New neural network algorithm for image reconstruction from fan-beam projections

R Cierniak - Neurocomputing, 2009 - Elsevier
Neurocomputing, 2009Elsevier
Neural networks have some applications in computerized tomography, in particular to
reconstruct an image from projections. The presented paper describes a new practical
approach to the reconstruction problem using a Hopfield-type neural network. The
methodology of this reconstruction algorithm resembles a transformation formula—the so-
called ρ-filtered layergram method. The method proposed in this work is adapted for discrete
fan beam projections, already used in practice. Performed computer simulations show that …
Neural networks have some applications in computerized tomography, in particular to reconstruct an image from projections. The presented paper describes a new practical approach to the reconstruction problem using a Hopfield-type neural network. The methodology of this reconstruction algorithm resembles a transformation formula—the so-called ρ-filtered layergram method. The method proposed in this work is adapted for discrete fan beam projections, already used in practice. Performed computer simulations show that the neural network reconstruction algorithm designed to work in this way outperforms conventional methods in obtained image quality, and in perspective of hardware implementation in the speed of the reconstruction process.
Elsevier
以上显示的是最相近的搜索结果。 查看全部搜索结果