Abstract
This paper presents a novel neural network approach to the problem of image reconstruction from projections obtained by spiral tomography scanner. The reconstruction process is performed during the minimizing of the energy function in recurrent neural network. Our method is of a great practical use in reconstruction from discrete cone-beam projections. Experimental results show that the appropriately designed neural network is able to reconstruct an image with better quality than obtained from used commercial conventional algorithms.
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Cierniak, R. (2010). A Three-Dimentional Neural Network Based Approach to the Image Reconstruction from Projections Problem. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2010. Lecture Notes in Computer Science(), vol 6113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13208-7_63
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DOI: https://doi.org/10.1007/978-3-642-13208-7_63
Publisher Name: Springer, Berlin, Heidelberg
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