Rotational Motion Artifact Correction in Magnetic Resonance Imaging

The body motion of patients, during magnetic resonance (MR) imaging causes significant artifacts in the reconstructed image. Artifacts are manifested as a motion induced blur and ghost repetitions of the moving structures. which obscure vital anatomical and pathological detail. The techniques that have been proposed for suppressing motion artifacts fall into two major categories. Real-time techniques attempt to prevent the motion from corrupting the data by restricting the data acquisition times or motion of the patients, whereas the post-processing techniques use the information embedded in the corrupted data to restore the image. Most methods currently in widespread use belong to the real-time techniques, however with the advent of fast computing platforms and sophisticated signal processing algorithms, the emergence of post-processing techniques is clearly evident. The post-processing techniques usually demand an appropriate model of the motion. The restoration of the image requires that the motion parameters be determined in order to invert the data degradation process. Methods for the correction of translational motion have been studied extensively in the past. The subject of this thesis encompasses the rotational motion model and the effect of rotational motion on the collected MR data in the spatial frequency space (k-space), which is in general, more complicated than the translational model. Rotational motion artifacts are notably prevalent in MR images of head, brain and limbs. Post-processing techniques for the correction of rotational motion artifacts often involve interpolation and re-gridding of the acquired data in the k-space. These methods create significant data overlap and void regions. Therefore, in the past, proposed corrective techniques have been limited to suppression of artifacts caused by small angle rotations. This thesis presents a method of managing overlap regions, using weighted averaging of redundant data, in order to correct for large angle rotations. An iterative estimation technique for filling the data void regions has also been developed by the use of iterated application of projection operators onto constraint sets. These constraint sets are derived from the k-space data generated by the MR imager, and available a priori knowledge. It is shown that the iterative algorithm diverges at times from the required image, due to inconsistency among the constraint sets. It is also shown that this can be overcome by using soft. constraint sets and fuzzy projections. One of the constraints applied in the iterative algorithm is the finite support of the imaged object, marked by the outer boundary of the region of interest (ROI). However, object boundary extraction directly from the motion affected MR image can be difficult, specially if the motion function of the object is unknown. This thesis presents a new ROI extraction scheme based on entropy minimization in the image background. The object rotation function is usually unknown or unable to be measured with sufficient accuracy. The motion estimation algorithm proposed in this thesis is based on maximizing the similarity among the k-space data subjected to angular overlap. This method is different to the typically applied parameter estimation technique based on minimization of pixel energy outside the ROI, and has higher efficiency and ability to estimate rotational motion parameters in the midst of concurrent translational motion. The algorithms for ROI extraction, rotation estimation and data correction have been tested with both phantom images and spin echo MR images producing encouraging results

Doctor of Philosophy

dissertationEach year in the United States, a quarter million cases of stroke are caused directly by atherosclerotic disease of the cervical carotid artery. This represents a significant portion of health care costs that could be avoided if high-risk carotid artery lesions could be detected early on in disease progression. There is mounting evidence that Magnetic Resonance Imaging of the carotid artery can better classify subjects who would benefit from interventions. Turbo Spin Echo sequences are a class of Magnetic Resonance Imaging sequences that provide a variety of tissue contrasts. While high resolution Turbo Spin Echo images have demonstrated important details of carotid artery morphology, it is evident that pulsatile blood and wall motion related to the cardiac cycle are still significant sources of image degradation. In addition, patient motion artifacts due to the relatively long scan times of Turbo Spin Echo sequences result in an unacceptable fraction of noninterpretable studies. This dissertation presents work done to detect and correct for types of voluntary and physiological patient motion

Magnetic Resonance Imaging of the Brain in Moving Subjects. Application of Fetal, Neonatal and Adult Brain Studies

Imaging in the presence of subject motion has been an ongoing challenge for magnetic resonance imaging (MRI). Motion makes MRI data inconsistent, causing artifacts in conventional anatomical imaging as well as invalidating diffusion tensor imaging (DTI) reconstruction. In this thesis some of the important issues regarding the acquisition and reconstruction of anatomical and DTI imaging of moving subjects are addressed; methods to achieve high resolution and high signalto- noise ratio (SNR) volume data are proposed. An approach has been developed that uses multiple overlapped dynamic single shot slice by slice imaging combined with retrospective alignment and data fusion to produce self consistent 3D volume images under subject motion. We term this method as snapshot MRI with volume reconstruction or SVR. The SVR method has been performed successfully for brain studies on subjects that cannot stay still, and in some cases were moving substantially during scanning. For example, awake neonates, deliberately moved adults and, especially, on fetuses, for which no conventional high resolution 3D method is currently available. Fine structure of the in-utero fetal brain is clearly revealed for the first time with substantially improved SNR. The SVR method has been extended to correct motion artifacts from conventional multi-slice sequences when the subject drifts in position during data acquisition. Besides anatomical imaging, the SVR method has also been further extended to DTI reconstruction when there is subject motion. This has been validated successfully from an adult who was deliberately moving and then applied to inutero fetal brain imaging, which no conventional high resolution 3D method is currently available. Excellent fetal brain 3D apparent diffusion coefficient (ADC) maps in high resolution have been achieved for the first time as well as promising fractional Anisotropy (FA) maps. Pilot clinical studies using SVR reconstructed data to study fetal brain development in-utero have been performed. Growth curves for the normally developing fetal brain have been devised by the quantification of cerebral and cerebellar volumes as well as some one dimensional measurements. A Verhulst model is proposed to describe these growth curves, and this approach has achieved a correlation over 0.99 between the fitted model and actual data

