Clustering Imaging For X-ray Based On Sensitivity Coefficient

Multiphase flow exists widely in the field of industrial processes and themeasurement of multiphase flow is of great important significance. As one ofsuccessful computed tomography, process tomography has the advantages ofnon-invasiveness, visualization and high-precision. And as an important processtomography, X-ray tomography that has the solid mathematical theory and theoperable and understandable computing technology is widely applied to themultiphase flow.This dissertation simulates X-ray system using Geant4software and comparesseveral image reconstruction algorithms based on the simulation data. The maincontent of the article is clustering imaging based on sensitivity coefficient andanalyzing the result. At the last this paper compares the clustering imaging formedical CT image using the new validity index. The main contents include severalaspects as follows:(1) System SimulationThis thesis established simulation of the X-ray CT system using Geant4software,simulated the physical process of the X-ray system and obtained the simulation data.(2) X-ray Image Reconstruction AlgorithmUsing the simulation data, several image reconstruction algorithms such as BP,FBP, CGLS algorithm have been compared. And in the Fan beam reconstructionalgorithm, the effect of the distance D and the grid of pixel for reconstruction imaginghave been analyzed.(3) Clustering Imaging Based On Sensitivity CoefficientBy means of establishing the different X-ray sensitivity coefficient matrix,clustering imaging based on sensitivity coefficient using the simulation data has beenanalyzed. And the effect of the different parameter for clustering imaging based onsensitivity coefficient also has been discussed. The experiment results show thatclustering imaging based on sensitivity coefficient provides the new research directionof X-ray tomography and is a new reconstruction imaging algorithm.(4)Clustering Imaging For Medical CT Image Using The New Validity IndexEstablishing the new validity index and using the new validity index for the medical CT imaging data has been discussed. And using different clustering algorithmto reconstruct CT image is based on the best number of the clusters of the validityindex. The result show that clustering imaging for medical CT image using thevalidity index is useful for distinguishing the different body part and will be potentialapplication.