Magnetic resonance electrical property tomography (MREPT) is a new imaging modality to visualize a distribution of admittivity γ=σ+iω inside the human body where σ and denote electrical conductivity and permittivity, respectively. Using B1 maps acquired by an magnetic resonance imaging scanner, it produces cross-sectional images of σ and 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 BBR3.
Bibliographical noteFunding Information:
Manuscript received May 20, 2011; revised July 26, 2011, August 23, 2011; accepted September 26, 2011. Date of publication October 10, 2011; date of current version February 03, 2012. The work of J. K. Seo was supported by the WCU program through MEST/NRF (R31-2008-000-10049-0). The work of E. J. Woo was supported by the NRF grant funded by the Korea government (MEST) (20100018275). The work of D. H. Kim was supported by the KOSEF grant funded by the Korea government (MEST) (2010-0016421). Asterisk indicates corresponding author.
All Science Journal Classification (ASJC) codes
- Radiological and Ultrasound Technology
- Computer Science Applications
- Electrical and Electronic Engineering