{"title":"心脏MRI图像去噪技术的性能评价","authors":"M. A. Alattar, A. Motaal, N. Osman, A. Fahmy","doi":"10.1109/CIBEC.2008.4786055","DOIUrl":null,"url":null,"abstract":"Black-blood cardiac magnetic resonance imaging (MRI) plays an important role in diagnosing a number of heart diseases. The technique suffers inherently from low contrast-to-noise ratio between the myocardium and the blood. In this work, we examined the performance of different classification techniques that can be used. The three techniques successfully removed the noise with different performance. Numerical simulation has been done to quantitatively evaluate the performance of each technique.","PeriodicalId":319971,"journal":{"name":"2008 Cairo International Biomedical Engineering Conference","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Performance Evaluation of Cardiac MRI Image Denoising Techniques\",\"authors\":\"M. A. Alattar, A. Motaal, N. Osman, A. Fahmy\",\"doi\":\"10.1109/CIBEC.2008.4786055\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Black-blood cardiac magnetic resonance imaging (MRI) plays an important role in diagnosing a number of heart diseases. The technique suffers inherently from low contrast-to-noise ratio between the myocardium and the blood. In this work, we examined the performance of different classification techniques that can be used. The three techniques successfully removed the noise with different performance. Numerical simulation has been done to quantitatively evaluate the performance of each technique.\",\"PeriodicalId\":319971,\"journal\":{\"name\":\"2008 Cairo International Biomedical Engineering Conference\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Cairo International Biomedical Engineering Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIBEC.2008.4786055\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Cairo International Biomedical Engineering Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIBEC.2008.4786055","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance Evaluation of Cardiac MRI Image Denoising Techniques
Black-blood cardiac magnetic resonance imaging (MRI) plays an important role in diagnosing a number of heart diseases. The technique suffers inherently from low contrast-to-noise ratio between the myocardium and the blood. In this work, we examined the performance of different classification techniques that can be used. The three techniques successfully removed the noise with different performance. Numerical simulation has been done to quantitatively evaluate the performance of each technique.
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