Nonmonotone Total Variation Minimization Based Projection Restoration for Low-Dose CT Reconstruction

QIAN Shan-shan; HUANG Jing; MA Jian-hua; ZHANG Hua; LIU Nan; ZHANG Xi-le; FENG Qian-jin; CHEN Wu-fan

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Nonmonotone Total Variation Minimization Based Projection Restoration for Low-Dose CT Reconstruction

更新时间：2025-07-16

- Nonmonotone Total Variation Minimization Based Projection Restoration for Low-Dose CT Reconstruction
- Acta Electronica Sinica Vol. 39, Issue 7, Pages: 1702-1707(2011)
- 作者机构：
  
  南方医科大学生物医学工程学院医学信息研究所,广东,广州,510515
- 作者简介：
- 基金信息：
- DOI：
  CLC： R391.4
- Published：2011
- 稿件说明：
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QIAN Shan-shan, HUANG Jing, MA Jian-hua, et al. Nonmonotone Total Variation Minimization Based Projection Restoration for Low-Dose CT Reconstruction[J]. Acta Electronica Sinica, 2011, 39(7): 1702-1707.
DOI：

QIAN Shan-shan, HUANG Jing, MA Jian-hua, et al. Nonmonotone Total Variation Minimization Based Projection Restoration for Low-Dose CT Reconstruction[J]. Acta Electronica Sinica, 2011, 39(7): 1702-1707. DOI：

摘要

为获取低剂量CT图像的优质重建

本文提出一种基于投影数据非单调性全变分恢复的低剂量CT重建方法.新方法首先通过非线性Anscombe变换将满足Poisson分布的投影数据转化为近似Gaussian分布

其后对变换后的Gaussian型数据进行非单调性全变分最小化算法(Nonmonotone Total Variation Minimization

NTVM)滤波

最后对Anscombe逆变换数据实现传统的滤波反投影(Filtered Back Projection

FBP)CT重建.仿真和临床低剂量CT重建实验表明

本文方法在噪声清除、伪影抑制和缩短重建时间等方面均有上佳表现.

Abstract

In order to improve the reconstruction quality of low-dose CT image

a new approach is proposed based on low-dose CT projection restoration in this paper.First

projection data is transformed from Poisson distribution to Gaussian distribution using nonlinear Anscombe transform.Then

the Anscombe transformed data is filtered by an efficient nonmonotone total variation minimization denoising algorithm.Last

the reconstruction is achieved by inverse Anscombe transform and filtered back projection (FBP) method.Simulated and clinical low-dose CT data experimental results demonstrate that a high-quality CT image can be reconstructed.

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BI Yi-ming

MA Jian-hua

LU Li-jun

LIU Nan

HUANG Jing

CHEN Wu-fan

Related Institution

Institute of Medical Information and Technology,School of Biomedical Engineering,Southern Medical University

School of Computer Science,Qufu Normal University

School of Computer Science and Technology, Xidian University

Faculty of Biomedical Engineering,Fourth Military Medical University

School of Computer ScienceQufu Normal UniversityRizhaoShandong 276826China

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