EIDORS
Initial release1999 (1999)
Stable release
3.10 / December 2019 (2019-12)
Written inMATLAB/GNU Octave, Objective C and C++
Operating systemWindows, Linux, SunOS/Solaris
LicenseGNU GPL 2 or 3
Websiteeidors.org

EIDORS is an open-source software tool box written mainly in MATLAB/GNU Octave designed primarily for image reconstruction from electrical impedance tomography (EIT) data, in a biomedical, industrial or geophysical setting. The name was originally an acronym for Electrical Impedance Tomography and Diffuse Optical Reconstruction Software. While the name reflects the original intention to cover image reconstruction of data from the mathematically similar near infra red diffuse optical imaging, to date there has been little development in that area.

The project was launched in 1999 [1] with a Matlab code for 2D EIT reconstruction which had its origin in the PhD thesis of Marko Vauhkonen and the work of his supervisor Jari Kaipio at the University of Kuopio. While Kuopio also developed a three dimensional EIT code [2] this was not released as open-source. Instead the three dimensional version of EIDORS was developed from work done at UMIST (now University of Manchester) by Nick Polydorides and William Lionheart.[3]

Methods and models

The forward models in EIDORS use the finite element method and this requires mesh generation for sometimes irregular objects (such as human bodies), and the meshing needs to reflect the electrodes used to drive and measure current in EIT. For this purpose an interface was developed to the Netgen Mesh Generator.

History

As the project grew there was a desire to incorporate forward modelling and reconstruction code from a variety of groups and Andy Adler and Lionheart developed a more extensible software system.[4] The most recent version is 3.10, released in Dec, 2019.

The EIDORS project also includes a repository of EIT data distributed under open-source licenses.

Applications

EIDORS has been extensively used in biomedical applications of EIT, including lung imaging,[5] measuring cardiac output.[6] It has been used for investigation of imaging electrical activity in the brain,[7] and monitoring conductivity changes during radio-frequency ablation.[8] Outside medical imaging the toolbox has been used in process tomography,[9] geophysics [10] and materials science.[11]

References

  1. ↑ W R B Lionheart, S R Arridge, M Schweiger, M Vauhkonen and J P Kaipio, Electrical Impedance and Diffuse Optical Tomography Reconstruction Software, Proceedings of the 1st World Congress on Industrial Process Tomography, pp 474–477, Buxton, Derbyshire, 1999
  2. ↑ Vauhkonen, P. J., Vauhkonen, M., Savolainen, T., & Kaipio, J. P. (1999). Three-dimensional electrical impedance tomography based on the complete electrode model. Biomedical Engineering, IEEE Transactions on, 46(9), 1150–1160.
  3. ↑ Polydorides N, Lionheart WRB, A Matlab toolkit for three-dimensional electrical impedance tomography: a contribution to the Electrical Impedance and Diffuse Optical Reconstruction Software project, Meas. Sci. Technol. 13 (December 2002) 1871–1883
  4. ↑ A Adler and W R B Lionheart, Uses and abuses of EIDORS: An extensible software base for EIT, Physiol Meas 27, S25–S42, 2006.
  5. ↑ A. Biguri; B. Grychtol; A. Adler; M. Soleimani (2015). "Tracking boundary movement and exterior shape modelling in lung EIT imaging" (PDF). Physiological Measurement. 36 (6): 1119–35. Bibcode:2015PhyM...36.1119B. doi:10.1088/0967-3334/36/6/1119. PMID 26007150. S2CID 30064176.
  6. ↑ Martin Proença et al., Influence of heart motion on cardiac output estimation by means of electrical impedance tomography: a case study Physiological Measurement 2015 36 1075
  7. ↑ Kirill Y. Aristovich et al Imaging fast electrical activity in the brain with electrical impedance tomography NeuroImage 2016 124 204
  8. ↑ Hun Wi et al. Real-time conductivity imaging of temperature and tissue property changes during radiofrequency ablation: An ex vivo model using weighted frequency difference Bioelectromagnetics 2015 36 277
  9. ↑ Kent Wei et al., ITS Reconstruction Tool-Suite: An inverse algorithm package for industrial process tomography Flow Measurement and Instrumentation 2015 46 292
  10. ↑ Suze-Anne Korteland and Timo Heimovaara, Quantitative inverse modelling of a cylindrical object in the laboratory using ERT: An error analysis Journal of Applied Geophysics 2015
  11. ↑ Gerard J. Gallo and Erik T. Thostenson Spatial damage detection in electrically anisotropic fiber-reinforced composites using carbon nanotube networks Composite Structures 2015
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