Range condition and ML-EM checkerboard artifacts

Jiangsheng You, Jing Wang, Zhengrong Liang

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The expectation maximization (EM) algorithm for the maximum likelihood (ML) image reconstruction criterion generates severe checkerboard artifacts in the presence of noise. A classical remedy is to impose an a priori constraint for a penalized ML or maximum a posteriori probability solution. The penalty reduces the checkerboard artifacts and also introduces uncertainty because a priori information is usually unknown in clinic. Recent theoretical investigation reveals that the noise can be divided into two components: one is called null-space noise and the other is range-space noise. The null-space noise can be numerically estimated using filtered backprojection (FBP) algorithm. By the FBP algorithm, the null-space noise annihilates in the reconstruction while the range-space noise propagates into the reconstructed image. The aim of this work is to investigate the relation between the null-space noise and the checkerboard artifacts in the ML-EM reconstruction from noisy projection data. Our study suggests that removing the null-space noise from the projection data could improve the signal-to-noise ratio of the projection data and, therefore, reduce the checkerboard artifacts in the ML-EM reconstructed images. This study reveals an in-depth understanding of the different noise propagations in analytical and iterative image reconstructions, which may be useful to single photon emission computed tomography, where the noise has been a major factor for image degradation. The reduction of the ML-EM checkerboard artifacts by removing the null-space noise avoids the uncertainty of using a priori penalty.

Original languageEnglish (US)
Pages (from-to)1696-1702
Number of pages7
JournalIEEE Transactions on Nuclear Science
Volume54
Issue number5
DOIs
StatePublished - Oct 2007

Fingerprint

Maximum likelihood
artifacts
Image reconstruction
Single photon emission computed tomography
projection
image reconstruction
penalties
Signal to noise ratio
Degradation
noise propagation
signal to noise ratios
tomography
degradation
Uncertainty
photons

Keywords

  • Attenuated Radon transform
  • Computed tomography
  • Consistent condition
  • Noise analysis
  • SPECT

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Nuclear Energy and Engineering

Cite this

Range condition and ML-EM checkerboard artifacts. / You, Jiangsheng; Wang, Jing; Liang, Zhengrong.

In: IEEE Transactions on Nuclear Science, Vol. 54, No. 5, 10.2007, p. 1696-1702.

Research output: Contribution to journalArticle

You, Jiangsheng ; Wang, Jing ; Liang, Zhengrong. / Range condition and ML-EM checkerboard artifacts. In: IEEE Transactions on Nuclear Science. 2007 ; Vol. 54, No. 5. pp. 1696-1702.
@article{d49888177e474aaf9a9303563395e56e,
title = "Range condition and ML-EM checkerboard artifacts",
abstract = "The expectation maximization (EM) algorithm for the maximum likelihood (ML) image reconstruction criterion generates severe checkerboard artifacts in the presence of noise. A classical remedy is to impose an a priori constraint for a penalized ML or maximum a posteriori probability solution. The penalty reduces the checkerboard artifacts and also introduces uncertainty because a priori information is usually unknown in clinic. Recent theoretical investigation reveals that the noise can be divided into two components: one is called null-space noise and the other is range-space noise. The null-space noise can be numerically estimated using filtered backprojection (FBP) algorithm. By the FBP algorithm, the null-space noise annihilates in the reconstruction while the range-space noise propagates into the reconstructed image. The aim of this work is to investigate the relation between the null-space noise and the checkerboard artifacts in the ML-EM reconstruction from noisy projection data. Our study suggests that removing the null-space noise from the projection data could improve the signal-to-noise ratio of the projection data and, therefore, reduce the checkerboard artifacts in the ML-EM reconstructed images. This study reveals an in-depth understanding of the different noise propagations in analytical and iterative image reconstructions, which may be useful to single photon emission computed tomography, where the noise has been a major factor for image degradation. The reduction of the ML-EM checkerboard artifacts by removing the null-space noise avoids the uncertainty of using a priori penalty.",
keywords = "Attenuated Radon transform, Computed tomography, Consistent condition, Noise analysis, SPECT",
author = "Jiangsheng You and Jing Wang and Zhengrong Liang",
year = "2007",
month = "10",
doi = "10.1109/TNS.2007.901198",
language = "English (US)",
volume = "54",
pages = "1696--1702",
journal = "IEEE Transactions on Nuclear Science",
issn = "0018-9499",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "5",

