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.