A study of wavelet-based denoising and a new shrinkage function for low-dose CT scans

被引：9

作者：

Mohammadi, Sadegh ^{[1
]}

Leventouri, Th ^{[1
]}

机构：

[1] Florida Atlantic Univ, Dept Phys, Boca Raton, FL 33431 USA

来源：

BIOMEDICAL PHYSICS & ENGINEERING EXPRESS | 2019年 / 5卷 / 03期

关键词：

image denoising; low-dose CT; medical diagnosis; noise reduction; wavelet transforms; DECOMPOSITION;

D O I：

10.1088/2057-1976/ab0fb9

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

Wavelet transformation is known as a strong method for signal and image processing tasks in the medical applications. We utilized this transformation to reduce the noise in low-dose x-ray computed tomography (CT) images. The CT images had been acquired with 75% less radiation dose compared to the normal dose scans. In this paper we propose a shrinkage function that outperforms the traditional ones and it doesn't require any selected parameters, if it is tuned for the specific region of the patient volume. In addition, the denoising performances of combinations of wavelet orders, decomposition levels, and thresholding methods were investigated. The results revealed the best combination of wavelet order and decomposition level for low dose CT denoising.

引用

页数：8

共 33 条

[11] IDEAL SPATIAL ADAPTATION BY WAVELET SHRINKAGE [J].