259 research outputs found
Effect of mixing and spatial dimension on the glass transition
We study the influence of composition changes on the glass transition of
binary hard disc and hard sphere mixtures in the framework of mode coupling
theory. We derive a general expression for the slope of a glass transition
line. Applied to the binary mixture in the low concentration limits, this new
method allows a fast prediction of some properties of the glass transition
lines. The glass transition diagram we find for binary hard discs strongly
resembles the random close packing diagram. Compared to 3D from previous
studies, the extension of the glass regime due to mixing is much more
pronounced in 2D where plasticization only sets in at larger size disparities.
For small size disparities we find a stabilization of the glass phase quadratic
in the deviation of the size disparity from unity.Comment: 13 pages, 8 figures, Phys. Rev. E (in print
Generalising Deep Learning MRI Reconstruction across Different Domains
We look into robustness of deep learning based MRI reconstruction when tested
on unseen contrasts and organs. We then propose to generalise the network by
training with large publicly-available natural image datasets with synthesised
phase information to achieve high cross-domain reconstruction performance which
is competitive with domain-specific training. To explain its generalisation
mechanism, we have also analysed patch sets for different training datasets.Comment: Accepted for ISBI2019 as a 1-page abstrac
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
3-D Coherent Multi-Transducer Ultrasound Imaging with Sparse Spiral Arrays
Coherent multi-transducer ultrasound (CoMTUS) creates an extended effective
aperture through the coherent combination of multiple arrays, which results in
images with enhanced resolution, extended field-of-view, and higher
sensitivity. The subwavelength localization accuracy of the multiple
transducers required to coherently beamform the data is achieved by using the
echoes backscattered from targeted points. In this study, CoMTUS is implemented
and demonstrated for the first time in 3-D imaging using a pair of 256-element
2-D sparse spiral arrays, which keep the channel-count low and limit the amount
of data to be processed. The imaging performance of the method was investigated
using both simulations and phantom tests. The feasibility of free-hand
operation is also experimentally demonstrated. Results show that, in comparison
to a single dense array system using the same total number of active elements,
the proposed CoMTUS system improves spatial resolution (up to 10 times) in the
direction where both arrays are aligned, contrast-to-noise-ratio (CNR, up to
30%), and generalized CNR (up to 11%). Overall, CoMTUS shows narrower main lobe
and higher contrast-to-noise-ratio, which results in an increased dynamic range
and better target detectability.Comment: 10 pages, 6 figure
Combined Diffusion-Relaxometry MRI to Identify Dysfunction in the Human Placenta
Purpose: A combined diffusion-relaxometry MR acquisition and analysis
pipeline for in-vivo human placenta, which allows for exploration of coupling
between T2* and apparent diffusion coefficient (ADC) measurements in a sub 10
minute scan time.
Methods: We present a novel acquisition combining a diffusion prepared
spin-echo with subsequent gradient echoes. The placentas of 17 pregnant women
were scanned in-vivo, including both healthy controls and participants with
various pregnancy complications. We estimate the joint T2*-ADC spectra using an
inverse Laplace transform.
Results: T2*-ADC spectra demonstrate clear quantitative separation between
normal and dysfunctional placentas.
Conclusions: Combined T2*-diffusivity MRI is promising for assessing fetal
and maternal health during pregnancy. The T2*-ADC spectrum potentially provides
additional information on tissue microstructure, compared to measuring these
two contrasts separately. The presented method is immediately applicable to the
study of other organs
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