Multi-sequence Registration of Cine, Tagged and Delay-Enhancement MRI with Shift Correction and Steerable Pyramid-Based Detagging

Authors:
Oscar Camara;Estanislao Oubel;Gemma Piella;Simone Balocco;Mathieu Craene;Alejandro Frangi
Affiliations:
Center for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), Universitat Pompeu Fabra (UPF) and Networking Biomedical Research Center on Bioengineering, Biomaterials and N ...;Center for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), Universitat Pompeu Fabra (UPF) and Networking Biomedical Research Center on Bioengineering, Biomaterials and N ...;Center for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), Universitat Pompeu Fabra (UPF) and Networking Biomedical Research Center on Bioengineering, Biomaterials and N ...;Center for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), Universitat Pompeu Fabra (UPF) and Networking Biomedical Research Center on Bioengineering, Biomaterials and N ...;Center for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), Universitat Pompeu Fabra (UPF) and Networking Biomedical Research Center on Bioengineering, Biomaterials and N ...;Center for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), Universitat Pompeu Fabra (UPF) and Networking Biomedical Research Center on Bioengineering, Biomaterials and N ...
Venue:
FIMH '09 Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart
Year:
2009

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Abstract

In this work, we present a registration framework for cardiac cine MRI (cMRI), tagged (tMRI) and delay-enhancement MRI (deMRI), where the two main issues to find an accurate alignment between these images have been taking into account: the presence of tags in tMRI and respiration artifacts in all sequences. A steerable pyramid image decomposition has been used for detagging purposes since it is suitable to extract high-order oriented structures by directional adaptive filtering. Shift correction of cMRI is achieved by firstly maximizing the similarity between the Long Axis and Short Axis cMRI. Subsequently, these shift-corrected images are used as target images in a rigid registration procedure with their corresponding tMRI/deMRI in order to correct their shift. The proposed registration framework has been evaluated by 840 registration tests, considerably improving the alignment of the MR images (mean RMS error of 2.04mm vs. 5.44mm).