Search

Purpose: Simultaneous multi-slice techniques are reliant on multiband RF pulses, for which conventional design strategies result in long pulse durations, lengthening echo-times so lowering SNR for spin-echo imaging, and lengthening repetition times for gradient echo sequences. Pulse durations can be reduced with advanced RF pulse design methods that use time-variable selection gradients. However, the ability of gradient systems to reproduce fast switching pulses is often limited and can lead to image artifacts when ignored. We propose a time-efficient pulse design method that inherently produces gradient waveforms with lower temporal bandwidth., Methods: Efficient multiband RF pulses with time-variable gradients were designed using time-optimal VERSE. Using VERSE directly on multiband pulses leads to gradient waveforms with high temporal bandwidth, whereas VERSE applied first to singleband RF pulses and then modulated to make them multiband, significantly reduces this. The relative performance of these approaches was compared using simulation and experimental measurements., Results: Applying VERSE before multiband modulation was successful at removing out-of-band slice distortion. This effectively removes the need for high frequency modulation in the gradient waveform while preserving the benefit of time-efficiency inherited from VERSE., Conclusion: We propose a time-efficient RF pulse design that produces gradient pulses with lower temporal bandwidth, reducing image artifacts associated with finite temporal bandwidth of gradient systems., (© International Society for Magnetic Resonance in Medicine.)

Advances in microstructural modelling are leading to growing requirements on diffusion MRI acquisitions, namely sensitivity to smaller structures and better resolution of the geometric orientations. The resulting acquisitions contain highly attenuated images that present particular challenges when there is motion and geometric distortion. This study proposes to address these challenges by breaking with the conventional one-volume-one-encoding paradigm employed in conventional diffusion imaging using single-shot Echo Planar Imaging. By enabling free choice of the diffusion encoding on the slice level, a higher temporal sampling of slices with low b-value can be achieved. These allow more robust motion correction, and in combination with a second reversed phase-encoded echo, also dynamic distortion correction. These proposed advances are validated on phantom and adult experiments and employed in a study of eight foetal subjects. Equivalence in obtained diffusion quantities with the conventional method is demonstrated as well as benefits in distortion and motion correction. The resulting capability can be combined with any acquisition parameters including multiband imaging and allows application to diffusion MRI studies in general., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

The development of MRI systems operating at or above 7 T has provided researchers with a new window into the human body, yielding improved imaging speed, resolution and signal-to-noise ratio. In order to fully realise the potential of ultrahigh-field MRI, a range of technical hurdles must be overcome. The non-uniformity of the transmit field is one of such issues, as it leads to non-uniform images with spatially varying contrast. Parallel transmission (i.e. the use of multiple independent transmission channels) provides previously unavailable degrees of freedom that allow full spatial and temporal control of the radiofrequency (RF) fields. This review discusses the many ways in which these degrees of freedom can be used, ranging from making more uniform transmit fields to the design of subject-tailored RF pulses for both uniform excitation and spatial selection, and also the control of the specific absorption rate. © 2015 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd., (© 2015 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Purpose: Parallel transmission (PTx) requires knowledge of the B1+ produced by each element. However, B1+ mapping can be challenging when transmit fields exhibit large dynamic range. This study presents a method to produce high quality relative B1+ maps when this is the case., Theory and Methods: The proposed technique involves the acquisition of spoiled gradient echo (SPGR) images at multiple radiofrequency drive levels for each transmitter. The images are combined using knowledge of the SPGR signal equation using maximum likelihood estimation, yielding an image for each channel whose signal is proportional to the B1+ field strength. Relative B1+ maps are then obtained by taking image ratios. The method was tested using numerical simulations, phantom imaging, and through in vivo experiments., Results: The numerical simulations demonstrated that the proposed method can reconstruct relative transmit sensitivities over a wide range of B1+ amplitudes and at several SNR levels. The method was validated at 3 Tesla (T) by comparing it with an alternative B1+ mapping method, and demonstrated in vivo at 7T., Conclusion: Relative B1+ mapping in the presence of large dynamic range has been demonstrated through numerical simulations, phantom imaging at 3T and experimentally at 7T. The method will enable PTx to be applied in challenging imaging scenarios at ultrahigh field. Magn Reson Med 76:490-499, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited., (© 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.)

