Y. Farouj, Liang Wang, P. Clarysse, L. Navarro, M. Clausel, P. Delachartre
{"title":"Cardiac motion analysis using wavelet projections from tagged MR sequences","authors":"Y. Farouj, Liang Wang, P. Clarysse, L. Navarro, M. Clausel, P. Delachartre","doi":"10.1109/ICIP.2014.7025037","DOIUrl":null,"url":null,"abstract":"We present an optical flow technique in a differential projected framework adapted to local myocardial motion estimation from MR Tagged images. The algorithm is based on the Dual Tree design of Hilbert transform pairs of wavelet bases. Such a design allows one to construct several orientation-sensitive wavelet filters for better analysis of the complex motion of the heart. The complex wavelet transform (CWT) integrates both energy and phase information in the wavelets coefficients for an effective motion estimation. The CWT also provides a high frequency analysis and enjoys a multiresolution aspect that allows multiscale flow estimate. Performances of the algorithm are evaluated on synthetic tagged MRI sequences for both displacement and strain estimation.","PeriodicalId":6856,"journal":{"name":"2014 IEEE International Conference on Image Processing (ICIP)","volume":"203 1","pages":"189-193"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Image Processing (ICIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2014.7025037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
We present an optical flow technique in a differential projected framework adapted to local myocardial motion estimation from MR Tagged images. The algorithm is based on the Dual Tree design of Hilbert transform pairs of wavelet bases. Such a design allows one to construct several orientation-sensitive wavelet filters for better analysis of the complex motion of the heart. The complex wavelet transform (CWT) integrates both energy and phase information in the wavelets coefficients for an effective motion estimation. The CWT also provides a high frequency analysis and enjoys a multiresolution aspect that allows multiscale flow estimate. Performances of the algorithm are evaluated on synthetic tagged MRI sequences for both displacement and strain estimation.
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