P. Santago, K. Link, W. Snyder, S. Rajala, J. Worley, Youn-Sik Han
{"title":"心脏磁共振图像的恢复","authors":"P. Santago, K. Link, W. Snyder, S. Rajala, J. Worley, Youn-Sik Han","doi":"10.1109/CBMSYS.1990.109379","DOIUrl":null,"url":null,"abstract":"Motion artifacts due to heart motion and blood flow within the heart chambers are a significant barrier to accurate interpretation of cardiac magnetic resonance images (MRI). The post-processing techniques of Wiener filtering, alternating projections onto convex sets (POCS), and mean field annealing (MFA) to remove these artifacts are studied. Removal of noise from the images is accomplished with MFA by setting up a restoration problem whose objective function encapsulates both data-dependent and a priori knowledge about the image. Two important aspects of MFA are the use of a penalty rather than a constraint, and the fact that it converges twenty times as rapidly as normal simulated annealing. Images of the results of Wiener filtering and MFA are shown, and the methods of POCS and MFA are briefly explained.<<ETX>>","PeriodicalId":365366,"journal":{"name":"[1990] Proceedings. Third Annual IEEE Symposium on Computer-Based Medical Systems","volume":"137 9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Restoration of cardiac magnetic resonance images\",\"authors\":\"P. Santago, K. Link, W. Snyder, S. Rajala, J. Worley, Youn-Sik Han\",\"doi\":\"10.1109/CBMSYS.1990.109379\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Motion artifacts due to heart motion and blood flow within the heart chambers are a significant barrier to accurate interpretation of cardiac magnetic resonance images (MRI). The post-processing techniques of Wiener filtering, alternating projections onto convex sets (POCS), and mean field annealing (MFA) to remove these artifacts are studied. Removal of noise from the images is accomplished with MFA by setting up a restoration problem whose objective function encapsulates both data-dependent and a priori knowledge about the image. Two important aspects of MFA are the use of a penalty rather than a constraint, and the fact that it converges twenty times as rapidly as normal simulated annealing. Images of the results of Wiener filtering and MFA are shown, and the methods of POCS and MFA are briefly explained.<<ETX>>\",\"PeriodicalId\":365366,\"journal\":{\"name\":\"[1990] Proceedings. Third Annual IEEE Symposium on Computer-Based Medical Systems\",\"volume\":\"137 9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1990] Proceedings. Third Annual IEEE Symposium on Computer-Based Medical Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CBMSYS.1990.109379\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1990] Proceedings. Third Annual IEEE Symposium on Computer-Based Medical Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMSYS.1990.109379","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Motion artifacts due to heart motion and blood flow within the heart chambers are a significant barrier to accurate interpretation of cardiac magnetic resonance images (MRI). The post-processing techniques of Wiener filtering, alternating projections onto convex sets (POCS), and mean field annealing (MFA) to remove these artifacts are studied. Removal of noise from the images is accomplished with MFA by setting up a restoration problem whose objective function encapsulates both data-dependent and a priori knowledge about the image. Two important aspects of MFA are the use of a penalty rather than a constraint, and the fact that it converges twenty times as rapidly as normal simulated annealing. Images of the results of Wiener filtering and MFA are shown, and the methods of POCS and MFA are briefly explained.<>