Unknown

Dataset Information

0

A high-impedance detector-array glove for magnetic resonance imaging of the hand.


ABSTRACT: Densely packed resonant structures used for magnetic resonance imaging (MRI), such as nuclear magnetic resonance phased-array detectors, suffer from resonant inductive coupling, which restricts coil design to fixed geometries, imposes performance limitations, and narrows the scope of MRI experiments to motionless subjects. Here, we report the design of high-impedance detectors, and the fabrication and performance of a wearable detector array for MRI of the hand, that cloak themselves from electrodynamic interactions with neighboring elements. We experimentally verified that the detectors do not suffer from signal-to-noise degradation mechanisms typically observed with the use of traditional low-impedance elements. The detectors are adaptive and can accommodate movement, providing access to the imaging of soft-tissue biomechanics with unprecedented flexibility. The design of the wearable detector glove exemplifies the potential of high-impedance detectors in enabling a wide range of applications that are not well suited to traditional coil designs.

SUBMITTER: Zhang B 

PROVIDER: S-EPMC6405230 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

altmetric image

Publications

A high-impedance detector-array glove for magnetic resonance imaging of the hand.

Zhang Bei B   Sodickson Daniel K DK   Cloos Martijn A MA  

Nature biomedical engineering 20180507 8


Densely packed resonant structures used for magnetic resonance imaging (MRI), such as nuclear magnetic resonance phased-array detectors, suffer from resonant inductive coupling, which restricts coil design to fixed geometries, imposes performance limitations, and narrows the scope of MRI experiments to motionless subjects. Here, we report the design of high-impedance detectors, and the fabrication and performance of a wearable detector array for MRI of the hand, that cloak themselves from electr  ...[more]

Similar Datasets

| S-EPMC3907494 | biostudies-literature
| S-EPMC8630230 | biostudies-literature
| S-EPMC6373455 | biostudies-literature
2018-12-01 | GSE101908 | GEO
| S-EPMC4568182 | biostudies-literature
2023-11-03 | GSE239379 | GEO
| S-EPMC9497728 | biostudies-literature
| S-EPMC3826760 | biostudies-literature
| S-EPMC5063234 | biostudies-literature
| S-EPMC5953275 | biostudies-literature