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Calculation of Projection Matrix in Image Reconstruction Based on Neural Network

机译:基于神经网络的图像重建投影矩阵的计算

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The iterative reconstruction algorithms can get better reconstruction result by adding constraints in the case of incomplete or uneven projection. In the iterative reconstruction algorithm, how to obtain the relationship between the reconstructed image and the projected data, namely, projection matrix, is the key to the image reconstruction. In this paper, the neural network algorithm is used to calculate the projection matrix, which gives a solution to a class of problems. In simulation, we use the projection matrix trained by the neural network to achieve the reconstruction, and the results show that the original image can be well reconstructed.
机译:在投影不完整或投影不均匀的情况下,通过添加约束,迭代重建算法可以获得更好的重建结果。在迭代重建算法中,如何获得重建图像与投影数据之间的关系,即投影矩阵,是图像重建的关键。本文采用神经网络算法计算投影矩阵,为一类问题提供了解决方案。在仿真中,我们使用了由神经网络训练的投影矩阵来实现重建,结果表明可以很好地重建原始图像。

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