Automated multi-modality registration of 64-slice coronary CT angiography with myocardial perfusion SPECT

Authors:
Jonghye Woo;Piotr J. Slomka;Damini Dey;Victor Cheng;Amit Ramesh;Byung-Woo Hong;Daniel S. Berman;C.-C. Jay Kuo;Guido Germano
Affiliations:
University of Southern California and Cedars-Sinai Medical Center, Los Angeles, CA;Cedars-Sinai Medical Center, Los Angeles, CA;Cedars-Sinai Medical Center, Los Angeles, CA;Cedars-Sinai Medical Center, Los Angeles, CA;Cedars-Sinai Medical Center, Los Angeles, CA;Chung-Ang University, Seoul, Korea;Cedars-Sinai Medical Center, Los Angeles, CA;University of Southern California, Los Angeles, CA;Cedars-Sinai Medical Center, Los Angeles, CA
Venue:
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Year:
2009

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Abstract

A multi-modality image registration algorithm for the alignment of myocardial perfusion SPECT (MPS) and coronary computed tomography angiography (CTA) scans is presented in this work. Coronary CTA and MPS provides clinically complementary information in the diagnosis of coronary artery disease. An automated registration algorithm is proposed utilizing segmentation results of MPS volumes, where regions of myocardium and blood pools are extracted and used as an anatomical mask. Using a variational framework, we adopt an energy functional with a piecewise constant image model and optimize it numerically with a gradient descent algorithm. The computational efficiency and robustness of the proposed automatic registration of CTA with MPS have been demonstrated by the experiments that yielded an average error smaller than a MPS voxel size.