Publication detail

Image Reconstuction in Electrical Impedance Tomography with Total Variation and Gauss-Newton Algorithm

KOUAKOUO NOMVUSSI, S. MIKULKA, J.

Original Title

Image Reconstuction in Electrical Impedance Tomography with Total Variation and Gauss-Newton Algorithm

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

In this paper, the Total Variation and Gauss-Newton algorithms are used to reconstruct the conductivity maps in Electrical Impedance Tomography. The Total Variation gives better results than the Gauss-Newton algorithm. The quality of the reconstructed conductivity maps is clear and almost identical to the image of the forward problem when using the Total Variation method on the whole dataset. In contrast, the Gauss-Newton algorithm provides a smooth image of the object without a perfect reconstruction of its edges. The correlation coefficient of the Total Variation is higher than that of the Gauss-Newton method. The drawback of these two algorithms is their inability to reconstruct the image from noisy data.

Keywords

Total Variation; Gauss Newton; EIT; EIDORS

Authors

KOUAKOUO NOMVUSSI, S.; MIKULKA, J.

Released

25. 4. 2023

ISBN

978-80-214-6153-6

Book

Proceedings I of the 29th Student EEICT 2023

Pages from

1

Pages to

5

Pages count

5

BibTex

@inproceedings{BUT183567,
  author="Serge Ayme {Kouakouo Nomvussi} and Jan {Mikulka}",
  title="Image Reconstuction in Electrical Impedance Tomography with Total Variation and Gauss-Newton Algorithm",
  booktitle="Proceedings I of the 29th Student EEICT 2023",
  year="2023",
  pages="1--5",
  isbn="978-80-214-6153-6"
}