Performance Evaluation Of Phase Retrieval Methods For In-line Phase-contrast X-ray Imaging

Phase contrast X-ray imaging techniques have shown the ability to overcome the weakness of the low sensitivity of conventional X-ray imaging.Among them,in-line phase contrast imaging,blessed with simplicity of arrangement,is deemed to be a promising technique in clinical application.In order to apply the technique to 3D imaging,phase retrieval is needed to obtain phase information from phase contrast images.Numerous phase-retrieval algorithms have been developed,which could be generally divided into two categories: the direct algorithms and the indirect ones.Based on different physical assumptions,the existing direct phase-retrieval algorithms excel at computation time but suffer from instability.The theories of these phase-retrieval algorithms are mostly proposed on the basis of ideal imaging conditions.However,in practice,both detector resolution and system noise would have influence on the performance of these phase-retrieval algorithms.To investigate such influence,we designed numerical simulations with Gaussian shaped detectors varying in the full width at half maximum(FWHM)and system noise at different levels.The performance of the phase-retrieval methods under such conditions was evaluated by the root mean square error(RMSE).The results demonstrated that an increase in the detector FWHM or noise level degrades the effect of phase retrieval,especially for objects in small size.The indirect phase-retrieval algorithms,usually iterative regularization algorithms,employ prior conditions to obtain relatively stable results.Based on the iterative regularization algorithms,we proposed a phase retrieval algorithm considering system transfer function compensation.The algorithm showed the ability to improve the resolution of the phase-retrieval results of both simulated and actual phase-contrast images.