CT image reconstruction by the Boltzmann machine

Abstract

The Boltzmann machine model is used in CT image reconstruction from four projections. The system is based on Boltzmann simulated annealing for adaptation of pixel values. As the temperature is decreased, the gray level of images is increased exponentially to 256. Satisfactory agreement between the original and reconstructed images was obtained in simulation, and the results obtained are compared to those obtained by the well-known algebraic reconstruction technique (ART), and it was found that the neural network method is more effective than ART when the number of projection directions is very limited.