Abstract
Presented paper shows a novel approach to the problem of image reconstruction from projections using recursive Hopfield-type neural network. The reconstruction process is performed during the minimizing of the energy function in this network. Our method is of a great practical use in reconstruction from discrete parallel beam projections. Experimental results show that the appropriately designed neural network is able to reconstruct an image with better quality than obtained from conventional algorithms.
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Cierniak, R. (2006). A Novel Approach to Image Reconstruction from Discrete Projections Using Hopfield-Type Neural Network. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_93
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DOI: https://doi.org/10.1007/11785231_93
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35748-3
Online ISBN: 978-3-540-35750-6
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