Name
Abstract | ||
|---|---|---|
Typical microwave tomographic techniques reconstruct the real part of the permittivity with much greater accuracy as compared to the imaginary part. In this paper, we propose a method to mitigate the imbalance between the reconstructed complex permittivity components and increase the accuracy of the overall image recovery. To do so, the complex permittivity in the imaging domain is expressed as a weighted sum of a few preselected permittivities, close to the range of the expected values. To obtain the permittivity weights, a Gauss–Newton algorithm is employed. Image reconstructions from simulated and experimental data for different biomedical phantoms are presented. Results show that the proposed method leads to excellent reconstruction with balanced real and imaginary parts, across different scenarios. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TBME.2019.2936125 | IEEE Transactions on Biomedical Engineering |
Keywords | DocType | Volume |
Complex permittivity,Gauss-Newton algorithm,inverse problems,microwave tomographic imaging | Journal | 67 |
Issue | ISSN | Citations |
5 | 0018-9294 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Md Asiful Islam | 1 | 0 | 0.34 |
| Asimina Kiourti | 2 | 22 | 8.01 |
| John L. Volakis | 3 | 25 | 7.53 |