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

机译:从扇形束投影图像重建的新神经网络算法

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摘要

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 p-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.
机译:神经网络在计算机断层摄影中有一些应用,特别是从投影重建图像。本文介绍了一种使用Hopfield型神经网络解决重构问题的新实用方法。这种重建算法的方法类似于一个转换公式-所谓的p过滤layergram方法。这项工作中提出的方法适用于已经在实践中使用的离散扇形束投影。进行的计算机仿真表明,以这种方式工作的神经网络重构算法在获得的图像质量方面以及在硬件实现速度方面,都优于传统方法。

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