An embedded optical tracking system for motion-corrected magnetic resonance imaging at 7T

Schulz, Jessica; Siegert, Thomas; Reimer, Enrico; Labadie, Christian; Maclaren, Julian; Herbst, M.; Zaitsev, Maxim; Turner, Robert

doi:10.1007/s10334-012-0320-0

Cited by 95 publications

(97 citation statements)

References 25 publications

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“…8A are likely expained by motion artifacts. Such problems can be avoided by employing 3D acquisition schemes [41] or by integrating perspective motion-correction strategies [42].…”

Section: Mt Experiments In Normal Human Brainmentioning

confidence: 99%

Matrix-algebra-based calculations of the time evolution of the binary spin-bath model for magnetization transfer

Müller¹,

Pampel²,

Möller³

2013

Journal of Magnetic Resonance

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“…8A are likely expained by motion artifacts. Such problems can be avoided by employing 3D acquisition schemes [41] or by integrating perspective motion-correction strategies [42].…”

Section: Mt Experiments In Normal Human Brainmentioning

confidence: 99%

Matrix-algebra-based calculations of the time evolution of the binary spin-bath model for magnetization transfer

Müller¹,

Pampel²,

Möller³

2013

Journal of Magnetic Resonance

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“…Particularly, impressive accuracy has been reported for optical tracking procedures [24]. In this regard, we should recall that our technique admits a straightforward combination with these sort of approaches.…”

Section: Discussionmentioning

confidence: 93%

Sensitivity Encoding for Aligned Multishot Magnetic Resonance Reconstruction

Cordero‐Grande

Teixeira

Hughes

et al. 2016

IEEE Trans. Comput. Imaging

155

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This paper introduces a framework for the reconstruction of magnetic resonance images in the presence of rigid motion. The rationale behind our proposal is to make use of the partial k-space information provided by multiple receiver coils in order to estimate the position of the imaged object throughout the shots that contribute to the image. The estimated motion is incorporated into the reconstruction model in an iterative manner to obtain a motion-free image. The method is parameter-free, does not assume any prior model for the image to be reconstructed, avoids blurred images due to resampling, does not make use of external sensors, and does not require modifications in the acquisition sequence. Validation is performed using synthetically corrupted data to study the limits for full motion-recovered reconstruction in terms of the amount of motion, encoding trajectories, number of shots and availability of prior information, and to compare with the state of the art. Quantitative and visual results of its application to a highly challenging volumetric brain imaging cohort of 207 neonates are also presented, showing the ability of the proposed reconstruction to generally improve the quality of reconstructed images, as evaluated by both sparsity and gradient entropy based metrics.

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“…Subtle motion artifacts are difficult to evaluate and quantify objectively. High-resolution imaging, which also entails longer scan times, would greatly benefit from prospective motion correction to prevent the occurrence of such artifacts (Schulz et al, 2012;Maclaren et al, 2013).…”

Section: Challengesmentioning

confidence: 99%

A subject-specific framework for in vivo myeloarchitectonic analysis using high resolution quantitative MRI

et al. 2016

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An embedded optical tracking system for motion-corrected magnetic resonance imaging at 7T

Abstract: Using a novel method for validating the effectiveness of in vivo prospective motion correction, we have demonstrated that prospective motion correction using motion data from the embedded tracking system considerably improved image quality.

Cited by 95 publications

References 25 publications

Matrix-algebra-based calculations of the time evolution of the binary spin-bath model for magnetization transfer

Matrix-algebra-based calculations of the time evolution of the binary spin-bath model for magnetization transfer

Sensitivity Encoding for Aligned Multishot Magnetic Resonance Reconstruction

A subject-specific framework for in vivo myeloarchitectonic analysis using high resolution quantitative MRI

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