{"title":"一种基于互信息的改进医学图像配准算法","authors":"Tian Lan, Hongbo Jiang, Yi Ding, Zhiguang Qin","doi":"10.1109/ICVISP.2017.9","DOIUrl":null,"url":null,"abstract":"Medical image registration is widely used in clinical diagnosis, treatment, quality assurance and it's also the prerequisite to realize the fusion and reconstruction. This paper presents an improved medical image registration algorithm based on mutual information. First of all, B-spline gradient operator is adopted to detect edges of the reference image and the floating image and then get binarization image respectively. Next, in order to obtain the centroid coordinates, the moments of the binarization image is calculated. According to the edge detection operator, the rotation angle of thereference image and floating image are obtained. In this paper, improved mutual information (IMI) is used as a measure ofsimilarity between the reference and floating images. Theexperimental results show that the proposed algorithm has theadvantages of low computational complexity and high accuracy, and overcomes the shortcomings of the traditional mutual information easily falling into local optimum.","PeriodicalId":404467,"journal":{"name":"2017 International Conference on Vision, Image and Signal Processing (ICVISP)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Improved Medical Image Registration Algorithm Based on Mutual Information\",\"authors\":\"Tian Lan, Hongbo Jiang, Yi Ding, Zhiguang Qin\",\"doi\":\"10.1109/ICVISP.2017.9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Medical image registration is widely used in clinical diagnosis, treatment, quality assurance and it's also the prerequisite to realize the fusion and reconstruction. This paper presents an improved medical image registration algorithm based on mutual information. First of all, B-spline gradient operator is adopted to detect edges of the reference image and the floating image and then get binarization image respectively. Next, in order to obtain the centroid coordinates, the moments of the binarization image is calculated. According to the edge detection operator, the rotation angle of thereference image and floating image are obtained. In this paper, improved mutual information (IMI) is used as a measure ofsimilarity between the reference and floating images. Theexperimental results show that the proposed algorithm has theadvantages of low computational complexity and high accuracy, and overcomes the shortcomings of the traditional mutual information easily falling into local optimum.\",\"PeriodicalId\":404467,\"journal\":{\"name\":\"2017 International Conference on Vision, Image and Signal Processing (ICVISP)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Vision, Image and Signal Processing (ICVISP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICVISP.2017.9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Vision, Image and Signal Processing (ICVISP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVISP.2017.9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Improved Medical Image Registration Algorithm Based on Mutual Information
Medical image registration is widely used in clinical diagnosis, treatment, quality assurance and it's also the prerequisite to realize the fusion and reconstruction. This paper presents an improved medical image registration algorithm based on mutual information. First of all, B-spline gradient operator is adopted to detect edges of the reference image and the floating image and then get binarization image respectively. Next, in order to obtain the centroid coordinates, the moments of the binarization image is calculated. According to the edge detection operator, the rotation angle of thereference image and floating image are obtained. In this paper, improved mutual information (IMI) is used as a measure ofsimilarity between the reference and floating images. Theexperimental results show that the proposed algorithm has theadvantages of low computational complexity and high accuracy, and overcomes the shortcomings of the traditional mutual information easily falling into local optimum.