| 注册
首页|期刊导航|北京生物医学工程|医用X-CT图像中金属伪影校正算法的研究进展

医用X-CT图像中金属伪影校正算法的研究进展

陈宗桂 彭哲宇 张靓 魏宁宁 董晓军

北京生物医学工程2026,Vol.45Issue(3):312-318,7.
北京生物医学工程2026,Vol.45Issue(3):312-318,7.DOI:10.3969/j.issn.1002-3208.2026.03.013

医用X-CT图像中金属伪影校正算法的研究进展

Research progress of metal artifact correction algorithm in medical X-CT image

陈宗桂 1彭哲宇 1张靓 1魏宁宁 1董晓军1

作者信息

  • 1. 湖南医药学院(湖南 怀化 418000)
  • 折叠

摘要

Abstract

Metal implants such as intracranial aneurysm embolisation,oral metal implants,spinal endoprostheses,and hip arthroplasty are increasingly used in clinical practice with the continuous progress of medical technology.However,the high-density metal implant absorbed a large number of X-ray photon counts resulting in missing projection data in the postoperative CT image review.Stripe artifacts appear on the reconstructed CT images,reducing the contrast of the images,making subtle anatomical structures poorly displayed,and even causing clinicians to make incorrect diagnoses.Interpolation algorithm to correct metal artifacts is to reduce the artifacts by estimating the missing data in the metal projection area.Iterative reconstruction technique is to approximate the real image step by step through several iterations of computation.Prior image correction algorithms use known metal object information or models to pre-process images to reduce the impact of metal artifacts.Deep learning algorithms are able to automatically identify and correct metal artifacts with high accuracy and efficiency by training neural network models.However,there are significant differences in the results demonstrated by different algorithms for metal artifact suppression.The interpolation algorithm is not effective for the suppression of polymetallic artifacts.Iterative reconstruction algorithms require multiple iterations to optimize the image reconstruction process,which can partially reduce the impact of metal artifacts,but may take longer to compute.Therefore,the application of interpolation algorithm,iterative reconstruction,prior image correction algorithm and deep learning algorithm to metal artifact correction is reviewed.

关键词

插值/迭代/先验图像/深度学习/金属伪影

Key words

interpolation/iteration/priori images/deep learning/metal artifacts

分类

医药卫生

引用本文复制引用

陈宗桂,彭哲宇,张靓,魏宁宁,董晓军..医用X-CT图像中金属伪影校正算法的研究进展[J].北京生物医学工程,2026,45(3):312-318,7.

基金项目

湖南省自然科学基金青年项目(2021JJ40385)、湖南省教育厅一般项目(22C1183)、2025年湖南医药学院大学生创新创业训练计划项目-68资助 (2021JJ40385)

北京生物医学工程

1002-3208

访问量0
|
下载量0
段落导航相关论文