Incorporating frame-to-frame coupling in simultaneous reconstruction of dynamic image sequences in PET

Elias A. Jonsson*, Sung Cheng Huang, Tony Chan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In dynamic PET studies, cross-sectional images of individual frames are reconstructed separately. Based on the general observation that images of adjacent frames do not change abruptly, we have explored a method to reconstruct all images of a dynamic sequence simultaneously that can incorporate frame-to-frame coupling to improve signal-to-noise level of the reconstructed images. In this study, frame-to-frame coupling is introduced by including in the objective function a penalty term that is proportional to the square of the pixel value difference between adjacent frames. The approach together with a total variation prior (for inplane regularization) in maximum likelihood reconstruction was found to achieve a significant reduction in image noise level, especially for images of early frames of short scan duration. The effectiveness of the method for signal-to-noise improvement is demonstrated with computer simulated data and with a real brain FDG study.

Original languageEnglish (US)
Title of host publicationIncorporating frame-to-frame coupling in simultaneous reconstruction of dynamic image sequences in PET
StatePublished - Dec 1 2000
Externally publishedYes
Event2000 IEEE Nuclear Science Symposium Conference Record - Lyon, France
Duration: Oct 15 2000Oct 20 2000

Conference

Conference2000 IEEE Nuclear Science Symposium Conference Record
CountryFrance
CityLyon
Period10/15/0010/20/00

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Industrial and Manufacturing Engineering

Fingerprint

Dive into the research topics of 'Incorporating frame-to-frame coupling in simultaneous reconstruction of dynamic image sequences in PET'. Together they form a unique fingerprint.

Cite this