Hyperparameter Algorithms in Electrical Impedance Tomography for Rotational Data

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Rotational electrical impedance tomography provides novel possibilities for multimodal imaging. This could be especially useful in tissue engineering studies where non-destructive and label-free imaging is needed. In difference electrical impedance tomography, the change in conductivity distribution between two samples or states is reconstructed from boundary measurements. Typically, regularization is employed in the solution to tackle the ill-posedness of the problem. The amount of regularization is controlled by a hyperparameter value that is commonly found by subjective and time consuming heuristic selection. In order to find an automatized method that works with rotational data, three state-of-the-art methods for hyperparameter selection were investigated: BestRes, L-Curve and the averaged signal-to-noise ratio (SNR¯ ) as noise performance metric. These were tested with conventional and rotational experimental data. The results show that SNR¯ was the only method that provided good image quality with rotational data.

Original languageEnglish
Title of host publication8th European Medical and Biological Engineering Conference
Subtitle of host publicationProceedings of the EMBEC 2020, November 29 – December 3, 2020 Portorož, Slovenia
EditorsTomaz Jarm, Aleksandra Cvetkoska, Samo Mahnič-Kalamiza, Damijan Miklavcic
Place of PublicationCham
Number of pages13
ISBN (Electronic)978-3-030-64610-3
ISBN (Print)978-3-030-64609-7
Publication statusPublished - 2021
Publication typeA4 Article in conference proceedings
EventEuropean Medical and Biological Engineering Conference - Portorož, Slovenia
Duration: 29 Nov 20203 Dec 2020

Publication series

NameIFMBE Proceedings
ISSN (Print)1680-0737
ISSN (Electronic)1433-9277


ConferenceEuropean Medical and Biological Engineering Conference
Abbreviated titleEMBEC


  • Electrical impedance tomography
  • Hyperparameter
  • Regularization parameter
  • Rotational EIT

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Bioengineering
  • Biomedical Engineering


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