A Comparison of Methods for Automated Motion Correction of DCE-MRI Perfusion Datasets Evaluated in Terms of Diagnostic Accuracy: A CE-MARC sub-study (2014)
Type of ContentJournal Article
PublisherUniversity of Canterbury. UC High Performance Computing
Automated mage registration in cardiac myocardial perfusion is a necessity before quantitative perfusion can be widely accepted in clinical practice. Increasingly complex motion correction algorithms are being developed to deal with cardiac motion. However, the impact of these improvements has not been evaluated in terms of the final clinical diagnosis. Advanced motion correction methods are associated with increased computational overhead and the potential of introducing subtle registration errors, which can be hard to detect and quantify. The aim of this study was to compare the performance of the various automated correction methods in terms of their impact on diagnostic accuracy.
CitationZakkaroff, C., Radjenovic, A., Biglands, J. D., Plein, S., Greenwood, J. P., &Magee, D. R. (2014) A Comparison of Methods for Automated Motion Correction of DCE-MRI Perfusion Datasets Evaluated in Terms of Diagnostic Accuracy: A CE-MARC sub-study. Journal of Cardiovascular Magnetic Resonance.
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ANZSRC Fields of Research32 - Biomedical and clinical sciences::3201 - Cardiovascular medicine and haematology::320101 - Cardiology (incl. cardiovascular diseases)
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