Conductivity image enhancement in MREIT using adaptively weighted spatial averaging filter

BioMedical Engineering OnLine

Tong In Oh¹  Hyung Joong Kim¹  Woo Chul Jeong¹  Hun Wi¹  Oh In Kwon²  Eung Je Woo¹ 

[1] Department of Biomedical Engineering and Impedance Imaging Research Center, Kyung Hee University, 446-701 Yongin, Korea

[2] Department of Mathematics, Konkuk University, 143-701 Seoul, Korea

关键词: Adaptively weighted spatial averaging filter;    Denoising method;    Noise estimation;    Conductivity image;    Magnetic resonance electrical impedance tomography;   

Others  :  1084799
DOI  :  10.1186/1475-925X-13-87

 received in 2014-04-20, accepted in 2014-06-24,  发布年份 2014

【 摘 要 】

Background

In magnetic resonance electrical impedance tomography (MREIT), we reconstruct conductivity images using magnetic flux density data induced by externally injected currents. Since we extract magnetic flux density data from acquired MR phase images, the amount of measurement noise increases in regions of weak MR signals. Especially for local regions of MR signal void, there may occur excessive amounts of noise to deteriorate the quality of reconstructed conductivity images. In this paper, we propose a new conductivity image enhancement method as a postprocessing technique to improve the image quality.

Methods

Within a magnetic flux density image, the amount of noise varies depending on the position-dependent MR signal intensity. Using the MR magnitude image which is always available in MREIT, we estimate noise levels of measured magnetic flux density data in local regions. Based on the noise estimates, we adjust the window size and weights of a spatial averaging filter, which is applied to reconstructed conductivity images. Without relying on a partial differential equation, the new method is fast and can be easily implemented.

Results

Applying the novel conductivity image enhancement method to experimental data, we could improve the image quality to better distinguish local regions with different conductivity contrasts. From phantom experiments, the estimated conductivity values had 80% less variations inside regions of homogeneous objects. Reconstructed conductivity images from upper and lower abdominal regions of animals showed much less artifacts in local regions of weak MR signals.

Conclusion

We developed the fast and simple method to enhance the conductivity image quality by adaptively adjusting the weights and window size of the spatial averaging filter using MR magnitude images. Since the new method is implemented as a postprocessing step, we suggest adopting it without or with other preprocessing methods for application studies where conductivity contrast is of primary concern.

【 授权许可】

   
2014 Oh et al.; licensee BioMed Central Ltd.

【 图 表 】

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