Abstract:
PURPOSE:In this study, an iterative k-t principal component analysis (PCA) algorithm with nonrigid frame-to-frame motion correction is proposed for dynamic contrast-enhanced three-dimensional perfusion imaging. METHODS:An iterative k-t PCA algorithm was implemented with regularization using training data corrected for frame-to-frame motion in the x-pc domain. Motion information was extracted using shape-constrained nonrigid image registration of the composite of training and k-t undersampled data. The approach was tested for 10-fold k-t undersampling using computer simulations and in vivo data sets corrupted by respiratory motion artifacts owing to free-breathing or interrupted breath-holds. Results were compared to breath-held reference data. RESULTS:Motion-corrected k-t PCA image reconstruction resolved residual aliasing. Signal intensity curves extracted from the myocardium were close to those obtained from the breath-held reference. Upslopes were found to be more homogeneous in space when using the k-t PCA approach with motion correction. CONCLUSIONS:Iterative k-t PCA with nonrigid motion correction permits correction of respiratory motion artifacts in three-dimensional first-pass myocardial perfusion imaging.
journal_name
Magn Reson Medjournal_title
Magnetic resonance in medicineauthors
Schmidt JF,Wissmann L,Manka R,Kozerke Sdoi
10.1002/mrm.24894subject
Has Abstractpub_date
2014-07-01 00:00:00pages
68-79issue
1eissn
0740-3194issn
1522-2594journal_volume
72pub_type
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