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 |
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EDP Sciences
2018-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | https://doi.org/10.1051/matecconf/201821002017 |
| _version_ | 1818413749566963712 |
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| author | Rymarczyk Tomasz Kozłowski Edward |
| author_facet | Rymarczyk Tomasz Kozłowski Edward |
| author_sort | Rymarczyk Tomasz |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-14T11:08:09Z |
| format | Article |
| id | doaj.art-46c6badf521244888e3212488714fad7 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-14T11:08:09Z |
| publishDate | 2018-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-46c6badf521244888e3212488714fad72022-12-21T23:04:26ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-012100201710.1051/matecconf/201821002017matecconf_cscc2018_02017Using Statistical Algorithms for Image Reconstruction in EITRymarczyk TomaszKozłowski EdwardThe 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.https://doi.org/10.1051/matecconf/201821002017 |
| spellingShingle | Rymarczyk Tomasz Kozłowski Edward Using Statistical Algorithms for Image Reconstruction in EIT MATEC Web of Conferences |
| title | Using Statistical Algorithms for Image Reconstruction in EIT |
| title_full | Using Statistical Algorithms for Image Reconstruction in EIT |
| title_fullStr | Using Statistical Algorithms for Image Reconstruction in EIT |
| title_full_unstemmed | Using Statistical Algorithms for Image Reconstruction in EIT |
| title_short | Using Statistical Algorithms for Image Reconstruction in EIT |
| title_sort | using statistical algorithms for image reconstruction in eit |
| url | https://doi.org/10.1051/matecconf/201821002017 |
| work_keys_str_mv | AT rymarczyktomasz usingstatisticalalgorithmsforimagereconstructionineit AT kozłowskiedward usingstatisticalalgorithmsforimagereconstructionineit |