An autofocus algorithm for the automatic correction of motion artifacts in MR images

Atkinson, David; Hill, Derek L. G.; Stoyle, P. N. R.; Summers, Paul; Keevil, Steven F.

doi:10.1007/3-540-63046-5_26

Cited by 9 publications

(8 citation statements)

References 21 publications

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“…A number of approaches have been developed to address intra-volume motion and can be split into two broad categories: retrospective motion correction (RMC) techniques that are applied via post-processing of the acquired data and prospective motion correction (PMC) techniques that monitor and correct for motion at the time of acquisition. RMC approaches based on auto-focusing (Atkinson et al, 1997a , b , 1999 ; Batchelor et al, 2005 ; Cheng et al, 2012 ) have the potential to greatly improve image quality but they also have a number of drawbacks. Estimating the motion trajectory from large raw k-space data sets requires significant computational effort.…”

Section: Introductionmentioning

confidence: 99%

An evaluation of prospective motion correction (PMC) for high resolution quantitative MRI

et al. 2015

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Quantitative imaging aims to provide in vivo neuroimaging biomarkers with high research and diagnostic value that are sensitive to underlying tissue microstructure. In order to use these data to examine intra-cortical differences or to define boundaries between different myelo-architectural areas, high resolution data are required. The quality of such measurements is degraded in the presence of motion hindering insight into brain microstructure. Correction schemes are therefore vital for high resolution, whole brain coverage approaches that have long acquisition times and greater sensitivity to motion. Here we evaluate the use of prospective motion correction (PMC) via an optical tracking system to counter intra-scan motion in a high resolution (800 μm isotropic) multi-parameter mapping (MPM) protocol. Data were acquired on six volunteers using a 2 × 2 factorial design permuting the following conditions: PMC on/off and motion/no motion. In the presence of head motion, PMC-based motion correction considerably improved the quality of the maps as reflected by fewer visible artifacts and improved consistency. The precision of the maps, parameterized through the coefficient of variation in cortical sub-regions, showed improvements of 11–25% in the presence of deliberate head motion. Importantly, in the absence of motion the PMC system did not introduce extraneous artifacts into the quantitative maps. The PMC system based on optical tracking offers a robust approach to minimizing motion artifacts in quantitative anatomical imaging without extending scan times. Such a robust motion correction scheme is crucial in order to achieve the ultra-high resolution required of quantitative imaging for cutting edge in vivo histology applications.

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Section: Introductionmentioning

confidence: 99%

An evaluation of prospective motion correction (PMC) for high resolution quantitative MRI

et al. 2015

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“…For other systems, typically nano-CT, where mechanical instabilities are an issue, the reprojection method introduced by Mayo et al 4 could be used to refine the time dependant misalignments after the best average misalignment has been found using the proposed method. Alternatively, methods to correct for patient movement could be adapted to apply to source drift in micro-CT. For example, Atkinson et al 5,6 presented a method in the field of nuclear magnetic resonance imaging that parameterized the trajectory of a patient over the acquisition time in order to find the set of parameter values that minimize the entropy of the reconstruction.…”

Section: Introductionmentioning

confidence: 99%

Reliable automatic alignment of tomographic projection data by passive auto‐focus

et al. 2011

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“…Data with SI motion estimation falling outside the interval calculated as mean ± 2 times SD are considered outliers because of deep breathing and are removed. The so‐obtained translational respiratory motion corrected acquisition is rescaled exploiting a gradient entropy autofocusing technique, to account for any errors in translational motion estimation because of reduced contrast in the even data sets. The estimated SI displacement is used to bin the acquired data into different respiratory positions within the breathing cycle.…”

Section: Methodsmentioning

confidence: 99%

Simultaneous 3D whole‐heart bright‐blood and black blood imaging for cardiovascular anatomy and wall assessment with interleaved T₂prep‐IR

Milotta

Ginami

Cruz

et al. 2019

Magnetic Resonance in Med

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CorrespondenceGiorgia Milotta, School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital (3rd Floor, Lambeth Wing), Westminster Bridge Rd, Purpose: To develop a motion-corrected 3D flow-insensitive imaging approach interleaved T 2 prepared-inversion recovery (iT 2 prep-IR) for simultaneous lumen and wall visualization of the great thoracic vessels and cardiac structures. Methods: A 3D flow-insensitive approach for simultaneous cardiovascular lumen and wall visualization (iT 2 prep) has been previously proposed. This approach requires subject-dependent weighted subtraction to completely null the arterial blood signal in the black-blood volume. Here, we propose an (T 2 prep-IR) approach to improve wall visualization and remove need for weighted subtraction. The proposed sequence is based on the acquisition and direct subtraction of 2 interleaved 3D whole-heart data sets acquired with and without T 2 prep-IR preparation. Image navigators are acquired before data acquisition to enable 2D translational and 3D non-rigid motion correction allowing 100% respiratory scan efficiency. The proposed approach was evaluated in 10 healthy subjects and compared with the conventional 2D double inversion recovery (DIR) sequence and the 3D iT 2 prep sequence.Additionally, 5 patients with congenital heart disease were acquired to test the clinical feasibility of the proposed approach. Results: The proposed iT 2 prep-IR sequence showed improved blood nulling compared to both DIR and iT 2 prep techniques in terms of SNR (SNR blood = 6.9, 12.2, and 18.2, respectively) and contrast-to-noise-ratio 15.4, and 15.3, respectively). No statistical difference was observed between iT 2 prep-IR, iT 2 prep and DIR atrial and ventricular wall thickness quantification. Conclusion: The proposed interleaved T 2 prep-IR sequence enables the simultaneous lumen and wall visualization of cardiac structures and shows promising results in terms of SNR, CNR, and wall thickness measurement. K E Y W O R D S3D whole-heart, black-blood atrial wall, black-blood vessel wall, bright-blood cardiac anatomy, interleaved T 2 prep-IR, respiratory motion correction

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An autofocus algorithm for the automatic correction of motion artifacts in MR images

Cited by 9 publications

References 21 publications

An evaluation of prospective motion correction (PMC) for high resolution quantitative MRI

An evaluation of prospective motion correction (PMC) for high resolution quantitative MRI

Reliable automatic alignment of tomographic projection data by passive auto‐focus

Simultaneous 3D whole‐heart bright‐blood and black blood imaging for cardiovascular anatomy and wall assessment with interleaved T₂prep‐IR

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An autofocus algorithm for the automatic correction of motion artifacts in MR images

Cited by 9 publications

References 21 publications

An evaluation of prospective motion correction (PMC) for high resolution quantitative MRI

An evaluation of prospective motion correction (PMC) for high resolution quantitative MRI

Reliable automatic alignment of tomographic projection data by passive auto‐focus

Simultaneous 3D whole‐heart bright‐blood and black blood imaging for cardiovascular anatomy and wall assessment with interleaved T2prep‐IR

Contact Info

Product

Resources

About

Simultaneous 3D whole‐heart bright‐blood and black blood imaging for cardiovascular anatomy and wall assessment with interleaved T₂prep‐IR