Automatic compensation of motion artifacts in MRI

Atkinson, David; Hill, Derek L. G.; Stoyle, P. N. R.; Summers, Paul; Clare, Stuart; Bowtell, Richard; Keevil, Stephen

doi:10.1002/(sici)1522-2594(199901)41:1<163::aid-mrm23>3.3.co;2-0

Cited by 7 publications

(10 citation statements)

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“…Figure 9 demonstrates the variety in the types of motion correctable by periodically rotated overlapping parallel lines with enhanced reconstruction. Alternatively, for standard pulse sequences, an entropy mini mization criterion has been shown to compensate for bulk motion in standard pulse sequences [50]. Image-domain correction can also be performed using template tracking and low-order, piecewise motion models [51].…”

Section: System Limitations and Imperfectionsmentioning

confidence: 99%

MRI artifacts and correction strategies

Smith

Nayak

2010

Imaging in Medicine

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REVIEWDuring the 35 years since the first nuclear MRI scanners were made, MRI has become a powerful and widely used clinical imaging modality. MRI is frequently utilized in neurological, musculo skeletal and cardiovascular examinations owing to the excellent soft-tissue contrast and spatial resolution of its images. Owing to its unique sensitivity to a range of physio logical and biological parameters such as flow, chemical composition and molecular configuration, MRI is also well-suited for functional and metabolic studies. There is an enormous flexibility when selecting imaging parameters; tissue contrast, image resolution and anatomical coverage can all be optimized for each specific application. Both 2D and 3D images can be formed with no restrictions on the orientation of the imaging volume. Perhaps most importantly, because it does not rely on ionizing radiation, MRI is safe for serial examinations, dynamic (timeresolved) imaging studies and screening in asymptomatic subjects.The MRI signal is created by a combination of a strong magnetic field (called the B 0 field) typically generated by a superconductive coil, one or more radiofrequency (RF) fields, and several weak magnetic fields generated by three gradient coils. When a patient enters the scanner, the magnetic moments of protons within the body tend to align with the B 0 field. An RF pulse tuned to the nuclear magnetic resonance (NMR) frequency (which is determined by the strength of the B 0 field and the gyromagnetic ratio of the particular nuclei -typically hydrogen -being imaged) is transmitted, forcing the moments to oscillate at their resonant frequency [1]. This oscillation is detected by one or more receiver coils, demodulated and stored. Spatial encoding along three axes is performed by the gradient coils, which alter the magnetic field strength so that the resonance frequency varies linearly with position, permitting a Fourier-based inter pretation of the space-frequency relationship [2]. During the scan, the spatial frequency content, or k-space, of the imaging volume is sampled according to a chosen k-space trajectory, image field-of-view and resolution. To fully sample k-space, multiple data acquisitions are often required, each covering a segment of the spatial frequency support. Once the desired k-space data have been acquired, spatial decoding and image reconstruction are performed, typically by an inverse Fourier transform (FT) [3]. The echo time, which is the interval between the RF pulse and a data acquisition, and the repetition time (TR), which is the interval between sequential data acquisitions, are two important scan parameters that influence image contrast, signal-to-noise ratio (SNR) and other image features.As with any other imaging modality, MRI is vulnerable to artifacts. These arise because one or more of the assumptions upon which the imaging principles depend have been violated. Often, several different kinds of artifacts occur Artifacts appear in MRI for a variety of reasons. Potential sources of artifacts include nonid...

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Section: System Limitations and Imperfectionsmentioning

confidence: 99%

MRI artifacts and correction strategies

Smith

Nayak

2010

Imaging in Medicine

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“…Two sequence‐independent approaches for reducing motion artifacts are the prospective motion correction 4 (PMC) with external tracking devices 5‐7 and retrospective motion correction (RMC) 7 . The latter may rely either on additional motion information 8,9 or redundancies in the MRI raw data 10,11 …”

Section: Introductionmentioning

confidence: 99%

“…However, RMC has no means of adapting the k‐space trajectory, which remains constant in the device coordinate system, fixed at the beginning of the measurement. Therefore all rotations of the object during the measurement result in so‐called “pie‐slice” sampling artifacts, a term describing regions in the k‐space represented in object coordinates, where no data were acquired, leading to a violation of the Nyquist criterion 7,8,10,22 . Additionally, the majority of existing RMC techniques are based either on specific pulse sequences (eg, extended to acquire navigator data) or on specific trajectories with data redundancy providing intrinsic navigation information 7‐10,22‐24 …”

Section: Introductionmentioning

confidence: 99%

Combining prospective and retrospective motion correction based on a model for fast continuous motion

Hucker

Dacko

Zaitsev

2021

Magnetic Resonance in Med

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Purpose Prospective motion correction (PMC) and retrospective motion correction (RMC) have different advantages and limitations. The present work aims to combine the advantages of both for rigid body motion, aiming at correcting for faster motions than was previously achievable. Additionally, it provides insights into the effects of motion on pulse sequences and MR signals with a goal of further improving motion correction in the future. Methods The effective encoding trajectory and a global phase offset in a moving object are calculated based on complete gradient waveforms of an arbitrary sequence and a continuous motion model. These data are used to feed the forward signal model, which is then used in iterative image reconstruction to suppress the artifacts still present after the PMC. Results Verification experiments with a rotation phantom and in vivo were performed. Predictions of simulated motion artifacts for PMC based on sequence waveforms are very accurate. The performance at combined PMC+RMC is limited by Nyquist violations in the sampled k‐space and can be compensated by oversampling. Conclusion The combined correction results in better images than pure PMC in the presence of fast motion. The predictions of artifacts are very accurate, allowing for comparing sequences or protocols in simulations. The observed artifacts due to Nyquist violations are expected to be corrected by utilizing parallel imaging.

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“…This type of methods does not require special machines, and it just needs a good metric, which can measure the image quality. Aktinson et al [2,3] used the entropy criterion to determine the motions, and Lin et al [4] proposed to use the normalized gradient squared (NGS) measure [5] instead.…”

Section: Introductionmentioning

confidence: 99%

MRI motion artifact correction based on spectral extrapolation with generalized series

Lee

Lai

et al. 2010

2010 IEEE International Conference on Image Processing

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Motion artifact is a serious problem to MRI diagnosis and analysis due to periodic motion or patient motion during the image acquisition. A metric-based method, EXTRACT, used the information by using extrapolation of the k-space data and a metric based on correlation between the extrapolated k-space data and the motion corrupted k-space data. In this paper, we propose to use the finite support technique in conjunction with the generalized series in the spectral extrapolation to determine the motion that causes phase shift in the corrupted k-space data, thus improving the performance of MRI motion correction. Some experimental results are given to demonstrate the performance of the proposed algorithm.

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Automatic compensation of motion artifacts in MRI

Cited by 7 publications

References 0 publications

MRI artifacts and correction strategies

MRI artifacts and correction strategies

Combining prospective and retrospective motion correction based on a model for fast continuous motion

MRI motion artifact correction based on spectral extrapolation with generalized series

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