"published-print":{"date-parts":[[2025,9,30]]},"abstract":"<jats:p> Medical image fusion is an image processing method that uses computer technology to integrate medical images of different modalities to achieve synchronous visualization of multiple types of information; in this way, multiple medical images complement each other, increasing the accuracy and completeness of clinical diagnosis and treatment. Multiple medical image fusion algorithms have been developed, but they all have drawbacks. One of these is that they are not always reusable or portable due to issues such as faulty fusion rule design. Image reconstruction leads to a decrease in image quality, as the reconstruction process may lose some original information, and the complexity of transformation algorithms and medical images can easily affect performance and robustness. By merging spectral residual (SR) saliency with total variation decomposition, this paper presents a medical image fusion method that addresses current issues. Using total variation, we first dissect the source images to identify their structural and textural elements. Additionally, SRs are utilized for the extraction of saliency images. Moreover, separate procedures are used to merge the structural, textural, and saliency pictures. Finally, the three fused images are added together to form the final product. In terms of both clarity of detail and information retention, our experimental results show that this approach is superior to competing methods. In addition, our [Formula: see text] increased by 31.76%, and our [Formula: see text] increased by 48.19% compared with the average value of the reference algorithms. <\/jats:p>","DOI":"10.1142\/s0218001425570162","type":"journal-article","created":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T00:11:24Z","timestamp":1749773484000},"source":"Crossref","is-referenced-by-count":0,"title":["Multimodal Medical Image Fusion Based on Total Variation Decomposition and Spectral Residual Saliency"],"prefix":"10.1142","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6225-3535","authenticated-orcid":false,"given":"Xiaolong","family":"Gu","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.\u00a0R.\u00a0China"},{"name":"National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing, P.\u00a0R.\u00a0China"}]},{"given":"Ying","family":"Xia","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.\u00a0R.\u00a0China"}]},{"given":"Ying","family":"Wei","sequence":"additional","affiliation":[{"name":"School of Business Administration, Chongqing Technology and Business University, Chongqing, P.\u00a0R.\u00a0China"}]}],"member":"219","published-online":{"date-parts":[[2025,7,23]]},"reference":[{"key":"S0218001425570162BIB001","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2015.2465935"},{"key":"S0218001425570162BIB002","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2013.2244870"},{"key":"S0218001425570162BIB003","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2020.105603"},{"key":"S0218001425570162BIB004","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2017.12.008"},{"key":"S0218001425570162BIB005","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2016.09.008"},{"key":"S0218001425570162BIB006","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2023.104814"},{"key":"S0218001425570162BIB007","doi-asserted-by":"publisher","DOI":"10.1049\/iet-ipr.2017.0104"},{"key":"S0218001425570162BIB008","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-013-9664-x"},{"key":"S0218001425570162BIB009","doi-asserted-by":"publisher","DOI":"10.1049\/iet-ipr.2012.0558"},{"key":"S0218001425570162BIB010","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2011.08.002"},{"key":"S0218001425570162BIB011","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2024.108381"},{"key":"S0218001425570162BIB012","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.09.018"},{"key":"S0218001425570162BIB013","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2633863"},{"first-page":"1","volume-title":"IEEE Conf. 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