{"title":"基于正则化的计算机断层扫描同步代数重建技术","authors":"Shailendra Tiwari, Deepikanshu Chouksey, Vinod Todwal","doi":"10.1109/IC3.2016.7880219","DOIUrl":null,"url":null,"abstract":"Simultaneous algebraic reconstruction Technique(SART) based iterative method play a major role in the quality of images reconstructed by Computed Tomography (CT). The basic limitations associated with this method include poor visual quality and ill-posedness. To address these drawbacks, SART iterative method is modified using Anisotropic Diffusion (AD) as regularization prior to tackle with ill-posedness as well as visual quality issue. To evaluate the proposed method, both qualitative and quantitative studies were conducted and results were compared with existing methods using two different simulated test phantoms. Experimental results show that the proposed model yields significant gain in terms of visual reconstructed image quality and noise suppression.","PeriodicalId":294210,"journal":{"name":"2016 Ninth International Conference on Contemporary Computing (IC3)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Regularization based simultaneous algebraic reconstruction techniques for computed tomography\",\"authors\":\"Shailendra Tiwari, Deepikanshu Chouksey, Vinod Todwal\",\"doi\":\"10.1109/IC3.2016.7880219\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Simultaneous algebraic reconstruction Technique(SART) based iterative method play a major role in the quality of images reconstructed by Computed Tomography (CT). The basic limitations associated with this method include poor visual quality and ill-posedness. To address these drawbacks, SART iterative method is modified using Anisotropic Diffusion (AD) as regularization prior to tackle with ill-posedness as well as visual quality issue. To evaluate the proposed method, both qualitative and quantitative studies were conducted and results were compared with existing methods using two different simulated test phantoms. Experimental results show that the proposed model yields significant gain in terms of visual reconstructed image quality and noise suppression.\",\"PeriodicalId\":294210,\"journal\":{\"name\":\"2016 Ninth International Conference on Contemporary Computing (IC3)\",\"volume\":\"70 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Ninth International Conference on Contemporary Computing (IC3)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IC3.2016.7880219\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Ninth International Conference on Contemporary Computing (IC3)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3.2016.7880219","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Regularization based simultaneous algebraic reconstruction techniques for computed tomography
Simultaneous algebraic reconstruction Technique(SART) based iterative method play a major role in the quality of images reconstructed by Computed Tomography (CT). The basic limitations associated with this method include poor visual quality and ill-posedness. To address these drawbacks, SART iterative method is modified using Anisotropic Diffusion (AD) as regularization prior to tackle with ill-posedness as well as visual quality issue. To evaluate the proposed method, both qualitative and quantitative studies were conducted and results were compared with existing methods using two different simulated test phantoms. Experimental results show that the proposed model yields significant gain in terms of visual reconstructed image quality and noise suppression.