Principal component analysis and artificial neural network approach to electrical impedance tomography problems approximated by multi-region boundary element method

Engineering Analysis with Boundary Elements

Volumn 31, Issue 8, 2007, Pages 713-720

  Stasiak, Magdalena ^a   Sikora, Jan ^b   Filipowicz, Stefan F ^b   Nita, Konrad ^b  

^a LODZ UNIVERSITY OF TECHNOLOGY   (Poland)

^b WARSAW UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Artificial neural network; Boundary element methods; Impedance tomography; Principal component analysis

Indexed keywords

BOUNDARY ELEMENT METHOD; DATA REDUCTION; ELECTRIC IMPEDANCE; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS; REAL TIME SYSTEMS;

ELECTRICAL IMPEDANCE TOMOGRAPHY (EIT); PERMITTIVITY DISTRIBUTION;

TOMOGRAPHY;

EID: 34347221886     PISSN: 09557997     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enganabound.2006.12.003     Document Type: Article

References (25)

1. Clay M.T., and Ferree T.C. Weighted regularization in EIT with applications acute cerebral stroke. IEEE Trans Med Imaging 21 6 (2002) 629-637
2. Fear E.C., Hagness S.C., Meaney P.M., Okoniewski M., and Stuchly M.A. Enhancing breast tumor detection with near-field imaging. IEEE Microwave Mag (2002)
3. Malich A., Fritsch T., Anderson R., Boehm T., Freesmeyer M.G., Fleck M., et al. Electrical impedance scanning for classifying suspicious breast lesion: first results. Eur Radiol 10 (2000) 1555-1561
4. Aliabadi M.H. The boundary element method vol. 2 (2002), Wiley, New York
5. Sikora J., Zacharopoulos A., Douiri A., Schweiger M., Horesh L., Arridge S.R., et al. Diffuse photon propagation in multilayered geometries. Phys Med Biol 51 (2006) 497-516
6. Saulnier GJ, Blue RS, Newell JC, Isaacson D, Edic PM. Electrical impedance tomography. IEEE Signal Process Mag 2001;31-43.
7. Levy S., Adam D., and Brester Y. Electromagnetic impedance tomography (EMIT): a new method for impedance imaging. IEEE Trans Med Imaging 21 6 (2002) 676-687
8. Yerworth R, Horesh L, Bayford RH, Tizzard A, Holder DS. Robustness of linear and nonlinear reconstruction algorithms for brain EITS. Proceedings of the XIIth international conference on electrical bioimpedance and V electrical impedance tomography, vol. 2, Poland, 2004. p. 499-502.
9. Frangi A.F., Riu P.J., Rosell J., and Viergever M.A. Propagation of measurement noise through backprojection reconstruction in electrical impedance tomography. IEEE Trans Med Imaging 21 6 (2002) 566-578
10. Polydorides N., Lionheart W.R.B., and McCann H. Krylov subspace iterative techniques: on the detection of brain activity with electrical impedance tomography. IEEE Trans Med Imaging 21 6 (2002) 596-603
11. Hsiao Ch., Chahine G., and Gumerov N. Application of hybrid genetic/powell algorithm and a boundary element method to electrical impedance tomography. J Comput Phys 173 (2001) 433-454
12. Giza Z, Filipowicz SF, Sikora J. Simulated annealing in electrical impedance tomography. Conference on inverse problems, Hong Kong, January 2002. p. 336-43.
13. Aykroyd RG, Cattle BA, West RM. Boundary element methods and Markov chain Monte Carlo for object location applied to electrical tomography problems. Third international symposium on process tomography, Poland, 2004. p. 11-4.
14. Ratajewicz-Mikolajczak E., and Sikora J. Neural networks method for identification of objects behind the screen. IEEE Trans Med Imaging 21 6 (2002) 613-619
15. Waristo W, Fan LS. Development of 3-dimensional electrical capacitance tomography based on neural network multi-criterion optimization image reconstruction. Third world congress on industrial process tomography, Canada, 2003. p. 391-6.
16. Tidswell T., Gibson A., Bayford R.H., and Holder D.S. Three-dimensional electrical impedance tomography of human brain activity. NeuroImage 13 2 (2001)
17. de Munk J.C., Faes T.J.C., and Heethaar R.M. The boundary element method in the forward and inverse problem of electrical impedance tomography. IEEE Trans Biomed Eng 47 6 (2000) 792-800
18. Ferguson A.S., and Stroink G. Factors affecting the accuracy of the boundary element method in the forward problem-calculating surface potentials. IEEE Trans Biomed Eng 44 11 (1997)
19. Frijns J., de Snoo S., and Schoonhoven R. Improving the accuracy of the boundary element method by the use of second-order interpolation functions. IEEE Trans Biomed Eng 47 10 (2000) 1336-1346
20. Cichocki A., and Amari S. Adaptive blind signal and image processing (2002), Wiley, New York
21. Jolliffe IT. Principal component analysis. Springer series in statistics, 1986.
22. Yorkey T.J., Webster J.G., and Tompkins W.J. Comparing reconstruction algorithms for electrical impedance tomography. IEEE Trans Biomed Eng 34 11 (1987) 843-851
23. Lisboa P.J.G., Ifeachor E.C., and Szczepaniak P.S. Artificial neural networks in biomedicine (2000), Springer, London
24. Egmont-Petersen M., de Ridder D., and Handels H. Image processing with neural network-a review. Pattern Recognition 35 (2002) 2279-2301
25. Stasiak M, Siwek K, Sikora R, Filipowicz SF, Sikora J. The combination of principal component analysis with neural network as a highly efficient 3D EIT solution. Proceedings of third world congress on industrial process tomography, Canada, 2003. p. 664-70.