USING NEURAL NETWORKS AND DEEP LEARNING ALGORITHMS IN ELECTRICAL IMPEDANCE TOMOGRAPHY
Grzegorz Kłosowski
g.klosowski@pollub.plLublin University of Technology, Faculty of Management, Department of Organization of Enterprise (Poland)
Tomasz Rymarczyk
Research and Development Center, Netrix S.A., Lublin; University of Economics and Innovation in Lublin (Poland)
Abstract
This paper refers to the cases of the use of Artificial Neural Networks and Convolutional Neural Networks in impedance tomography. Machine Learning methods can be used to teach computers different technical problems. The efficient use of conventional artificial neural networks in tomography is possible able to effectively visualize objects. The first step of implementation Deep Learning methods in Electrical Impedance Tomography was performed in this work.
Keywords:
Imaging tomography, Multilayer Perceptron, Deep Learning, Convolutional Neural NetworksReferences
Bladt E. et al.: Electron tomography based on highly limited data using a neural network reconstruction technique. Ultramicroscopy 158/2015, 81–88.
Google Scholar
Buduma N., Locascio N.: Fundamentals of Deep Learning. Designing Next-Generation Machine Intelligence Algorithms. O'Reilly Media, 2017.
Google Scholar
Durairaj D. C., Krishna M. C., Murugesan R.: A neural network approach for image reconstruction in electron magnetic resonance tomography. Computers in biology and medicine 37(10)/2007, 1492–1501.
Google Scholar
Egmont-Petersen M., Ridder de D., Handels H.: Image processing with neural networks – a review. Pattern Recognition 35/2002, 2279–2301.
Google Scholar
Minnett R. C. J. et al.: Neural network tomography: Network replication from output surface geometry. Neural Networks 24(5)/2011, 484–492.
Google Scholar
Pelt D. M., Batenburg K. J.: Fast tomographic reconstruction from limited data using artificial neural networks. IEEE Trans. Image Process. 22/2013, 5238–5251.
Google Scholar
Rybak G., Chaniecki Z., Grudzień K., Romanowski A., Sankowski D.: Non–invasive methods of industrial process control. Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 4(3)/2014, 41–45.
Google Scholar
Rymarczyk T.: New Methods to Determine Moisture Areas by Electrical Impedance Tomography. International Journal of Applied Electromagnetics and Mechanics 37(1-2)/2016, 79–87.
Google Scholar
Stasiak M. et al.: 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 31(8)/2007, 713–720.
Google Scholar
Tapson J.: Neural Networks and Stochastic Search Methods Applied to Capacitive Tomography. IFAC Proceedings Volumes 30(7)/1997, 631–634.
Google Scholar
Tapson J.: Neural networks and stochastic search methods applied to industrial capacitive tomography. Control Engineering Practice 7(1)/1999, 117–121.
Google Scholar
Tchorzewski P., Rymarczyk T., Sikora J.: Using Topological Algorithms to Solve Inverse Problem in Electrical Impedance Tomography. International Interdisciplinary Phd Workshop 2016, 46–50.
Google Scholar
Wang J. et al.: Neural-network approach for optical tomography. Signal processing, 86(9)/2006, 2495–2502.
Google Scholar
Authors
Grzegorz Kłosowskig.klosowski@pollub.pl
Lublin University of Technology, Faculty of Management, Department of Organization of Enterprise Poland
Authors
Tomasz RymarczykResearch and Development Center, Netrix S.A., Lublin; University of Economics and Innovation in Lublin Poland
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