A multi-material diagnosis method based on high-energy proton radiography

Diagnosis of fluids is extremely significant at high temperatures and high pressures.As an advanced imaging technique,high-energy proton radiography has great potential for application to the diagnosis of high-density fluids.In high-energy proton radiography,an angular collimator can control the proton flux and thus enable material diagnosis and reconstruction of density.In this paper,we propose a multimaterial diagnostic method using angular collimators.The method is verified by reconstructing the density distribution from the proton flux obtained via theoretical calculations and numerical simulations.We simulate a 20 GeV proton imaging system using the Geant4 software toolkit and obtain the characteristic parameters of single-material objects.We design several concentric spherical objects to verify the method.We discuss its application to detonation tests.The results show that this method can determine the material and boundary information about each component of a multi-material object.Thus,it can be used to diagnose a mixed material and reconstruct densities in a detonation.

HYBRID REGULARIZED CONE-BEAM RECONSTRUCTION FOR AXIALLY SYMMETRIC OBJECT TOMOGRAPHY

In this paper,we consider 3 D tomographic reconstruction for axially symmetric objects from a single radiograph formed by cone-beam X-rays.All contemporary density reconstruction methods in high-energy X-ray radiography are based on the assumption that the cone beam can be treated as fan beams located at parallel planes perpendicular to the symmetric axis,so that the density of the whole object can be recovered layer by layer.Considering the relationship between different layers,we undertake the cone-beam global reconstruction to solve the ambiguity effect at the material interfaces of the reconstruction results.In view of the anisotropy of classical discrete total variations,a new discretization of total variation which yields sharp edges and has better isotropy is introduced in our reconstruction model.Furthermore,considering that the object density consists of continually changing parts and jumps,a high-order regularization term is introduced.The final hybrid regularization model is solved using the alternating proximal gradient method,which was recently applied in image processing.Density reconstruction results are presented for simulated radiographs,which shows that the proposed method has led to an improvement in terms of the preservation of edge location.