Purpose: This paper presents Precise Radiofrequency Inference from Multiple Observations (PRIMO), a comprehensive reconstruction framework for calibrating MRI systems with parallel transmit and parallel receive radiofrequency capabilities., Theory and Methods: To date, the vast majority of radiofrequency (RF) calibration methods have considered transmit and receive calibration separately, without acknowledging that transmit field calibration sequences measure sufficient data for receive calibration. PRIMO provides a method of extracting both transmit and receive fields from transmit calibration data without presuming knowledge of either. The method is tested for accuracy through simulation, comparison to a gold standard dataset, and is demonstrated on in-vivo data acquired at 3T., Results: PRIMO is shown to produce RF fields faithful to the gold standard with errors of less than 3% in realistic noise conditions. The in-vivo reconstructions demonstrate the method's ability to produce high quality transmit and receive maps, with an 8 transmit/8 receive channel system being fully calibrated in three dimensions in approximately 2 minutes., Conclusion: PRIMO provides a unified framework for estimating all transmit and receive fields in a single calibration step. This is becoming increasingly relevant in an era of MRI systems with highly parallel RF architectures., (© 2014 Wiley Periodicals, Inc.)

Purpose: The aim of this study was to determine T2* values for the fetal brain in utero and to compare them with previously reported values in preterm and term neonates. Knowledge of T2* may be useful for assessing brain development, brain abnormalities, and for optimizing functional imaging studies., Methods: Maternal respiration and unpredictable fetal motion mean that conventional multishot acquisition techniques used in adult T2* relaxometry studies are not practical. Single shot multiecho echo planar imaging was used as a rapid method for measuring fetal T2* by effectively freezing intra-slice motion., Results: T2* determined from a sample of 24 subjects correlated negatively with gestational age with mean values of 220 ms (±45) for frontal white matter, 159 ms (±32) for thalamic gray matter, and 236 ms (±45) for occipital white matter., Conclusion: Fetal T2* values are higher than those previously reported for preterm neonates and decline with a consistent trend across gestational age. The data suggest that longer than usual echo times or direct T2* measurement should be considered when performing fetal fMRI to reach optimal BOLD sensitivity., (© 2014 Wiley Periodicals, Inc.)

Purpose: Parallel transmission (PTx) offers spatial control of radiofrequency (RF) fields that can be used to mitigate nonuniformity effects in high-field MRI. In practice, the ability to achieve uniform RF fields by static shimming is limited by the typically small number of channels. Thus, tailored RF pulses that mix gradient with RF encoding have been proposed. A complementary approach termed "Direct Signal Control" (DSC) is to dynamically update RF shims throughout a sequence, exploiting interactions between each pulse and the spin system to achieve uniform signal properties from potentially nonuniform fields. This work applied DSC to T2-weighted driven-equilibrium three-dimensional fast spin echo (3D-FSE) brain imaging at 3T., Theory and Methods: The DSC concept requires an accurate signal model, provided by extending the spatially resolved extended phase graph framework to include the steady-state response of driven-equilibrium sequences. An 8-channel PTx body coil was used for experiments., Results: Phantom experiments showed the model to be accurate to within 0.3% (root mean square error). In vivo imaging showed over two-fold improvement in signal homogeneity compared with quadrature excitation. Although the nonlinear optimization cannot guarantee a global optimum, significantly improved local solutions were found., Conclusion: DSC has been demonstrated for 3D-FSE brain imaging at 3T. The concept is generally applicable to higher field strengths and other anatomies., (© 2014 Wiley Periodicals, Inc.)

