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  Blind Retrospective Motion Correction of MR Images

Loktyuschin, A., Nickisch, H., Pohmann, R., & Schölkopf, B. (2013). Blind Retrospective Motion Correction of MR Images. Magnetic Resonance in Medicine, 70(6), 1608-1618. doi:10.1002/mrm.24615.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-001A-122A-E Version Permalink: http://hdl.handle.net/21.11116/0000-0001-1875-1
Genre: Journal Article

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Loktyuschin, A1, Author
Nickisch, H, Author              
Pohmann, R2, 3, Author              
Schölkopf, B1, Author              
Affiliations:
1Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              
2Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497796              
3Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: 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.

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 Dates: 2013-12
 Publication Status: Published in print
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 Identifiers: DOI: 10.1002/mrm.24615
BibTex Citekey: LoktyuschinNPS2013
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Title: Magnetic Resonance in Medicine
Source Genre: Journal
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Pages: - Volume / Issue: 70 (6) Sequence Number: - Start / End Page: 1608 - 1618 Identifier: -