105 research outputs found
MIXANDMIX: numerical techniques for the computation of empirical spectral distributions of population mixtures
The MIXANDMIX (mixtures by Anderson mixing) tool for the computation of the
empirical spectral distribution of random matrices generated by mixtures of
populations is described. Within the population mixture model the mapping
between the population distributions and the limiting spectral distribution can
be obtained by solving a set of systems of non-linear equations, for which an
efficient implementation is provided. The contributions include a method for
accelerated fixed point convergence, a homotopy continuation strategy to
prevent convergence to non-admissible solutions, a blind non-uniform grid
construction for effective distribution support detection and approximation,
and a parallel computing architecture. Comparisons are performed with available
packages for the single population case and with results obtained by simulation
for the more general model implemented here. Results show competitive
performance and improved flexibility.Comment: 17 pages, 6 figure
Complex diffusion-weighted image estimation via matrix recovery under general noise models
We propose a patch-based singular value shrinkage method for diffusion
magnetic resonance image estimation targeted at low signal to noise ratio and
accelerated acquisitions. It operates on the complex data resulting from a
sensitivity encoding reconstruction, where asymptotically optimal signal
recovery guarantees can be attained by modeling the noise propagation in the
reconstruction and subsequently simulating or calculating the limit singular
value spectrum. Simple strategies are presented to deal with phase
inconsistencies and optimize patch construction. The pertinence of our
contributions is quantitatively validated on synthetic data, an in vivo adult
example, and challenging neonatal and fetal cohorts. Our methodology is
compared with related approaches, which generally operate on magnitude-only
data and use data-based noise level estimation and singular value truncation.
Visual examples are provided to illustrate effectiveness in generating denoised
and debiased diffusion estimates with well preserved spatial and diffusion
detail.Comment: 26 pages, 9 figure
Non-Rigid Groupwise Registration for Motion Estimation and Compensation in Compressed Sensing Reconstruc- tion of Breath-Hold Cardiac Cine MRI
Purpose: Compressed sensing methods with motion estimation and compensation techniques
have been proposed for the reconstruction of accelerated dynamic MRI. However, artifacts that
naturally arise in compressed sensing reconstruction procedures hinder the estimation of motion
from reconstructed images, especially at high acceleration factors. This work introduces a robust
groupwise non-rigid motion estimation technique applied to the compressed sensing reconstruction
of dynamic cardiac cine MRI sequences.
Theory and Methods: A spatio-temporal regularized, groupwise, non-rigid registration method
based on a B-splines deformation model and a least squares metric is used to estimate and to
compensate the movement of the heart in breath-hold cine acquisitions and to obtain a quasi-static
sequence with highly sparse representation in temporally transformed domains.
Results: Short axis in vivo datasets are used for validation, both original multi-coil as well as
DICOM data. Fully sampled data were retrospectively undersampled with various acceleration
factors and reconstructions were compared with the two well-known methods k-t FOCUSS and
MASTeR. The proposed method achieves higher signal to error ratio and structure similarity index
for medium to high acceleration factors.
Conclusions: Reconstruction methods based on groupwise registration show higher quality recon-
structions for cardiac cine images than the pairwise counterparts tested
Multi-Oriented Windowed Harmonic Phase Reconstruction for Robust Cardiac Strain Imaging
The purpose of this work is to develop a method for direct estimation of
the cardiac strain tensor by extending the harmonic phase reconstruction on
tagged magnetic resonance images to obtain more precise and robust measurements.
The extension relies on the reconstruction of the local phase of
the image by means of the windowed Fourier transform and the acquisition of
an overdetermined set of stripe orientations in order to avoid the phase interferences
from structures outside the myocardium and the instabilities arising
from the application of a gradient operator. Results have shown that increasing
the number of acquired orientations provides a signi cant improvement
in the reproducibility of the strain measurements and that the acquisition of
an extended set of orientations also improves the reproducibility when compared
with acquiring repeated samples from a smaller set of orientations.
Additionally, biases in local phase estimation when using the original harmonic
phase formulation are greatly diminished by the one here proposed.
The ideas here presented allow the design of new methods for motion sensitive
magnetic resonance imaging, which could simultaneously improve the
resolution, robustness and accuracy of motion estimates
Autocalibrated cardiac tissue phase mapping with multiband imaging and k-t acceleration
PURPOSE: To develop an autocalibrated multiband (MB) CAIPIRINHA acquisition scheme with in-plane k-t acceleration enabling multislice three-directional tissue phase mapping in one breath-hold. METHODS: A k-t undersampling scheme was integrated into a time-resolved electrocardiographic-triggered autocalibrated MB gradient-echo sequence. The sequence was used to acquire data on 4 healthy volunteers with MB factors of two (MB2) and three (MB3), which were reconstructed using a joint reconstruction algorithm that tackles both k-t and MB acceleration. Forward simulations of the imaging process were used to tune the reconstruction model hyperparameters. Direct comparisons between MB and single-band tissue phase-mapping measurements were performed. RESULTS: Simulations showed that the velocities could be accurately reproduced with MB2 k-t (average ± twice the SD of the RMS error of 0.08 ± 0.22 cm/s and velocity peak reduction of 1.03% ± 6.47% compared with fully sampled velocities), whereas acceptable results were obtained with MB3 k-t (RMS error of 0.13 ± 0.58 cm/s and peak reduction of 2.21% ± 13.45%). When applied to tissue phase-mapping data, the proposed technique allowed three-directional velocity encoding to be simultaneously acquired at two/three slices in a single breath-hold of 18 heartbeats. No statistically significant differences were detected between MB2/MB3 k-t and single-band k-t motion traces averaged over the myocardium. Regional differences were found, however, when using the American Heart Association model for segmentation. CONCLUSION: An autocalibrated MB k-t acquisition / reconstruction framework is presented that allows three-directional velocity encoding of the myocardial velocities at multiple slices in one breath-hold
- …