Machine learning techniques have been widely used to detect morphological abnormalities from structural brain magnetic resonance imaging data and to support the diagnosis of neurological diseases such as dementia. In this paper, we propose to use a multiple instance learning (MIL) method in an application for the detection of Alzheimer's disease (AD) and its prodromal stage mild cognitive impairment (MCI). In our work, local intensity patches are extracted as features. However, not all the patches extracted from patients with dementia are equally affected by the disease and some of them may not be characteristic of morphology associated with the disease. Therefore, there is some ambiguity in assigning disease labels to these patches. The problem of the ambiguous training labels can be addressed by weakly supervised learning techniques such as MIL. A graph is built for each image to exploit the relationships among the patches and then to solve the MIL problem. The constructed graphs contain information about the appearances of patches and the relationships among them, which can reflect the inherent structures of images and aids the classification. Using the baseline MR images of 834 subjects from the ADNI study, the proposed method can achieve a classification accuracy of 89% between AD patients and healthy controls, and 70% between patients defined as stable MCI and progressive MCI in a leave-one-out cross validation. Compared with two state-of-the-art methods using the same dataset, the proposed method can achieve similar or improved results, providing an alternative framework for the detection and prediction of neurodegenerative diseases., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Purpose: The use of tailored RF excitation pulses for prospective correction of non-linear motion-induced phase patterns is shown to enable diffusion-weighted (DW) fast spin echo (FSE) imaging in vivo. Echo-planar imaging (EPI) remains the most used sequence for DW imaging. Despite being highly sensitive to field inhomogeneities, EPI is robust to motion-induced phase shifts. FSE sequences are much less sensitive to field inhomogeneities, but require precise control of the transverse magnetization phase, which is hard to achieve with DW. Real time measurements and correction of phase ramps due to rigid-body motion had been proposed, but performance remained unsatisfactory because of non-linear phase patterns related to pulsatile motion., Methods: Reproducible non-linear phase components are calibrated using 2D-EPI navigators and tailored RF excitation pulses designed. Real time correction of rigid-body motion was not yet implemented., Results: Phase correction was confirmed with full signal DW-FSE images obtained on co-operative subjects. Full diffusion tensor acquisitions were obtained and color-coded maps displaying principal fiber directionality calculated. Results were consistent with corresponding EPI acquisitions except for absence of spatial distortions., Conclusion: Combining the proposed method with real time compensation of rigid-body motion has the potential to allow high quality, distortion free diffusion imaging throughout the brain., (Copyright © 2013 Wiley Periodicals, Inc.)

In this paper we present a semi-automatic method for analysis of the fetal thorax in genuine three-dimensional volumes. After one initial click we localize the spine and accurately determine the volume of the fetal lung from high resolution volumetric images reconstructed from motion corrupted prenatal Magnetic Resonance Imaging (MRI). We compare the current state-of-the-art method of segmenting the lung in a slice-by-slice manner with the most recent multi-scan reconstruction methods. We use fast rotation invariant spherical harmonics image descriptors with Classification Forest ensemble learning methods to extract the spinal cord and show an efficient way to generate a segmentation prior for the fetal lung from this information for two different MRI field strengths. The spinal cord can be segmented with a DICE coefficient of 0.89 and the automatic lung segmentation has been evaluated with a DICE coefficient of 0.87. We evaluate our method on 29 fetuses with a gestational age (GA) between 20 and 38 weeks and show that our computed segmentations and the manual ground truth correlate well with the recorded values in literature.

Medical image segmentation has traditionally been regarded as a separate process from image acquisition and reconstruction, even though its performance directly depends on the quality and characteristics of these first stages of the imaging pipeline. Adopting an integrated acquisition-reconstruction-segmentation process can provide a more efficient and accurate solution. In this paper we propose a joint segmentation and reconstruction algorithm for undersampled magnetic resonance data. Merging a reconstructive patch-based sparse modelling and a discriminative Gaussian mixture modelling can produce images with enhanced edge information ultimately improving their segmentation.

