Quantitative Conductivity Estimation Error due to Statistical Noise in Complex B1+ Map.
10.13104/jksmrm.2014.18.4.303
- Author:
Jaewook SHIN
1
;
Joonsung LEE
;
Min Oh KIM
;
Narae CHOI
;
Jin Keun SEO
;
Dong Hyun KIM
Author Information
1. Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea. donghyunkim@yonsei.ac.kr
- Publication Type:Original Article
- Keywords:
MREPT;
Conductivity mapping;
Noise analysis
- MeSH:
Evaluation Studies as Topic;
Magnetic Resonance Imaging;
Noise*;
Radius;
Signal-To-Noise Ratio
- From:Journal of the Korean Society of Magnetic Resonance in Medicine
2014;18(4):303-313
- CountryRepublic of Korea
- Language:English
-
Abstract:
PURPOSE: In-vivo conductivity reconstruction using transmit field (B1+) information of MRI was proposed. We assessed the accuracy of conductivity reconstruction in the presence of statistical noise in complex B1 + map and provided a parametric model of the conductivity-to-noise ratio value. MATERIALS AND METHODS: The B1+ distribution was simulated for a cylindrical phantom model. By adding complex Gaussian noise to the simulated B1+ map, quantitative conductivity estimation error was evaluated. The quantitative evaluation process was repeated over several different parameters such as Larmor frequency, object radius and SNR of B1+ map. A parametric model for the conductivity-to-noise ratio was developed according to these various parameters. RESULTS: According to the simulation results, conductivity estimation is more sensitive to statistical noise in B1+ phase than to noise in B1+ magnitude. The conductivity estimate of the object of interest does not depend on the external object surrounding it. The conductivity-to-noise ratio is proportional to the signal-to-noise ratio of the B1+ map, Larmor frequency, the conductivity value itself and the number of averaged pixels. To estimate accurate conductivity value of the targeted tissue, SNR of B1+ map and adequate filtering size have to be taken into account for conductivity reconstruction process. In addition, the simulation result was verified at 3T conventional MRI scanner. CONCLUSION: Through all these relationships, quantitative conductivity estimation error due to statistical noise in B1+ map is modeled. By using this model, further issues regarding filtering and reconstruction algorithms can be investigated for MREPT.
