Prior image constrained compressed sensing (PICCS)

A method to accurately reconstruct dynamic CT images from highly undersampled projection data sets

Guang Hong Chen, Jie Tang, Shuai Leng

Research output: Contribution to journalArticle

675 Citations (Scopus)

Abstract

When the number of projections does not satisfy the Shannon/Nyquist sampling requirement, streaking artifacts are inevitable in x-ray computed tomography (CT) images reconstructed using filtered backprojection algorithms. In this letter, the spatial-temporal correlations in dynamic CT imaging have been exploited to sparsify dynamic CT image sequences and the newly proposed compressed sensing (CS) reconstruction method is applied to reconstruct the target image sequences. A prior image reconstructed from the union of interleaved dynamical data sets is utilized to constrain the CS image reconstruction for the individual time frames. This method is referred to as prior image constrained compressed sensing (PICCS). In vivo experimental animal studies were conducted to validate the PICCS algorithm, and the results indicate that PICCS enables accurate reconstruction of dynamic CT images using about 20 view angles, which corresponds to an undersampling factor of 32. This undersampling factor implies a potential radiation dose reduction by a factor of 32 in myocardial CT perfusion imaging.

Original languageEnglish (US)
Pages (from-to)660-663
Number of pages4
JournalMedical Physics
Volume35
Issue number2
DOIs
StatePublished - 2008
Externally publishedYes

Fingerprint

Tomography
Perfusion Imaging
Computer-Assisted Image Processing
Artifacts
X-Rays
Datasets
Radiation

Keywords

  • Compressed sensing
  • Dynamic CT
  • Image reconstruction

ASJC Scopus subject areas

  • Biophysics

Cite this

Prior image constrained compressed sensing (PICCS) : A method to accurately reconstruct dynamic CT images from highly undersampled projection data sets. / Chen, Guang Hong; Tang, Jie; Leng, Shuai.

In: Medical Physics, Vol. 35, No. 2, 2008, p. 660-663.

Research output: Contribution to journalArticle

@article{10de006163a1412db73d3b8d31022e22,
title = "Prior image constrained compressed sensing (PICCS): A method to accurately reconstruct dynamic CT images from highly undersampled projection data sets",
abstract = "When the number of projections does not satisfy the Shannon/Nyquist sampling requirement, streaking artifacts are inevitable in x-ray computed tomography (CT) images reconstructed using filtered backprojection algorithms. In this letter, the spatial-temporal correlations in dynamic CT imaging have been exploited to sparsify dynamic CT image sequences and the newly proposed compressed sensing (CS) reconstruction method is applied to reconstruct the target image sequences. A prior image reconstructed from the union of interleaved dynamical data sets is utilized to constrain the CS image reconstruction for the individual time frames. This method is referred to as prior image constrained compressed sensing (PICCS). In vivo experimental animal studies were conducted to validate the PICCS algorithm, and the results indicate that PICCS enables accurate reconstruction of dynamic CT images using about 20 view angles, which corresponds to an undersampling factor of 32. This undersampling factor implies a potential radiation dose reduction by a factor of 32 in myocardial CT perfusion imaging.",
keywords = "Compressed sensing, Dynamic CT, Image reconstruction",
author = "Chen, {Guang Hong} and Jie Tang and Shuai Leng",
year = "2008",
doi = "10.1118/1.2836423",
language = "English (US)",
volume = "35",
pages = "660--663",
journal = "Medical Physics",
issn = "0094-2405",
publisher = "AAPM - American Association of Physicists in Medicine",
number = "2",

}

TY - JOUR

T1 - Prior image constrained compressed sensing (PICCS)

T2 - A method to accurately reconstruct dynamic CT images from highly undersampled projection data sets

AU - Chen, Guang Hong

AU - Tang, Jie

AU - Leng, Shuai

PY - 2008

Y1 - 2008

N2 - When the number of projections does not satisfy the Shannon/Nyquist sampling requirement, streaking artifacts are inevitable in x-ray computed tomography (CT) images reconstructed using filtered backprojection algorithms. In this letter, the spatial-temporal correlations in dynamic CT imaging have been exploited to sparsify dynamic CT image sequences and the newly proposed compressed sensing (CS) reconstruction method is applied to reconstruct the target image sequences. A prior image reconstructed from the union of interleaved dynamical data sets is utilized to constrain the CS image reconstruction for the individual time frames. This method is referred to as prior image constrained compressed sensing (PICCS). In vivo experimental animal studies were conducted to validate the PICCS algorithm, and the results indicate that PICCS enables accurate reconstruction of dynamic CT images using about 20 view angles, which corresponds to an undersampling factor of 32. This undersampling factor implies a potential radiation dose reduction by a factor of 32 in myocardial CT perfusion imaging.

AB - When the number of projections does not satisfy the Shannon/Nyquist sampling requirement, streaking artifacts are inevitable in x-ray computed tomography (CT) images reconstructed using filtered backprojection algorithms. In this letter, the spatial-temporal correlations in dynamic CT imaging have been exploited to sparsify dynamic CT image sequences and the newly proposed compressed sensing (CS) reconstruction method is applied to reconstruct the target image sequences. A prior image reconstructed from the union of interleaved dynamical data sets is utilized to constrain the CS image reconstruction for the individual time frames. This method is referred to as prior image constrained compressed sensing (PICCS). In vivo experimental animal studies were conducted to validate the PICCS algorithm, and the results indicate that PICCS enables accurate reconstruction of dynamic CT images using about 20 view angles, which corresponds to an undersampling factor of 32. This undersampling factor implies a potential radiation dose reduction by a factor of 32 in myocardial CT perfusion imaging.

KW - Compressed sensing

KW - Dynamic CT

KW - Image reconstruction

UR - http://www.scopus.com/inward/record.url?scp=38849164794&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=38849164794&partnerID=8YFLogxK

U2 - 10.1118/1.2836423

DO - 10.1118/1.2836423

M3 - Article

VL - 35

SP - 660

EP - 663

JO - Medical Physics

JF - Medical Physics

SN - 0094-2405

IS - 2

ER -