Brain images acquired at 3T often display central brightening with spatially varying tissue contrast, caused by inhomogeneity in the transmit radiofrequency fields used for excitation. Tailored radiofrequency pulses can provide mitigation of radiofrequency field inhomogeneity, but previous designs have been unsuitable for 3D imaging in rapid pulse sequences. This article presents a nonselective pulse design based on a short (1 ms) 3D spiral k-space trajectory that covers low spatial frequencies. The resulting excitations are optimized to produce a uniform excitation within a specified volume of interest covering the whole brain. B1 mapping and pulse calculation times were reduced by optimizing in only five slices within the brain. The method has been tested with both single and parallel transmission: in phantom experiments, normalized root-mean-square error in excitation was 0.022 for single and 0.020 for parallel transmission. The corresponding results in vivo were 0.066 and 0.055 respectively. A pilot brain imaging study using the proposed pulses for excitation within the Alzheimer's disease neuroimaging initiative magnetization prepared rapid gradient echo (MP-RAGE) protocol, yielded excellent image quality with improved signal to noise ratio in peripheral brain regions and enhanced uniformity of contrast compared with standard excitation. Greatest performance enhancement was achieved using parallel transmission, but single channel transmission offers significant improvement over standard excitation pulses., (Copyright © 2011 Wiley Periodicals, Inc.)

To enable clinical use of parallel transmission technology, it is necessary to rapidly produce transmit sensitivity (σ) maps. Actual flip angle imaging is an efficient mapping technique, which is accurate when used with 3D encoding and nonselective RF pulses. Mapping single slices is quicker, but 2D encoding leads to systematic errors due to slice profile effects. By simulating steady-state slice profiles, we computed the relationship between σ and the signals received from the actual flip angle imaging sequence for arbitrarily chosen slice selective RF pulses. Pulse specific lookup tables were then used for reconstruction. The resulting σ-maps are sensitive to T(1) in a manner that depends strongly on the specific pulse, for example a precision of ±3% can be achieved by using a 3-lobe sinc pulse. The method is applicable to any RF pulse; simulations must be performed once and thereafter fast reconstruction of σ-maps is possible., (Copyright © 2010 Wiley-Liss, Inc.)

Purpose: To prospectively evaluate the clinical effectiveness of snapshot inversion recovery (SNAPIR), which is a dedicated optimized inversion-recovery-prepared single-shot fast spin-echo T1-weighted sequence, in the delineation of normal fetal brain anatomy compared with that of the currently used T1-weighted gradient-echo protocol, which often yields images of poor quality due to motion artifacts and inadequate contrast., Materials and Methods: This study was approved by the hospital research ethics committee, and informed written consent was obtained from all patients. Forty-one fetuses were examined at 19-37 weeks gestation (mean, 29 weeks gestation) by using both the standard T1-weighted protocol and the optimized T1-weighted SNAPIR protocol with a 1.5-T imager. Two independent blinded observers performed qualitative analysis, evaluating overall diagnostic quality, detailed anatomic delineation, and severity of motion artifacts. Quantitative analysis comprised calculation of contrast ratios (CRs) for the cortical gray matter, subplate, white matter, and cerebrospinal fluid. The Wilcoxon signed rank test was used to compare image rating scores, the paired t test was used to compare CRs, and κ statistics were used to test interobserver agreement., Results: Both overall diagnostic quality (P < .001) and detailed anatomic delineation (P < .001) were enhanced with SNAPIR compared with the standard T1-weighted acquisition. Also, motion artifacts were less severe (P = .008) and less extensive (P < .001) with SNAPIR. Corresponding CRs were increased with SNAPIR in seven of eight examined regions., Conclusion: SNAPIR is a promising robust alternative to the current T1-weighted acquisitions; its role in the detection of disease requires further study.