}

TY - JOUR

T1 - Range condition and ML-EM checkerboard artifacts

AU - You, Jiangsheng

AU - Wang, Jing

AU - Liang, Zhengrong

PY - 2007/10

Y1 - 2007/10

N2 - The expectation maximization (EM) algorithm for the maximum likelihood (ML) image reconstruction criterion generates severe checkerboard artifacts in the presence of noise. A classical remedy is to impose an a priori constraint for a penalized ML or maximum a posteriori probability solution. The penalty reduces the checkerboard artifacts and also introduces uncertainty because a priori information is usually unknown in clinic. Recent theoretical investigation reveals that the noise can be divided into two components: one is called null-space noise and the other is range-space noise. The null-space noise can be numerically estimated using filtered backprojection (FBP) algorithm. By the FBP algorithm, the null-space noise annihilates in the reconstruction while the range-space noise propagates into the reconstructed image. The aim of this work is to investigate the relation between the null-space noise and the checkerboard artifacts in the ML-EM reconstruction from noisy projection data. Our study suggests that removing the null-space noise from the projection data could improve the signal-to-noise ratio of the projection data and, therefore, reduce the checkerboard artifacts in the ML-EM reconstructed images. This study reveals an in-depth understanding of the different noise propagations in analytical and iterative image reconstructions, which may be useful to single photon emission computed tomography, where the noise has been a major factor for image degradation. The reduction of the ML-EM checkerboard artifacts by removing the null-space noise avoids the uncertainty of using a priori penalty.

AB - The expectation maximization (EM) algorithm for the maximum likelihood (ML) image reconstruction criterion generates severe checkerboard artifacts in the presence of noise. A classical remedy is to impose an a priori constraint for a penalized ML or maximum a posteriori probability solution. The penalty reduces the checkerboard artifacts and also introduces uncertainty because a priori information is usually unknown in clinic. Recent theoretical investigation reveals that the noise can be divided into two components: one is called null-space noise and the other is range-space noise. The null-space noise can be numerically estimated using filtered backprojection (FBP) algorithm. By the FBP algorithm, the null-space noise annihilates in the reconstruction while the range-space noise propagates into the reconstructed image. The aim of this work is to investigate the relation between the null-space noise and the checkerboard artifacts in the ML-EM reconstruction from noisy projection data. Our study suggests that removing the null-space noise from the projection data could improve the signal-to-noise ratio of the projection data and, therefore, reduce the checkerboard artifacts in the ML-EM reconstructed images. This study reveals an in-depth understanding of the different noise propagations in analytical and iterative image reconstructions, which may be useful to single photon emission computed tomography, where the noise has been a major factor for image degradation. The reduction of the ML-EM checkerboard artifacts by removing the null-space noise avoids the uncertainty of using a priori penalty.

KW - Attenuated Radon transform

KW - Computed tomography

KW - Consistent condition

KW - Noise analysis

KW - SPECT

UR - http://www.scopus.com/inward/record.url?scp=35348992773&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=35348992773&partnerID=8YFLogxK

U2 - 10.1109/TNS.2007.901198

DO - 10.1109/TNS.2007.901198

M3 - Article

C2 - 18449363

AN - SCOPUS:35348992773

VL - 54

SP - 1696

EP - 1702

JO - IEEE Transactions on Nuclear Science

JF - IEEE Transactions on Nuclear Science

SN - 0018-9499

IS - 5

ER -