Name
Abstract | ||
|---|---|---|
Magnetic resonance electrical property tomography (MREPT) is a new imaging modality to visualize a distribution of admittivity γ = σ+iωε inside the human body where σ and ε denote electrical conductivity and permittivity, respectively. Using B1 maps acquired by an magnetic resonance imaging scanner, it produces cross-sectional images of σ and ε at the Larmor frequency. Since current MREPT methods rely on an assumption of a locally homogeneous admittivity, there occurs a reconstruction error where this assumption fails. Rigorously analyzing the reconstruction error in MREPT, we showed that the error is fundamental and may cause technical difficulties in interpreting MREPT images of a general inhomogeneous object. We performed numerical simulations and phantom experiments to quantitatively support the error analysis. We compared the MREPT image reconstruction problem with that of magnetic resonance electrical impedance tomography (MREIT) to highlight distinct features of both methods to probe the same object in terms of its high- and low-frequency conductivity distributions, respectively. MREPT images showed large errors along boundaries where admittivity values changed whereas MREIT images showed no such boundary effects. Noting that MREIT makes use of the term neglected in MREPT, a novel MREPT admittivity image reconstruction method is proposed to deal with the boundary effects, which requires further investigation on the complex directional derivative in the real Euclidian space [Formula: see text]. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TMI.2011.2171000 | IEEE transactions on medical imaging |
Keywords | Field | DocType |
mrept image reconstruction,bioelectric potentials,magnetic resonance electrical property tomography,electrical conductivity,error analysis,magnetic resonance electrical property tomography (mrept),electric admittance,magnetic resonance electrical impedance tomography (mreit),image reconstruction,larmor frequency,real euclidian space,conductivity,biomedical mri,magnetic resonance electrical impedance tomography,mr based electric property imaging,reconstruction error,permittivity,admittivity distribution,phantoms,b1 map,medical image processing,phantom experiments,nonconstant admittivity,directional derivative,electric conductivity,magnetic resonance image,tomography,low frequency,human body,numerical simulation,magnetic resonance imaging,cross section | Mathematical analysis,Imaging phantom,Artificial intelligence,Directional derivative,Iterative reconstruction,Computer vision,Boundary effects,Euclidean space,Tomography,Larmor precession,Scanner,Nuclear magnetic resonance,Physics | Journal |
Volume | Issue | ISSN |
31 | 2 | 0278-0062 |
Citations | PageRank | References |
12 | 1.17 | 4 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jin Keun Seo | 1 | 376 | 58.65 |
| Min-Oh Kim | 2 | 21 | 2.23 |
| Joon-Sung Lee | 3 | 15 | 1.95 |
| Narae Choi | 4 | 17 | 1.96 |
| Eung Je Woo | 5 | 264 | 72.69 |
| Hyung Joong Kim | 6 | 32 | 6.01 |
| Ohin Kwon | 7 | 183 | 32.17 |
| Dong-Hyun Kim | 8 | 39 | 6.05 |