Accuracy of B(1) mapping for array coils can be improved by mapping the fields produced by driving linear combinations of the array elements, chosen to produce a more uniform distribution of B(1) amplitude. Quality of the resulting single element B(1) maps is influenced by the transformation used both via the uniformity of the resulting linear combination fields and by the degree to which these linear combinations differ from one another. In this work we investigate the effect of using different transformations on the quality of B(1) maps by simulating the B(1) mapping process for two different techniques, using real data from a 3T 8-channel body transmit system. Different transformations are generated using a single complex parameter. It is demonstrated that the optimal transformation within this framework is different for different imaging targets (pelvis and brain of healthy volunteers, and water and oil phantoms). For the same target (pelvis) the optimum condition, however, is similar for a number of subjects, suggesting that optimal configurations to be used for calibrating coils in specific anatomical contexts can be determined in advance. Potential gains may be translated into significant reductions in scan time for equivalent signal-to-noise ratio coil maps., ((c) 2009 Wiley-Liss, Inc.)

We present a methodology to achieve 3D high-resolution diffusion tensor image reconstruction of the brain in moving subjects. The source data is diffusion-sensitized single-shot echo-planar images. After continuous scanning to acquire a repeated series of parallel slices with 15 diffusion directions, image registration is used to realign the images to correct for subject motion. Once aligned, the diffusion images are treated as irregularly-sampled data where each voxel is associated with an appropriately rotated diffusion direction. This data is used to estimate the diffusion tensor on a regular grid. The method has been tested on data acquired at 1.5T from adults who deliberately moved and from eight fetuses imaged in utero. Maps of apparent diffusion coefficient (ADC) were reliably produced in all cases and promising performance was achieved for fractional anisotropy maps. Results from normal fetal brains were found to be consistent with published data from premature infants of similar gestational age.

The aim of this paper is to investigate techniques that can identify and quantify cross-sectional differences and longitudinal changes in vivo from magnetic resonance images of murine models of brain disease. Two different approaches have been compared. The first approach is a segmentation-based approach: Each subject at each time point is automatically segmented into a number of anatomical structures using atlas-based segmentation. This allows cross-sectional and longitudinal analyses of group differences on a structure-by-structure basis. The second approach is a deformation-based approach: Longitudinal changes are quantified by the registration of each subject's follow-up images to that subject's baseline image. In addition the baseline images can be registered to an atlas allowing voxel-wise analysis of cross-sectional differences between groups. Both approaches have been tested on two groups of mice: A transgenic model of Alzheimer's disease and a wild-type background strain, using serial imaging performed over the age range from 6-14 months. We show that both approaches are able to identify longitudinal and cross-sectional differences. However, atlas-based segmentation suffers from the inability to detect differences across populations and across time in regions which are much smaller than the anatomical regions. In contrast to this, the deformation-based approach can detect statistically significant differences in highly localized areas.

Background: Diagnostic decisions in clinical imaging currently rely almost exclusively on visual image interpretation. This can lead to uncertainty, for example in dementia disease, where some of the changes resemble those of normal ageing. We hypothesized that extracting volumetric data from patients' MR brain images, relating them to reference data and presenting the results as a colour overlay on the grey scale data would aid diagnostic readers in classifying dementia disease versus normal ageing., Methods: A proof-of-concept forced-choice reader study was designed using MR brain images from 36 subjects. Images were segmented into 43 regions using an automatic atlas registration-based label propagation procedure. Seven subjects had clinically probable AD, the remaining 29 of a similar age range were used as controls. Seven of the control subject data sets were selected at random to be presented along with the seven AD datasets to two readers, who were blinded to all clinical and demographic information except age and gender. Readers were asked to review the grey scale MR images and to record their choice of diagnosis (AD or non-AD) along with their confidence in this decision. Afterwards, readers were given the option to switch on a false-colour overlay representing the relative size of the segmented structures. Colorization was based on the size rank of the test subject when compared with a reference group consisting of the 22 control subjects who were not used as review subjects. The readers were then asked to record whether and how the additional information had an impact on their diagnostic confidence., Results: The size rank colour overlays were useful in 18 of 28 diagnoses, as determined by their impact on readers' diagnostic confidence. A not useful result was found in 6 of 28 cases. The impact of the additional information on diagnostic confidence was significant (p < 0.02)., Conclusion: Volumetric anatomical information extracted from brain images using automatic segmentation and presented as colour overlays can support diagnostic decision making.

