25 research outputs found
Improving B1 homogeneity in abdominal imaging at 3 T with light and compact metasurface
Radiofrequency field inhomogeneity is a significant issue in imaging large
fields of view in high- and ultrahigh-field MRI. Passive shimming with coupled
coils or dielectric pads is the most common approach at 3 T. We introduce and
test light and compact metasurface, providing the same homogeneity improvement
in clinical abdominal imaging at 3 T as a conventional dielectric pad. The
metasurface comprising a periodic structure of copper strips and parallel-plate
capacitive elements printed on a flexible polyimide substrate supports
propagation of slow electromagnetic waves similar to a high-permittivity slab.
We compare the metasurface operating inside a transmit body birdcage coil to
the state-of-the-art pad by numerical simulations and in vivo study on healthy
volunteers. Numerical simulations with different body models show that the
local minimum of B1+ causing a dark void in the abdominal domain is removed by
the metasurface with comparable resulting homogeneity as for the pad without
noticeable SAR change. In vivo results confirm similar homogeneity improvement
and demonstrate the stability to body mass index. The light, flexible, and
cheap metasurface can replace a relatively heavy and expensive pad based on the
aqueous suspension of barium titanate in abdominal imaging at 3 T.Comment: 18 pages, 6 figures, 4 supplementary figure
Deep learning-based fully automatic segmentation of wrist cartilage in MR images
The study objective was to investigate the performance of a dedicated
convolutional neural network (CNN) optimized for wrist cartilage segmentation
from 2D MR images. CNN utilized a planar architecture and patch-based (PB)
training approach that ensured optimal performance in the presence of a limited
amount of training data. The CNN was trained and validated in twenty
multi-slice MRI datasets acquired with two different coils in eleven subjects
(healthy volunteers and patients). The validation included a comparison with
the alternative state-of-the-art CNN methods for the segmentation of joints
from MR images and the ground-truth manual segmentation. When trained on the
limited training data, the CNN outperformed significantly image-based and
patch-based U-Net networks. Our PB-CNN also demonstrated a good agreement with
manual segmentation (Sorensen-Dice similarity coefficient (DSC) = 0.81) in the
representative (central coronal) slices with large amount of cartilage tissue.
Reduced performance of the network for slices with a very limited amount of
cartilage tissue suggests the need for fully 3D convolutional networks to
provide uniform performance across the joint. The study also assessed inter-
and intra-observer variability of the manual wrist cartilage segmentation
(DSC=0.78-0.88 and 0.9, respectively). The proposed deep-learning-based
segmentation of the wrist cartilage from MRI could facilitate research of novel
imaging markers of wrist osteoarthritis to characterize its progression and
response to therapy
A Parametric Study of Radiative Dipole Body Array Coil for 7 Tesla MRI
In this contribution we present numerical and experimental results of a
parametric quantitative study of radiative dipole antennas in a phased array
configuration for efficient body magnetic resonance imaging at 7T via parallel
transmission. For magnetic resonance imaging (MRI) at ultrahigh fields (7T and
higher) dipole antennas are commonly used in phased arrays, particularly for
body imaging targets. This study reveals the effects of dipole positioning in
the array (elevation of dipoles above the subject and inter-dipole spacing) on
their mutual coupling, per and per maximum local
SAR efficiencies as well as the RF-shimming capability. The numerical and
experimental results are obtained and compared for a homogeneous phantom as
well as for a real human models confirmed by in-vivo experiments
A Quantitative Study of a New RF-coil for 7 Tesla Small-Animal Imaging
International audienc
Tunable hybrid metasurfaces for MRI applications
One of many exciting application of metasurfaces is in the magnetic resonance imaging (MRI). Here we demonstrate theoretically and experimentally how to improve substantially the MRI sensitivity by employing the concept of hybrid metasurfaces. We design a novel hybrid metasurface as an array of nonmagnetic metallic wires with high-permittivity dielectric blocks at the edges. We demonstrate that tunability of this metasurface can be achieved via a change of the effective permittivity of blocks near the edges. Moreover, altering the coupling strength between the dielectric and metallic elements allows to obtain nearly homogeneous shapes of the near-field magnetic modes.This work was supported by Ministry of Education and Science of the Russian Federation (Zadanie
No. 3.2465.2017/4.6) and by the Grant of the Government of the Russian Federation (No. 074-U01). AGW acknowledges support by European Research Council Advanced Grant 670629 NOMA MRI and NWO Topsubside
Tunable hybrid metasurfaces for image quality enhancement
Metasurfaces created a new paradigm in the research of artificial electromagnetic structures owing to their potential to overcome many challenges typically associated with bulk metamaterials. However, a majority of demonstrated metasurface structures possess fixed properties, e.g. fixed operational bandwidth or functionality. An active control of metasurface functionalities and bandwidth is highly desirable for engineering an advanced electromagnetic and photonic devices. Here, we suggest and demonstrate experimentally a novel type of metasurface capable of dramatic enhancing the image quality.This work was supported by Russian Science Foundation (Project No. 15-19-20054)
A mechanically tunable and efficient ceramic probe for MR-microscopy at 17 Tesla
International audienc