Abstract
The image reconstruction from projections problem is still the primary challenge for designers of the computed tomography devices. The presented paper describes a new approach to the reconstruction problem, which takes into consideration the statistical conditions of the signals measured in real tomographic scanners. The reconstruction problem is reformulated to the optimization problem. The new form of optimization loss function is proposed. The optimization process is performed using a recurrent neural network. 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., Lorent, A. (2012). A Neuronal Approach to the Statistical Image Reconstruction from Projections Problem. In: Nguyen, NT., Hoang, K., Jȩdrzejowicz, P. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2012. Lecture Notes in Computer Science(), vol 7653. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34630-9_36
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DOI: https://doi.org/10.1007/978-3-642-34630-9_36
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