Research On CT Image Metal Artifact Correction Algorithm Based On Guided Filtering And Relative Total Variation

Computerized Tomography is an emerging interdisciplinary that combines contemporary nuclear physics and image technology theory.It is currently developing rapidly in the medical and industrial fields.Affected by the metal implant,there are some differences between the real object and the image reconstructed by CT,and these differences are reflected as metal artifacts on the reconstructed image.Metal artifacts impair the quality of the image and cause serious harm to the subsequent reprocessing and analysis of the image.Therefore,removing metal artifacts from the image has always been a hot issue in the CT field.This article first summarizes the relevant research results in the field of CT image metal artifact correction at home and abroad,analyzes the basic causes of metal artifacts,describes the CT imaging principle,the basic theory of the reconstruction process,and two commonly used reconstruction algorithms.For the correction of metal artifacts in CT images,the following tasks have been completed:(1)The theoretical and experimental verifications of several mainstream metal artifact correction methods are introduced in detail.The linear interpolation method is simple and efficient,and it has a good effect when the metal structure is relatively simple;the iterative correction method uses linear interpolation and full variational filtering,which solves the problem of secondary artifacts introduced by the interpolation method and reduces the iterative method The number of calculations.The method based on deep learning to remove metal artifacts has a very good correction effect,and can well maintain the tissue structure near the metal.(2)Apply several image repair methods to remove metal artifacts.Aiming at the problem of repairing small defect areas in the image,the mathematical theories of the four models of BSCB method,TV method,CDD method and adaptive TV method are elaborated.In order to solve the problem of repairing large defect areas in the image,the specific steps of the Criminisi algorithm and a CIEI model proposed by Wu et al.are first analyzed.This model can better maintain the basic structure of the image;finally,the combination of the CIEI model and the The data items calculated in the continuity-constrained Criminisi algorithm are assigned appropriate parameters as the final data items.The experimental results show that these methods have good effects in removing metal artifacts.(3)Improvements are made on the basis of the iterative correction method,and a metal artifact correction algorithm based on guided filtering and relative total variation is proposed.The basic step of the algorithm in this paper is to obtain the target metal projection area by threshold segmentation method,then use linear interpolation method to interpolate and complete the target metal projection area,and then use the filter back projection algorithm to perform CT reconstruction to obtain the initial correction result.Full variational filtering is used to keep the edges smooth,and then use guided filtering combined with the structural information of the original image.These two steps can gradually optimize the image quality and obtain the final result after many iterations.The experimental results show that the algorithm in this paper removes most of the metal artifacts in the image,the tissue structure around the metal is also maintained,and no other new artifacts are generated.