Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. Global maxwell tomography using an 8-channel radiofrequency coil: Simulation results for a tissue-mimicking phantom at 7T

Global maxwell tomography using an 8-channel radiofrequency coil: Simulation results for a tissue-mimicking phantom at 7T

Thumbnail Image
Download
Name

Paper.pdf

Description
Accepted version
Size

168.92 KB

Format

Adobe PDF

Checksum (MD5)

f269c3fc7a0e0e9feb964100ab2f4bd7

sword-2020-12-07T16:30:49.original.xml (130 B)
Original SWORD entry document
Author(s)
Serrallés, José E.C.
•
Daniel, Luca
•
White, Jacob K.
Date Issued
July 2019
Journal
2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings
Publisher
IEEE
Citation
Giannakopoulos, Ilias I. et al. “Global maxwell tomography using an 8-channel radiofrequency coil: Simulation results for a tissue-mimicking phantom at 7T.” Paper presented in 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, Atlanta, GA, 7-12 July 2019, IEEE © 2019 The Author(s)
Version
Author's final manuscript
Abstract
We simulated a Global Maxwell Tomography experiment for the estimation of electrical properties in a numerical tissue-mimicking phantom using a decoupled 8 channel radiofrequency coil designed for 7 Tesla magnetic resonance scanners. The goal of this work was to investigate whether the orthogonality of the coil's transmit fields (b1+ measurements) is required to ensure accurate results. We demonstrated a normalized root mean squared error smaller than 0.6% with respect to the true electrical properties distribution. Our results showed that electrical properties reconstruction with Global Maxwell Tomography is accurate and robust.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
http://creativecommons.org/licenses/by-nc-sa/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/130074
DOI of Published Version
https://doi.org/10.1109/APUSNCURSINRSM.2019.8889009
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.