Literature DB >> 16088075

Noise analysis in magnetic resonance electrical impedance tomography at 3 and 11 T field strengths.

Rosalind Sadleir1, Samuel Grant, Sung Uk Zhang, Byung Il Lee, Hyun Chan Pyo, Suk Hoon Oh, Chunjae Park, Eung Je Woo, Soo Yeol Lee, Ohin Kwon, Jin Keun Seo.   

Abstract

In magnetic resonance electrical impedance tomography (MREIT), we measure the induced magnetic flux density inside an object subject to an externally injected current. This magnetic flux density is contaminated with noise, which ultimately limits the quality of reconstructed conductivity and current density images. By analysing and experimentally verifying the amount of noise in images gathered from two MREIT systems, we found that a carefully designed MREIT study will be able to reduce noise levels below 0.25 and 0.05 nT at main magnetic field strengths of 3 and 11 T, respectively, at a voxel size of 3 x 3 x 3 mm(3). Further noise level reductions can be achieved by optimizing MREIT pulse sequences and using signal averaging. We suggest two different methods to estimate magnetic flux noise levels, and the results are compared to validate the experimental setup of an MREIT system.

Mesh:

Year:  2005        PMID: 16088075     DOI: 10.1088/0967-3334/26/5/023

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  18 in total

1.  High field MREIT: setup and tissue phantom imaging at 11 T.

Authors:  Rosalind Sadleir; Samuel Grant; Sung Uk Zhang; Suk Hoon Oh; Byung Il Lee; Eung Je Woo
Journal:  Physiol Meas       Date:  2006-04-24       Impact factor: 2.833

2.  Can high-field MREIT be used to directly detect neural activity? Theoretical considerations.

Authors:  R J Sadleir; S C Grant; E J Woo
Journal:  Neuroimage       Date:  2010-04-09       Impact factor: 6.556

3.  Direct detection of neural activity in vitro using magnetic resonance electrical impedance tomography (MREIT).

Authors:  Rosalind J Sadleir; Fanrui Fu; Corey Falgas; Stephen Holland; May Boggess; Samuel C Grant; Eung Je Woo
Journal:  Neuroimage       Date:  2017-08-14       Impact factor: 6.556

4.  Multishot echo-planar MREIT for fast imaging of conductivity, current density, and electric field distributions.

Authors:  Munish Chauhan; Rohini Vidya Shankar; Neeta Ashok Kumar; Vikram D Kodibagkar; Rosalind Sadleir
Journal:  Magn Reson Med       Date:  2017-02-16       Impact factor: 4.668

5.  Magnetic-resonance-based measurement of electromagnetic fields and conductivity in vivo using single current administration-A machine learning approach.

Authors:  Saurav Z K Sajib; Munish Chauhan; Oh In Kwon; Rosalind J Sadleir
Journal:  PLoS One       Date:  2021-07-22       Impact factor: 3.240

6.  Evaluation of magnetohydrodynamic effects in magnetic resonance electrical impedance tomography at ultra-high magnetic fields.

Authors:  Atul S Minhas; Munish Chauhan; Fanrui Fu; Rosalind Sadleir
Journal:  Magn Reson Med       Date:  2018-11-19       Impact factor: 4.668

7.  MREIT with SENSE acceleration using a dedicated RF coil design.

Authors:  L Tugan Muftuler; Gang Chen; Mark J Hamamura; Seung Hoon Ha
Journal:  Physiol Meas       Date:  2009-07-30       Impact factor: 2.833

8.  Functional magnetic resonance electrical impedance tomography (fMREIT) sensitivity analysis using an active bidomain finite-element model of neural tissue.

Authors:  Rosalind J Sadleir; Fanrui Fu; Munish Chauhan
Journal:  Magn Reson Med       Date:  2018-05-16       Impact factor: 4.668

9.  Low-Frequency Conductivity Tensor Imaging of the Human Head In Vivo Using DT-MREIT: First Study.

Authors:  Munish Chauhan; Aprinda Indahlastari; Aditya K Kasinadhuni; Michael Schar; Thomas H Mareci; Rosalind J Sadleir
Journal:  IEEE Trans Med Imaging       Date:  2018-04       Impact factor: 10.048

10.  A feasibility study of magnetic resonance electrical impedance tomography for prostate cancer detection.

Authors:  Yang Liu; Yingchun Zhang
Journal:  Physiol Meas       Date:  2014-03-12       Impact factor: 2.833

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