Using Statistical Algorithms for Image Reconstruction in EIT
The problem with image reconstruction from impedance tomography is an ill-posed inverse problem. To get quantitative information on the change in conductivity, it would be better to use a non-linear model in the differential imaging solution. Statistical methods such as PCR, PLRS, elastic net, Lars,...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2018-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | https://doi.org/10.1051/matecconf/201821002017 |
| Summary: | The problem with image reconstruction from impedance tomography is an ill-posed inverse problem. To get quantitative information on the change in conductivity, it would be better to use a non-linear model in the differential imaging solution. Statistical methods such as PCR, PLRS, elastic net, Lars, SVR were used to reconstruct the image. The discussed techniques can be applied to the problem of electrical tomography. The algorithms used to identify unknown material coefficient. |
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| ISSN: | 2261-236X |