Fast method for correcting image misregistration due to organ motion in time-series MRI data.
Time-series MRI data often suffers from image misalignment due to patient movement and respiratory and other physiologic motion during the acquisition process. It is necessary that this misalignment be corrected prior to any automated quantitative analysis. In this article a fast and automated technique for removing in-plane misalignment from time-series MRI data is presented. The method is computationally efficient, robust, and fine-tuned for the clinical setting. The method was implemented and tested on data from 21 human subjects, including myocardial perfusion imaging, renal perfusion imaging, and blood-oxygen level-dependent cardiac T(2*) imaging. In these applications 10-fold or better reduction in image misalignment is reported. The improvement after registration on representative time-intensity curves is shown. Although the method currently corrects translation motion using image center of mass, the mathematical framework of our approach may be extended to correct rotation and other higher-order displacements.
Gupta
Sandeep N
SN
Applied Sciences Laboratory, GE Medical Systems, Baltimore, Maryland 21287, USA. Sandeep.Gupta@med.ge.com
Solaiyappan
Meiyappan
M
Beache
Garth M
GM
Arai
Andrew E
AE
Foo
Thomas K F
TK
D000465:Algorithms; D006321:Heart / Q000502:physiology*; D006801:Humans; D007668:Kidney / Q000502:physiology*; D018810:Magnetic Resonance Angiography / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009068:Movement / Q000502:physiology; D010477:Perfusion; D012815:Signal Processing, Computer-Assisted