{"title":"Registration of dynamic renal MR images using neurobiological model of saliency","authors":"D. Mahapatra, Ying Sun","doi":"10.1109/ISBI.2008.4541197","DOIUrl":null,"url":null,"abstract":"In this paper we propose the use of a neurobiology-based saliency measure to improve the performance of a quantitative- qualitative measure of mutual information for rigid registration of 4D renal perfusion MR images. Our registration method assigns greater importance to more salient voxels by applying a soft thresholding function to normalized saliency values. The resulting saliency map is a better representation of what is truly visually salient than an entropy-based saliency map. Our tests on real patient datasets show that incorporating this saliency measure produces better registration results than traditional entropy-based approaches.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"199 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"43","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBI.2008.4541197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 43
Abstract
In this paper we propose the use of a neurobiology-based saliency measure to improve the performance of a quantitative- qualitative measure of mutual information for rigid registration of 4D renal perfusion MR images. Our registration method assigns greater importance to more salient voxels by applying a soft thresholding function to normalized saliency values. The resulting saliency map is a better representation of what is truly visually salient than an entropy-based saliency map. Our tests on real patient datasets show that incorporating this saliency measure produces better registration results than traditional entropy-based approaches.