EIDORS

EIDORS is a MATLAB based software library that aims to provide free software algorithms for forward modelling and inverse solutions of Electrical Impedance and (to some extent) Diffusion-based Optical Tomography, in medical, industrial and geophysical settings and to share data and promote collaboration. Release 3.8 of EIDORS builds upon a strong foundation in reconstruction algorithms, adding and improving a number of aspects.


References in zbMATH (referenced in 21 articles )

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  1. Benyuan Liu; Bin Yang; Canhua Xu; Junying Xia; Meng Dai; Zhenyu Ji; Fusheng You; Xiuzhen Dong; Xuetao Shi; Feng Fu: pyEIT: A python based framework for Electrical Impedance Tomography (2018) not zbMATH
  2. Chada, Neil K.; Iglesias, Marco A.; Roininen, Lassi; Stuart, Andrew M.: Parameterizations for ensemble Kalman inversion (2018)
  3. Harrach, Bastian; Minh, Mach Nguyet: Monotonicity-based regularization for phantom experiment data in electrical impedance tomography (2018)
  4. Ren, Shangjie; Soleimani, Manuchehr; Xu, Yaoyuan; Dong, Feng: Inclusion boundary reconstruction and sensitivity analysis in electrical impedance tomography (2018)
  5. Crabb, M. G.: Convergence study of (2D) forward problem of electrical impedance tomography with high-order finite elements (2017)
  6. Dunlop, Matthew M.; Iglesias, Marco A.; Stuart, Andrew M.: Hierarchical Bayesian level set inversion (2017)
  7. Suryanto, B.; Saraireh, D.; Kim, J.; McCarter, W. J.; Starrs, G.; Taha, H. M.: Imaging water ingress into concrete using electrical resistance tomography (2017)
  8. Aykroyd, Robert G.; Barber, Stuart; Miller, Luke R.: Classification of multiple time signals using localized frequency characteristics applied to industrial process monitoring (2016)
  9. Dunlop, Matthew M.; Stuart, Andrew M.: The Bayesian formulation of EIT: analysis and algorithms (2016)
  10. Iglesias, Marco A.: A regularizing iterative ensemble Kalman method for PDE-constrained inverse problems (2016)
  11. Adler, Andy; Gaburro, Romina; Lionheart, William: Electrical impedance tomography (2015)
  12. Harrach, Bastian: Interpolation of missing electrode data in electrical impedance tomography (2015)
  13. Maire, Sylvain; Simon, Martin: A partially reflecting random walk on spheres algorithm for electrical impedance tomography (2015)
  14. Simon, Martin: Bayesian anomaly detection in heterogeneous media with applications to geophysical tomography (2014)
  15. Nasehi Tehrani, J.; McEwan, Alistair L.; Jin, Craig; van Schaik, André: (L^1) regularization method in electrical impedance tomography by using the (L^1)-curve (Pareto frontier curve) (2012)
  16. Tehrani, J. Nasehi; Jin, C.; McEwan, A. L.: Modelling of an oesophageal electrode for cardiac function tomography (2012)
  17. Zhang, Yan; Passmore, Peter J.; Bayford, Richard H.: Visualization of multidimensional and multimodal tomographic medical imaging data, a case study (2009)
  18. Ijaz, Umer Zeeshan; Khambampati, Anil Kumar; Lee, Jeong Seong; Kim, Sin; Kim, Kyung Youn: Nonstationary phase boundary estimation in electrical impedance tomography using unscented Kalman filter (2008)
  19. Graham, B. M.; Adler, A.: A nodal Jacobian inverse solver for reduced complexity EIT reconstructions (2006)
  20. Fedele, F.; Laible, J. P.; Eppstein, M. J.: Coupled complex adjoint sensitivities for frequency-domain fluorescence tomography: Theory and vectorized implementation (2003)

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