895 research outputs found
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
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
Designing a Low-Cost Mobile Tracking System for Communication with a Medium Earth Orbit Satellite
An essential part of satellite communication is the orientation of the antenna, which can be difficult to ascertain on mobile platforms such as ships. While equipment to measure orientation accurately at sea exists, current solutions are expensive. This paper describes work toward an antenna orientation system using low-cost Global Position System (GPS) receivers. We investigated two methods: one using the spatial difference between multiple GPS units at the vertices of a polygon, and the other using the differences over time measured using a single GPS unit
We tested the antenna orientation system with the Omnispace F2 satellite at the US Electrodynamics, Inc. (USEI) teleport in Brewster, WA. Although non-correlated systematic errors in the GPS receivers made the multiple-GPS system impractical, the time-differential method was able to maintain a satellite lock for the majority of a simple test course. The reliability of this solution may be further improved using a gain-based correction algorithm
Integrated and efficient diffusion-relaxometry using ZEBRA
The emergence of multiparametric diffusion models combining diffusion and
relaxometry measurements provide powerful new ways to explore tissue
microstructure with the potential to provide new insights into tissue structure
and function. However, their ability to provide rich analyses and the potential
for clinical translation critically depends on the availability of efficient,
integrated, multi-dimensional acquisitions. We propose a fully integrated
sequence simultaneously sampling the acquisition parameter spaces required for
T1 and T2* relaxometry and diffusion MRI. Slice-level interleaved diffusion
encoding, multiple spin/gradient echoes and slice-shuffling are combined for
higher efficiency, sampling flexibility and enhanced internal consistency.
In-vivo data was successfully acquired on healthy adult brains. Obtained
parametric maps as well as clustering results demonstrate the potential of the
technique regarding its ability to provide eloquent data with an acceleration
of roughly 20 compared to conventionally used approaches. The proposed
integrated acquisition, called ZEBRA, offers significant acceleration and
flexibility compared to existing diffusion-relaxometry studies and thus
facilitates wider use of these techniques both for research-driven and clinical
applications
3D T2w fetal body MRI:automated organ volumetry, growth charts and population-averaged atlas
Structural fetal body MRI provides true 3D information required for volumetry of fetal organs. However, current clinical and research practice primarily relies on manual slice-wise segmentation of raw T2-weighted stacks, which is time consuming, subject to inter- and intra-observer bias and affected by motion-corruption. Furthermore, there are no existing standard guidelines defining a universal approach to parcellation of fetal organs. This work produces the first parcellation protocol of the fetal body organs for motion-corrected 3D fetal body MRI. It includes 10 organ ROIs relevant to fetal quantitative volumetry studies. We also introduce the first population-averaged T2w MRI atlas of the fetal body. The protocol was used as a basis for training of a neural network for automated organ segmentation. It showed robust performance for different gestational ages. This solution minimises the need for manual editing and significantly reduces time. The general feasibility of the proposed pipeline was also assessed by analysis of organ growth charts created from automated parcellations of 91 normal control 3T MRI datasets that showed expected increase in volumetry during 22-38 weeks gestational age range. In addition, the results of comparison between 60 normal and 12 fetal growth restriction datasets revealed significant differences in organ volumes.</p
Fully automated planning for anatomical fetal brain MRI on 0.55T
Purpose: Widening the availability of fetal MRI with fully automatic
real-time planning of radiological brain planes on 0.55T MRI. Methods: Deep
learning-based detection of key brain landmarks on a whole-uterus EPI scan
enables the subsequent fully automatic planning of the radiological single-shot
Turbo Spin Echo acquisitions. The landmark detection pipeline was trained on
over 120 datasets from varying field strength, echo times and resolutions and
quantitatively evaluated. The entire automatic planning solution was tested
prospectively in nine fetal subjects between 20 and 37 weeks. Comprehensive
evaluation of all steps, the distance between manual and automatic landmarks,
the planning quality and the resulting image quality was conducted. Results:
Prospective automatic planning was performed in real-time without latency in
all subjects. The landmark detection accuracy was 4.21+-2.56 mm for the fetal
eyes and 6.47+-3.23 for the cerebellum, planning quality was 2.44/3 (compared
to 2.56/3 for manual planning) and diagnostic image quality was 2.14 compared
to 2.07 for manual planning. Conclusions: Real-time automatic planning of all
three key fetal brain planes was successfully achieved and will pave the way
towards simplifying the acquisition of fetal MRI thereby widening the
availability of this modality in non-specialist centres.Comment: 17 pages, 8 figures, 1 table, MR
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