CT Reconstruction Algorithms with Sparse Radiographs Based on Bayes Estimates

A Bayes estimation method is presented via analyzing CT reconstruction with sparse radiograph data.We transform prior information about target object based on medical treatment anatomy to prior probability density and measurement information to likelihood function,and combine them to get posterior probability density.Through sampling and mean estimates,the expected value is taken as the result of CT reconstruction.The simulation results show that,compared to conventional CT reconstruction methods,the Bayes estimation method has less radiation data,short reconstruction time,good-quality images and high noise resistance.