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A Conjugate Gradient Algorithm for Density Reconstruction in High-energy X-ray Radiography
XU Hai-bo, WEI Su-hua
CHINESE JOURNAL OF COMPUTATIONAL PHYSICS    2006, 23 (2): 144-150.  
Abstract256)      PDF (351KB)(1135)      
A point spread function and a cost function are obtained with a physical analysis of the high-energy x-ray radiography. Taking the French Test Object model as an example, the conjugate gradient algorithm is applied to the density reconstruction in high-energy x-ray radiography, and the result is satisfactory. The algorithm starts at a simulation in radiography and searches for a maximum likelihood by comparing the simulated radiographs with the measured radiographs. To some extent, the algorithm overcomes the uncertainty in eliminating the blurting effects through a deconvolution process in reconstruction methods.
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