Conductivity image enhancement in MREIT using adaptively weighted spatial averaging filter
BioMedical Engineering Online, ISSN: 1475-925X, Vol: 13, Issue: 1, Page: 87
2014
- 2Citations
- 7Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations2
- Citation Indexes2
- Captures7
- Readers7
Article Description
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. © 2014 Oh et al.; licensee BioMed Central Ltd.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84902938077&origin=inward; http://dx.doi.org/10.1186/1475-925x-13-87; http://www.ncbi.nlm.nih.gov/pubmed/24970640; https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/1475-925X-13-87; http://biomedical-engineering-online.biomedcentral.com/articles/10.1186/1475-925X-13-87; http://dx.doi.org/10.1186/1475-925X-13-87; https://dx.doi.org/10.1186/1475-925X-13-87
Springer Science and Business Media LLC
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