Z. Xinyu, Wang Ziyi, Cao Guogang, Chen Ying, W. Yijie, Li Mengxue, Liu Shunkun, Mao Hongdong
{"title":"医学图像配准目标空间混沌头脑风暴优化算法","authors":"Z. Xinyu, Wang Ziyi, Cao Guogang, Chen Ying, W. Yijie, Li Mengxue, Liu Shunkun, Mao Hongdong","doi":"10.1109/ICIIBMS50712.2020.9336423","DOIUrl":null,"url":null,"abstract":"Image registration is the basis of medical image analysis whichhas profound significance in the field of medical image processing. In order to improve its accuracy, a method based on chaotic brain storm optimization algorithm in objective space(CBSO-OS) is proposed. The CBSO-OS increases its ability of global exploitation by replacing random function with guass map. Compared with other four optimization algorithms in image registration experiments, the root mean square error of the proposed algorithm is reduced by 0.69%, 2.26%, 3.54% and 1.37%, respectively. Meanwhile, the translation error of the proposed registration algorithm is the smallest. Experimental results show that the proposed registration algorithm effectively reduces the registration error of medical images so as to provide doctors with high-precision registered images.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Chaotic Brain Storm Optimization Algorithm in Objective Space for Medical Image Registration\",\"authors\":\"Z. Xinyu, Wang Ziyi, Cao Guogang, Chen Ying, W. Yijie, Li Mengxue, Liu Shunkun, Mao Hongdong\",\"doi\":\"10.1109/ICIIBMS50712.2020.9336423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image registration is the basis of medical image analysis whichhas profound significance in the field of medical image processing. In order to improve its accuracy, a method based on chaotic brain storm optimization algorithm in objective space(CBSO-OS) is proposed. The CBSO-OS increases its ability of global exploitation by replacing random function with guass map. Compared with other four optimization algorithms in image registration experiments, the root mean square error of the proposed algorithm is reduced by 0.69%, 2.26%, 3.54% and 1.37%, respectively. Meanwhile, the translation error of the proposed registration algorithm is the smallest. Experimental results show that the proposed registration algorithm effectively reduces the registration error of medical images so as to provide doctors with high-precision registered images.\",\"PeriodicalId\":243033,\"journal\":{\"name\":\"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIIBMS50712.2020.9336423\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIIBMS50712.2020.9336423","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Chaotic Brain Storm Optimization Algorithm in Objective Space for Medical Image Registration
Image registration is the basis of medical image analysis whichhas profound significance in the field of medical image processing. In order to improve its accuracy, a method based on chaotic brain storm optimization algorithm in objective space(CBSO-OS) is proposed. The CBSO-OS increases its ability of global exploitation by replacing random function with guass map. Compared with other four optimization algorithms in image registration experiments, the root mean square error of the proposed algorithm is reduced by 0.69%, 2.26%, 3.54% and 1.37%, respectively. Meanwhile, the translation error of the proposed registration algorithm is the smallest. Experimental results show that the proposed registration algorithm effectively reduces the registration error of medical images so as to provide doctors with high-precision registered images.