Although the evaluation of cardiac perfusion using MRI could be of crucial importance for the diagnosis of ischemic heart diseases, it is still not a routinely used technique. The major difficulty is that MR perfusion images are often corrupted by inconsistent myocardial motion. Although motion compensation methods have been studied throughout the past decade, no clinically accepted solution has emerged. This is partly due to the lack of comprehensive validation. To address this deficit we collected a large multi-centre MR perfusion dataset and used this to characterize typical myocardial motion and confirmed that under clinically relevant conditions motion correction is a frequent requirement (67% of all 586 cases). We then developed a proposed solution which includes both rigid/affine and the non-rigid image registration. Quantitative validation has been conducted using 6 different statistics to provide a comprehensive evaluation, showing the proposed techniques to be highly robust to different myocardial anatomy and motion patterns as well as to MR imaging acquisition parameters.

Motion degrades magnetic resonance (MR) images and prevents acquisition of self-consistent and high-quality volume images. A novel methodology, Snapshot magnetic resonance imaging (MRI) with Volume Reconstruction (SVR) has been developed for imaging moving subjects at high resolution and high signal-to-noise ratio (SNR). The method combines registered 2-D slices from sequential dynamic single-shot scans. The SVR approach requires that the anatomy in question is not changing shape or size and is moving at a rate that allows snapshot images to be acquired. After imaging the target volume repeatedly to guarantee sufficient sampling every where, a robust slice-to-volume registration method has been implemented that achieves alignment of each slice within 0.3 mm in the examples tested. Multilevel scattered interpolation has been used to obtain high-fidelity reconstruction with root-mean-square (rms) error that is less than the noise level in the images. 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 3-D method is currently available. Fine structure of the in-utero fetal brain is clearly revealed for the first time and substantial SNR improvement is realized by having many individually acquired slices contribute to each voxel in the reconstructed image.

We present a methodology to achieve 3D high resolution in-utero fetal brain DTI that shows excellent ADC as well as promising FA maps. After continuous DTI scanning to acquire a repeated series of parallel slices with 15 diffusion directions, image registration is used to realign the images to correct for fetal motion. Once aligned, the diffusion images are treated as irregularly sampled data where each voxel is associated with an appropriately rotated diffusion direction, and used to estimate the diffusion tensor on a regular grid. The method has been tested successful on eight fetuses and has been validated on adults imaged at 1.5T.

Recent innovations in drug therapies have made it highly desirable to obtain sensitive biomarkers of disease progression that can be used to quantify the performance of candidate disease modifying drugs. In order to measure potential image-based biomarkers of disease progression in an experimental model of rheumatoid arthritis (RA), we present two different methods to automatically quantify changes in a bone in in-vivo serial magnetic resonance (MR) images from the model. Both methods are based on rigid and nonrigid image registration to perform the analysis. The first method uses segmentation propagation to delineate a bone from the serial MR images giving a global measure of temporal changes in bone volume. The second method uses rigid body registration to determine intensity change within a bone, and then maps these into a reference coordinate system using nonrigid registration. This gives a local measure of temporal changes in bone lesion volume. We detected significant temporal changes in local bone lesion volume in five out of eight identified candidate bone lesion regions, and significant difference in local bone lesion volume between male and female subjects in three out of eight candidate bone lesion regions. But the global bone volume was found to be fluctuating over time. Finally, we compare our findings with histology of the subjects and the manual segmentation of bone lesions.

