{"title":"基于遗传算法的医学图像配准","authors":"S. Shanmugapriya, S. Poonguzhali, U. Maheshwari","doi":"10.5121/SIPIJ.2014.5305","DOIUrl":null,"url":null,"abstract":"Medical imaging plays a vital role to create images of human body for clinical purposes. Biomedical imaging has taken a leap by entering into the field of image registration. Image registration integrates the large amount of medical information embedded in the images taken at different time intervals and images at different orientations. In this paper, an intensity-based real-coded genetic algorithm is used for registering two MRI images. To demonstrate the efficiency of the algorithm developed, the alignment of the image is altered and algorithm is tested for better performance. Also the work involves the comparison of two similarity metrics, and based on the outcome the best metric suited for genetic algorithm is studied.","PeriodicalId":90726,"journal":{"name":"Signal and image processing : an international journal","volume":"27 1","pages":"53-58"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Intensity-Based Medical Image Registration Using Genetic Algorithm\",\"authors\":\"S. Shanmugapriya, S. Poonguzhali, U. Maheshwari\",\"doi\":\"10.5121/SIPIJ.2014.5305\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Medical imaging plays a vital role to create images of human body for clinical purposes. Biomedical imaging has taken a leap by entering into the field of image registration. Image registration integrates the large amount of medical information embedded in the images taken at different time intervals and images at different orientations. In this paper, an intensity-based real-coded genetic algorithm is used for registering two MRI images. To demonstrate the efficiency of the algorithm developed, the alignment of the image is altered and algorithm is tested for better performance. Also the work involves the comparison of two similarity metrics, and based on the outcome the best metric suited for genetic algorithm is studied.\",\"PeriodicalId\":90726,\"journal\":{\"name\":\"Signal and image processing : an international journal\",\"volume\":\"27 1\",\"pages\":\"53-58\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Signal and image processing : an international journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5121/SIPIJ.2014.5305\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal and image processing : an international journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/SIPIJ.2014.5305","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Intensity-Based Medical Image Registration Using Genetic Algorithm
Medical imaging plays a vital role to create images of human body for clinical purposes. Biomedical imaging has taken a leap by entering into the field of image registration. Image registration integrates the large amount of medical information embedded in the images taken at different time intervals and images at different orientations. In this paper, an intensity-based real-coded genetic algorithm is used for registering two MRI images. To demonstrate the efficiency of the algorithm developed, the alignment of the image is altered and algorithm is tested for better performance. Also the work involves the comparison of two similarity metrics, and based on the outcome the best metric suited for genetic algorithm is studied.