Melvyn B. Ooi

Echo‐planar imaging with prospective slice‐by‐slice motion correction using active markers

Head motion is a fundamental problem in functional magnetic resonance imaging and is often a limiting factor in its clinical implementation. This work presents a rigid‐body motion correction strategy for echo‐planar imaging sequences that uses micro radiofrequency coil “active markers” for real‐time, slice‐by‐slice prospective correction. Before the acquisition of each echo‐planar imaging‐slice, a short tracking pulse‐sequence measures the positions of three active markers integrated into a headband worn by the subject; the rigid‐body transformation that realigns these markers to their initial positions is then fed back to dynamically update the scan‐plane, maintaining it at a fixed orientation relative to the head. Using this method, prospectively‐corrected echo‐planar imaging time series are acquired on volunteers performing in‐plane and through‐plane head motions, with results demonstrating increased image stability over conventional retrospective image‐realignment. The benefit of this improved image stability is assessed in a blood oxygenation level dependent functional magnetic resonance imaging application. Finally, a non‐rigid‐body distortion‐correction algorithm is introduced to reduce the remaining signal variation. Magn Reson Med, 2011.

Combined prospective and retrospective correction to reduce motion-induced image misalignment and geometric distortions in EPI.

Despite rigid‐body realignment to compensate for head motion during an echo‐planar imaging time‐series scan, nonrigid image deformations remain due to changes in the effective shim within the brain as the head moves through the B0 field. The current work presents a combined prospective/retrospective solution to reduce both rigid and nonrigid components of this motion‐related image misalignment. Prospective rigid‐body correction, where the scan‐plane orientation is dynamically updated to track with the subjects head, is performed using an active marker setup. Retrospective distortion correction is then applied to unwarp the remaining nonrigid image deformations caused by motion‐induced field changes. Distortion correction relative to a reference time‐frame does not require any additional field mapping scans or models, but rather uses the phase information from the echo‐planar imaging time‐series itself. This combined method is applied to compensate echo‐planar imaging scans of volunteers performing in‐plane and through‐plane head motions, resulting in increased image stability beyond what either prospective or retrospective rigid‐body correction alone can achieve. The combined method is also assessed in a blood oxygen level dependent functional MRI task, resulting in improved Z‐score statistics. Magn Reson Med, 2013.

Prospective Motion Correction Using Inductively Coupled Wireless RF Coils

A novel prospective motion correction technique for brain MRI is presented that uses miniature wireless radio‐frequency coils, or “wireless markers,” for position tracking.

Diffusion tensor imaging (DTI) with retrospective motion correction for large-scale pediatric imaging

To develop and implement a clinical DTI technique suitable for the pediatric setting that retrospectively corrects for large motion without the need for rescanning and/or reacquisition strategies, and to deliver high‐quality DTI images (both in the presence and absence of large motion) using procedures that reduce image noise and artifacts.

Prospective active marker motion correction improves statistical power in BOLD fMRI

Group level statistical maps of blood oxygenation level dependent (BOLD) signals acquired using functional magnetic resonance imaging (fMRI) have become a basic measurement for much of systems, cognitive and social neuroscience. A challenge in making inferences from these statistical maps is the noise and potential confounds that arise from the head motion that occurs within and between acquisition volumes. This motion results in the scan plane being misaligned during acquisition, ultimately leading to reduced statistical power when maps are constructed at the group level. In most cases, an attempt is made to correct for this motion through the use of retrospective analysis methods. In this paper, we use a prospective active marker motion correction (PRAMMO) system that uses radio frequency markers for real-time tracking of motion, enabling on-line slice plane correction. We show that the statistical power of the activation maps is substantially increased using PRAMMO compared to conventional retrospective correction. Analysis of our results indicates that the PRAMMO acquisition reduces the variance without decreasing the signal component of the BOLD (beta). Using PRAMMO could thus improve the overall statistical power of fMRI based BOLD measurements, leading to stronger inferences of the nature of processing in the human brain.

Prospective motion correction using coil‐mounted cameras: Cross‐calibration considerations

Optical prospective motion correction substantially reduces sensitivity to motion in neuroimaging of human subjects. However, a major barrier to clinical deployment has been the time‐consuming cross‐calibration between the camera and MRI scanner reference frames. This work addresses this challenge.

Optical motion tracking to improve image quality in MRI of the brain

Magnetic resonance imaging (MRI) of the brain is highly sensitivity to head motion. Prospective motion correction is a promising new method to prevent artifacts resulting from this effect. The image volume is continuously updated based on head tracking information, ensuring that the magnetic fields used for imaging maintain a constant geometric relationship relative to the object. This paper reviews current developments and methods of performing prospective correction. Optical tracking using cameras has major advantages over other methods used to obtain head pose information, as it does not affect the MR imaging process or interfere with the sequence timing. Results show that motion artifacts can be almost completely prevented for most imaging sequences. Despite this success, there are still engineering challenges to be solved before the technique becomes widely accepted in the clinic. These include improvements in miniaturization, marker fixation and MR compatibility.