280 research outputs found

    Travelling-wave nuclear magnetic resonance

    Full text link
    Nuclear magnetic resonance (NMR) is one of the most versatile experimental methods in chemistry, physics and biology, providing insight into the structure and dynamics of matter at the molecular scale. Its imaging variant-magnetic resonance imaging (MRI)-is widely used to examine the anatomy, physiology and metabolism of the human body. NMR signal detection is traditionally based on Faraday induction in one or multiple radio-frequency resonators that are brought into close proximity with the sample. Alternative principles involving structured-material flux guides, superconducting quantum interference devices, atomic magnetometers, Hall probes or magnetoresistive elements have been explored. However, a common feature of all NMR implementations until now is that they rely on close coupling between the detector and the object under investigation. Here we show that NMR can also be excited and detected by long-range interaction, relying on travelling radio-frequency waves sent and received by an antenna. One benefit of this approach is more uniform coverage of samples that are larger than the wavelength of the NMR signal-an important current issue in MRI of humans at very high magnetic fields. By allowing a significant distance between the probe and the sample, travelling-wave interaction also introduces new possibilities in the design of NMR experiments and systems

    Analysis of nickel concentration profiles around the roots of the hyperaccumulator plant Berkheya coddii using MRI and numerical simulations

    Get PDF
    Investigations of soil-root interactions are hampered by the difficult experimental accessibility of the rhizosphere. Here we show the potential of Magnetic Resonance Imaging (MRI) as a non-destructive measurement technique in combination with numerical modelling to study the dynamics of the spatial distribution of dissolved nickel (Ni2+) around the roots of the nickel hyperaccumulator plant Berkheya coddii. Special rhizoboxes were used in which a root monolayer had been grown, separated from an adjacent inert glass bead packing by a nylon membrane. After applying a Ni2+ solution of 10mgl−1, the rhizobox was imaged repeatedly using MRI. The obtained temporal sequence of 2-dimensional Ni2+ maps in the vicinity of the roots showed that Ni2+ concentrations increased towards the root plane, revealing an accumulation pattern. Numerical modelling supported the Ni2+ distributions to result from advective water flow towards the root plane, driven by transpiration, and diffusion of Ni2+ tending to eliminate the concentration gradient. With the model, we could study how the accumulation pattern of Ni2+ in the root zone transforms into a depletion pattern depending on transpiration rate, solute uptake rate, and Ni2+ concentration in solutio

    APIR-Net: Autocalibrated Parallel Imaging Reconstruction using a Neural Network

    Full text link
    Deep learning has been successfully demonstrated in MRI reconstruction of accelerated acquisitions. However, its dependence on representative training data limits the application across different contrasts, anatomies, or image sizes. To address this limitation, we propose an unsupervised, auto-calibrated k-space completion method, based on a uniquely designed neural network that reconstructs the full k-space from an undersampled k-space, exploiting the redundancy among the multiple channels in the receive coil in a parallel imaging acquisition. To achieve this, contrary to common convolutional network approaches, the proposed network has a decreasing number of feature maps of constant size. In contrast to conventional parallel imaging methods such as GRAPPA that estimate the prediction kernel from the fully sampled autocalibration signals in a linear way, our method is able to learn nonlinear relations between sampled and unsampled positions in k-space. The proposed method was compared to the start-of-the-art ESPIRiT and RAKI methods in terms of noise amplification and visual image quality in both phantom and in-vivo experiments. The experiments indicate that APIR-Net provides a promising alternative to the conventional parallel imaging methods, and results in improved image quality especially for low SNR acquisitions.Comment: To appear in the proceedings of MICCAI 2019 Workshop Machine Learning for Medical Image Reconstructio

    A comprehensive approach for correcting voxel‐wise b‐value errors in diffusion MRI

    Get PDF
    Purpose In diffusion MRI, the actual b‐value played out on the scanner may deviate from the nominal value due to magnetic field imperfections. A simple image‐based correction method for this problem is presented. Methods The apparent diffusion constant (ADC) of a water phantom was measured voxel‐wise along 64 diffusion directions at b = 1000 s/mm2. The true diffusion constant of water was estimated, considering the phantom temperature. A voxel‐wise correction factor, providing an effective b‐value including any magnetic field deviations, was determined for each diffusion direction by relating the measured ADC to the true diffusion constant. To test the method, the measured b‐value map was used to calculate the corrected voxel‐wise ADC for additionally acquired diffusion data sets on the same water phantom and data sets acquired on a small water phantom at three different positions. Diffusion tensor was estimated by applying the measured b‐value map to phantom and in vivo data sets. Results The b‐value‐corrected ADC maps of the phantom showed the expected spatial uniformity as well as a marked improvement in consistency across diffusion directions. The b‐value correction for the brain data resulted in a 5.8% and 5.5% decrease in mean diffusivity and angular differences of the primary diffusion direction of 2.71° and 0.73° inside gray and white matter, respectively. Conclusion The actual b‐value deviates significantly from its nominal setting, leading to a spatially variable error in the common diffusion outcome measures. The suggested method measures and corrects these artifacts

    The CAT-ACT Beamline at ANKA: A new high energy X-ray spectroscopy facility for CATalysis and ACTinide research

    Get PDF
    A new hard X-ray beamline for CATalysis and ACTinide research has been built at the synchrotron radiation facility ANKA. The beamline design is dedicated to X-ray spectroscopy, including ‘flux hungry’ photon-in/photon-out and correlative techniques with a special infrastructure for radionuclide and catalysis research. The CAT-ACT beamline will help serve the growing need for high flux/hard X-ray spectroscopy in these communities. The design, the first spectra and the current status of this project are reported

    The CAT-ACT Beamline at ANKA : A new high energy X-ray spectroscopy facility for CATalysis and ACTinide research

    Get PDF
    A new hard X-ray beamline for CATalysis and ACTinide research has been built at the synchrotron radiation facility ANKA. The beamline design is dedicated to X-ray spectroscopy, including ‘flux hungry’ photon-in/photon-out and correlative techniques with a special infrastructure for radionuclide and catalysis research. The CAT-ACT beamline will help serve the growing need for high flux/hard X-ray spectroscopy in these communities. The design, the first spectra and the current status of this project are reported

    Analytical form of Shepp-Logan phantom for parallel MRI

    Get PDF
    ABSTRACT We present an analytical form of ground-truth k-space data for the 2-D Shepp-Logan brain phantom in the presence of multiple and non-homogeneous receiving coils. The analytical form allows us to conduct realistic simulations and validations of reconstruction algorithms for parallel MRI. The key contribution of our work is to use a polynomial representation of the coil's sensitivity. We show that this method is particularly accurate and fast with respect to the conventional methods. The implementation is made available to the community
    • 

    corecore