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Blind retrospective motion correction of MR images
Author(s) -
Loktyushin Alexander,
Nickisch Hannes,
Pohmann Rolf,
Schölkopf Bernhard
Publication year - 2013
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.24615
Subject(s) - computer vision , computer science , artificial intelligence , motion estimation , ghosting , motion (physics) , trajectory , match moving , quarter pixel motion , motion field , physics , astronomy
Purpose Subject motion can severely degrade MR images. A retrospective motion correction algorithm, Gradient‐based motion correction, which significantly reduces ghosting and blurring artifacts due to subject motion was proposed. The technique uses the raw data of standard imaging sequences; no sequence modifications or additional equipment such as tracking devices are required. Rigid motion is assumed. Methods The approach iteratively searches for the motion trajectory yielding the sharpest image as measured by the entropy of spatial gradients. The vast space of motion parameters is efficiently explored by gradient‐based optimization with a convergence guarantee. Results The method has been evaluated on both synthetic and real data in two and three dimentions using standard imaging techniques. MR images are consistently improved over different kinds of motion trajectories. Using a graphics processing unit implementation, computation times are in the order of a few minutes for a full three‐dimentional volume. Conclusion The presented technique can be an alternative or a complement to prospective motion correction methods and is able to improve images with strong motion artifacts from standard imaging sequences without requiring additional data. Magn Reson Med 70:1608–1618, 2013. © 2013 Wiley Periodicals, Inc.