Robust and time-effcient determination of perfusion parameters using time-encoded Arterial Spin Labeling MRI

In clinical routine, arterial spin labeling (ASL) faces many challenges, such as time pressure, patient- and disease-specific artifacts, e.g., in steno-occlusive and Moya-Moya disease. In addition, individually tailored parametrization of the MR pulse-sequence is frequently required. Time-encoded ASL-techniques like Hadamard time-encoded pseudocontinuous ASL (H-pCASL) offers a time and signal efficient way to measure accurately both perfusion and arterial transit-times. However, it relies on the decoding of a series of volumes. If even a single volume is corrupted this might, via the decoding process, lead to artifacts in the entire dataset and in the worst case result in the loss of the data. In this thesis a general introduction to time encoded ASL is given and three methods are introduced to increase the robustness of time-encoded ASL against image artifacts and to detect corrupted images. The first method is Walsh-ordered time-encoded H-pCASL (WH-pCASL). It proposes the Walsh-ordering of Hadamard encoding-matrices. In contrast to conventional H-pCASL, this makes perfusion-weighted images accessible during a running experiment and even from incomplete sets of encoded images. An optional additional averaging strategy is based on a mirrored matrix and results in more perfusion-weighted images without any penalty in time. The feasibility of the method is shown using five volunteer datasets. As a second method non-decoded time-encoded ASL is introduced. This novel model-based approach to quantification avoids the decoding step altogether. It models the non-decoded time encoded signal. Therefore it uses the convolution of the tissue response function with a model of the true encoded arterial input function, which is determined by the employed encoding matrix. The model was implemented in a Bayesian model-based ASL analysis framework to fit maps for hemodynamic parameters. The feasibility of the method is demonstrated in a study with five volunteers. The last method is an algorithm for the automated detection of outliers and corrupted images, which is based on variational Bayesian inference (VB). Using the variance of the posterior normal distributions, the algorithm measures the quality of a fit directly and without the need for a separate reference dataset. Its performance and feasibility is demonstrated using volunteer data and a clinical dataset

Processing strategies for functional magnetic resonance imaging data sets

Thesis (Ph.D.)--Harvard--Massachusetts Institute of Technology Division of Health Sciences and Technology, 1999.Includes bibliographical references (leaves 108-118).by Luis Carlos Maas, III.Ph.D

Doctor of Philosophy

dissertationThis dissertation presents original research that improves the ability of magnetic resonance imaging (MRI) to measure temperature in aqueous tissue using the proton resonance frequency (PRF) shift and T1 measurements in fat tissue in order to monitor focused ultrasound (FUS) treatments. The inherent errors involved in measuring the longitudinal relaxation time T1 using the variable flip angle method with a two-dimensional (2D) acquisition are presented. The edges of the slice profile can contribute a significant amount of signal for large flip angles at steady state, which causes significant errors in the T1 estimate. Only a narrow range of flip angle combinations provided accurate T1 estimates. Respiration motion causes phase artifacts, which lead to errors when measuring temperature changes using the PRF method. A respiration correction method for 3D imaging temperature of the breast is presented. Free induction decay (FID) navigators were used to measure and correct phase offsets induced by respiration. The precision of PRF temperature measurements within the breast was improved by an average factor of 2.1 with final temperature precision of approximately 1 °C. Locating the position of the ultrasound focus in MR coordinates of an ultrasound transducer with multiple degrees of freedom can be difficult. A rapid method for predicting the position using 3 tracker coils with a special MRI pulse iv sequence is presented. The Euclidean transformation of the coil's current positions to their calibration positions was used to predict the current focus position. The focus position was predicted to within approximately 2.1 mm in less than 1 s. MRI typically has tradeoffs between imaging field of view and spatial and temporal resolution. A method for acquiring a large field of view with high spatial and temporal resolution is presented. This method used a multiecho pseudo-golden angle stack of stars imaging sequence to acquire the large field of view with high spatial resolution and k-space weighted image contrast (KWIC) to increase the temporal resolution. The pseudo-golden angle allowed for removal of artifacts introduced by the KWIC reconstruction algorithm. The multiple echoes allowed for high readout bandwidth to reduce blurring due to off resonance and chemical shift as well as provide separate water/fat images, estimates of the initial signal magnitude M(0), T2 * time constant, and combination of echo phases. The combined echo phases provided significant improvement to the PRF temperature precision, and ranged from ~0.3-1.0 °C within human breast. M(0) and T2 * values can possibly be used as a measure of temperature in fat

Real-time motion and main magnetic field correction in MR spectroscopy using an EPI volumetric navigator

In population groups where subjects do not lie still during Magnetic Resonance Spectroscopy (MRS) scans, real-time volume of interest (VOI), frequency, and main magnetic field (B0) shim correction may be necessary. This work demonstrates firstly that head movement causes significant B0 disruption in both single voxel spectroscopy and spectroscopic imaging