Highly Efficient Respiratory Gating in Whole Heart MR Employing Non-Rigid Retrospective Motion Correction
Johannes F M Schmidt¹, Martin Buehrer¹, Peter Boesiger¹, Sebastian Kozerke^1
1Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland

Respiratory motion artifacts in coronary MR scans were retrospectively corrected using a non-rigid motion model acquired interleaved during the sequence pauses in each heart cycle. Gating efficiency could be doubled without loss in image quality.

High Temporal Resolution Radial Motion Correction with GROWL
Wei Lin¹, Feng Huang¹, Yu Li¹, Arne Reykowski^1
1Advanced Concepts Development, Invivo Corporation, Philips Healthcare, Gainesville, FL, United States

The self-navigating property of radial imaging has been exploited in various motion correction methods. However, there is always a tradeoff between the robustness and temporal resolution of motion correction. In this work, a recently proposed rapid parallel imaging method, GRAPPA operator for wider radial bands (GROWL), is applied to increase the temporal resolution of motion correction in multi-coil radial imaging applications. It is demonstrated that robust in-plane rotation/translation motion detection and correction can be achieved with as few as 8 radial views using an 8-channel coil.

Robust 3-D Motion Correction for Spiral Projection Imaging
Kenneth Otho Johnson¹, James Grant Pipe^1
1Barrow Neurological Institute, Phoenix, AZ, United States

Using spiral planes to fill a 3-D sphere, the motion incurred during a scan can be deduced based on the geometry of how the planes overlap. A new physically based solver is tuned and used to provide robust accurate motion estimates across various scanning parameters that introduce rf coil bias, excessive off-resonance, and image space warping from gradient non-linearities. Estimates for expected accuracy of in-vivo scans are provided, which create a synthesis of multiple datasets, that are registered using an external program.

Robust ARC Parallel Imaging with 3D Prospective Motion Correction
Suchandrima Banerjee¹, Philip James Beatty¹, Jian Zhang², Eric T. Han¹, Ajit Shankaranarayanan^1
1Applied Science Laboratory, GE Healthcare, San Francisco, CA, United States; ²Electrical Engineering, Stanford University, Palo Alto, CA, United States

Recent trends in MRI have seen an increase in volumetric acquisitions. But three-dimensional (3D) scans are prone to motion artifacts because scan times are often long even after acceleration with parallel imaging and any motion affects the entire volume measurement. Prospective motion correction provides a robust method for suppressing motion artifacts, by tracking patient motion and adjusting scan coordinates to realign with the patient. This work investigates data-driven parallel imaging approaches that account for the k-space transformations associated with prospective motion correction.

Towards Combining Prospective Motion Correction and Distortion Correction for EPI
Rainer Boegle¹, Julian Maclaren¹, Maxim Zaitsev^1
1Dept. of Diagnostic Radiology, Medical Physics, University Hospital Freiburg, Freiburg, Baden-Württemberg, Germany

Subject head motion is a serious confound in fMRI, limiting its image quality and applicability. To lift this restriction for EPI based fMRI the combination of prospective motion correction with distortion correction based on field maps, calculated from the subject’s susceptibility distribution and pose, has been proposed. Here we present a proof-of-concept phantom study demonstrating the significance of motion dependent distortions in prospective motion correction and the feasibility of their correction via a field prediction method. Additionally comparative field simulations are shown, which suggest that a 'simple segmentation' of a human head would be sufficient for in vivo correction.

Improved Pose Detection for Single Camera Real-Time MR Motion Correction Using a Self-Encoded Marker
Christoph Forman¹, Murat Aksoy², Matus Straka², Joachim Hornegger¹, Roland Bammer^2
1Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany; ²Department of Radiology, Stanford University, Stanford, CA, United States

A new self-encoded marker for optical pose estimation has been developed. It was designed to cover a wider range of motion and allows to be combined with cameras with a smaller aperture. In this study, we measured accuracy and precision of this novel self-encoded marker on a precision pan-tilt unit and compared the results against similar measurements performed with a standard checkerboard marker. Comparative evaluations between the new self-encoded marker and the checkerboard marker were also performed in vivo and demonstrated superiority of the new marker approach.

A Parallel Computing Framework for Motion-Compensated Reconstruction Based on the Motion Point-Spread Function
Freddy Odille¹, Philip G. Batchelor², Claudia Prieto², Tobias Schaeffter², David Atkinson^1
1Centre for Medical Image Computing, University College London, London, United Kingdom; ²Division of Imaging Sciences, King's College London, London, United Kingdom

Generalized reconstruction algorithms have been proposed in order to correct for artifacts induced by nonrigid motion. However they are very time-consuming because large scale inverse problems have to be solved. Here we propose a technique for splitting the reconstruction into several smaller problems, based on the properties of the point-spread function associated with motion artifacts, which uses the local nature of artifacts (blurring) in the frequency-encoding direction. The method was implemented on a cluster of workstations, and applied to the correction of real motion-corrupted data. Efficient motion correction was achieved, with reconstruction times reduced by an order of magnitude.

Hybrid Prospective & Retrospective Head Motion Correction System to Mitigate Cross-Calibration Errors
Murat Aksoy¹, Christoph Forman^1,2, Matus Straka¹, Tolga Çukur³, Samantha Jane Holdsworth¹, Stefan Tor Skare^1,4, Juan Manuel Santos³, Joachim Hornegger², Roland Bammer^1
1Department of Radiology, Stanford University, Stanford, CA, United States; ²Computer Science, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany; ³Electrical Engineering, Stanford University, Stanford, CA, United States; ⁴Karolinska Institute, Stockholm, Sweden

Correction of motion artifacts in MRI is essential to assure diagnostic image quality. In case where external pose information is used for motion-correction, cross-calibration errors may impair image quality. In this study, we propose a combined prospective & retrospective approach to prospectively correct for motion and to mitigate residual image distortions which emanate from subtle cross-calibration errors. Specifically, a single camera mounted on the head coil was used to measure and correct patient motion in real-time. Resulting data inconsistencies – emanating primarily from cross-calibration errors – were removed by a retrospective autofocusing algorithm wherein k-space was divided into segments. The relative rotation and translation needed to realign these segments were determined by means of entropy-based autofocusing. Phantom and in-vivo results show that in the presence of inaccuracies in cross-calibration, the current method provides improved image quality over prospective motion correction only.

Spectroscopic Imaging with Prospective Motion Correction and Retrospective Phase Correction
Thomas Lange¹, Julian Maclaren¹, Martin Buechert¹, Maxim Zaitsev^1
1Dept. of Diagnostic Radiology, Medical Physics, University Hospital Freiburg, Freiburg, Germany

A method for prospective motion correction based on an optical tracking system has recently been proposed and has already been successfully applied to single voxel spectroscopy. In this work, the utility of prospective motion correction in combination with retrospective phase correction is evaluated for spectroscopic imaging in the human brain. Especially, the real-time adjustment of the outer volume suppression slabs appears to be crucial in vivo where lipid signal can drastically impair the spectral quality. The interleaved reference scan method is used to correct for motion-induced frequency drifts and to ensure correct phasing of the spectra across the whole slice.