Cardiac pulsatility causes a nonrigid motion of the brain. In multi-shot diffusion imaging this leads to spatially varying phase changes that must be corrected. A conjugate gradient based reconstruction is presented that includes phase changes measured using two-dimensional navigator echoes, coil sensitivity information, navigator-determined weightings, and data from multiple coils and averages.A multi-shot echo planar sequence was used to image brain regions where pulsatile motion is not uniform. Reduced susceptibility artifacts were observed compared to a clinical single-shot sequence. In a higher slice, fiber directions derived from single-shot data show distortions from anatomical scans by as much as 7 mm compared to less than 2 mm for our multi-shot reconstructions. The reduced distortions imply that phase encoding can be applied in the shorter left-right direction, enabling time savings through the use of a rectangular field of view. Higher resolution diffusion imaging in the spine permits visualization of a nerve root., ((c) 2006 Wiley-Liss, Inc.)

In this paper we propose a diffeomorphic non-rigid registration algorithm based on free-form deformations (FFDs) which are modelled by B-splines. In contrast to existing non-rigid registration methods based on FFDs the proposed diffeomorphic non-rigid registration algorithm based on free-form deformations (FFDs) which are modelled by B-splines. To construct a diffeomorphic transformation we compose a sequence of free-form deformations while ensuring that individual FFDs are one-to-one transformations. We have evaluated the algorithm on 20 normal brain MR images which have been manually segmented into 67 anatomical structures. Using the agreement between manual segmentation and segmentation propagation as a measure of registration quality we have compared the algorithm to an existing FFD registration algorithm and a modified FFD registration algorithm which penalises non-diffeomorphic transformations. The results show that the proposed algorithm generates diffeomorphic transformations while providing similar levels of performance as the existing FFD registration algorithm in terms of registration accuracy.

Segmentations of MR images of the human brain can be generated by propagating an existing atlas label volume to the target image. By fusing multiple propagated label volumes, the segmentation can be improved. We developed a model that predicts the improvement of labelling accuracy and precision based on the number of segmentations used as input. Using a cross-validation study on brain image data as well as numerical simulations, we verified the model. Fit parameters of this model are potential indicators of the quality of a given label propagation method or the consistency of the input segmentations used.

This paper describes an automatic tissue segmentation algorithm for brain MRI of young children. Existing segmentation methods developed for the adult brain do not take into account the specific tissue properties present in the brain MRI of young children. We examine the suitability of state-of-the-art methods developed for the adult brain when applied to the segmentation of the young child brain MRI. We develop a method of creation of a population-specific atlas from young children using a single manual segmentation. The method is based on non-linear propagation of the segmentation into population and subsequent affine alignment into a reference space and averaging. Using this approach we significantly improve the performance of the popular EM segmentation algorithm on brain MRI of young children.

Methods utilizing Padé approximants are investigated for implementation with magnetic resonance imaging data and are presented both for direct image reconstruction and for feature extraction. Padé approximants are a numerical tool that can be used to accelerate the convergence of a slowly converging sequence by estimating the fully converged sequence values from early data points. Padé approximants can be calculated directly from k-space data by solving a set of linear matrix equations to produce signal values for any desired location in the image domain. This gives an estimate of the fully converged signal intensity at each pixel location in the image, raising the possibility of reconstructing a better estimate of the object from a reduced data set. These methods have been tested on phantom and human data both for image reconstruction and for feature extraction. In image reconstruction, considerable convergence acceleration can be achieved, with steep intensity boundaries reproduced in keeping with higher resolution reconstructions and oscillatory truncation artifact characteristic of Fourier reconstruction removed. The convergence acceleration is variable and there is the possibility of fine detail suppression when insufficient data are included. The use of Padé methods as a tool for feature extraction has shown good agreement with extraction from high-resolution reference data. In this approach the edge information comes intrinsically from Padé reconstruction.