Multiscale penalized weighted least-squares sinogram restoration for low-dose X-ray computed tomography.

Jing Wang, Zhengrong Liang, Hongbing Lu

Research output: Contribution to journalArticle

Abstract

We propose a novel multiscale penalized weighted least-squares (PWLS) method for restoration of low-dose computed tomography (CT) sinogram. The method utilizes wavelet transform for the multiscale or multi-resolution analysis on the sinogram. Specifically the Mallat-Zhong's wavelet transform is applied to decompose the sinogram to different resolution levels. At each decomposed resolution level, a PWLS criterion is applied to restore the noise-contaminated wavelet coefficients, where the penalty is adaptive to each resolution scale and the weight is adaptive to each scale and each location. The proposed PWLS method is based on the observation that (1) the noisy sinogram of low-dose CT after logarithm transform can be modeled as signal-dependent Gaussian variables and the sample variance depends on the sample mean; and (2) the noise restoration can be more effective when it is adaptive to different resolution levels. The effectiveness of the proposed multiscale PWLS method is validated by an experimental study. The gain by multiscale approach over single-scale means is quantified by noise-resolution tradeoff measures.

Fingerprint

X Ray Computed Tomography
Least-Squares Analysis
Wavelet transforms
Restoration
Dosimetry
Tomography
Noise
X rays
Wavelet Analysis
Multiresolution analysis
Weights and Measures

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

@article{f43a45171e384e73bc29b15a38af1387,
title = "Multiscale penalized weighted least-squares sinogram restoration for low-dose X-ray computed tomography.",
abstract = "We propose a novel multiscale penalized weighted least-squares (PWLS) method for restoration of low-dose computed tomography (CT) sinogram. The method utilizes wavelet transform for the multiscale or multi-resolution analysis on the sinogram. Specifically the Mallat-Zhong's wavelet transform is applied to decompose the sinogram to different resolution levels. At each decomposed resolution level, a PWLS criterion is applied to restore the noise-contaminated wavelet coefficients, where the penalty is adaptive to each resolution scale and the weight is adaptive to each scale and each location. The proposed PWLS method is based on the observation that (1) the noisy sinogram of low-dose CT after logarithm transform can be modeled as signal-dependent Gaussian variables and the sample variance depends on the sample mean; and (2) the noise restoration can be more effective when it is adaptive to different resolution levels. The effectiveness of the proposed multiscale PWLS method is validated by an experimental study. The gain by multiscale approach over single-scale means is quantified by noise-resolution tradeoff measures.",
author = "Jing Wang and Zhengrong Liang and Hongbing Lu",
year = "2006",
language = "English (US)",
pages = "3282--3285",
journal = "Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference",
issn = "1557-170X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Multiscale penalized weighted least-squares sinogram restoration for low-dose X-ray computed tomography.

AU - Wang, Jing

AU - Liang, Zhengrong

AU - Lu, Hongbing

PY - 2006

Y1 - 2006

N2 - We propose a novel multiscale penalized weighted least-squares (PWLS) method for restoration of low-dose computed tomography (CT) sinogram. The method utilizes wavelet transform for the multiscale or multi-resolution analysis on the sinogram. Specifically the Mallat-Zhong's wavelet transform is applied to decompose the sinogram to different resolution levels. At each decomposed resolution level, a PWLS criterion is applied to restore the noise-contaminated wavelet coefficients, where the penalty is adaptive to each resolution scale and the weight is adaptive to each scale and each location. The proposed PWLS method is based on the observation that (1) the noisy sinogram of low-dose CT after logarithm transform can be modeled as signal-dependent Gaussian variables and the sample variance depends on the sample mean; and (2) the noise restoration can be more effective when it is adaptive to different resolution levels. The effectiveness of the proposed multiscale PWLS method is validated by an experimental study. The gain by multiscale approach over single-scale means is quantified by noise-resolution tradeoff measures.

AB - We propose a novel multiscale penalized weighted least-squares (PWLS) method for restoration of low-dose computed tomography (CT) sinogram. The method utilizes wavelet transform for the multiscale or multi-resolution analysis on the sinogram. Specifically the Mallat-Zhong's wavelet transform is applied to decompose the sinogram to different resolution levels. At each decomposed resolution level, a PWLS criterion is applied to restore the noise-contaminated wavelet coefficients, where the penalty is adaptive to each resolution scale and the weight is adaptive to each scale and each location. The proposed PWLS method is based on the observation that (1) the noisy sinogram of low-dose CT after logarithm transform can be modeled as signal-dependent Gaussian variables and the sample variance depends on the sample mean; and (2) the noise restoration can be more effective when it is adaptive to different resolution levels. The effectiveness of the proposed multiscale PWLS method is validated by an experimental study. The gain by multiscale approach over single-scale means is quantified by noise-resolution tradeoff measures.

UR - http://www.scopus.com/inward/record.url?scp=84903868331&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84903868331&partnerID=8YFLogxK

M3 - Article

SP - 3282

EP - 3285

JO - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference

JF - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference

SN - 1557-170X

ER -