Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Scatter correction for positron emission mammography.

Jinyi Qi1, Ronald H Huesman

  • 1Center for Functional Imaging, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. jqi@lbl.gov and rhhuesman@lbl.gov

Physics in Medicine and Biology
|August 31, 2002
PubMed
Summary

This study introduces a scatter correction method for positron emission mammography (PEM) reconstruction. The technique models scatter events and uses Monte Carlo simulations to improve image accuracy and reduce computation time.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Multimodal Fusion of Intraoperative FLIm and Preoperative PET/CT for Patient-Level Prediction of Lymph Node Metastasis in Head and Neck Cancer.

Cancers·2026
Same author

Label-free fluorescence lifetime imaging for rapid discrimination of high-grade prostate cancer in fresh biopsy cores: a feasibility study.

Journal of biomedical optics·2026
Same author

Development and Initial Evaluation of 3D-printed High Resolution Brain Phantom for PET.

IEEE transactions on radiation and plasma medical sciences·2025
Same author

Developing Topics.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Exceptional brain PET images from the NeuroEXPLORER: scans with targeted radiopharmaceuticals and comparison to HRRT.

European journal of nuclear medicine and molecular imaging·2025
Same author

Bayesian additive regression trees for machine learning to classify benign vs atypical lipomatous tumors on MRI.

Radiology advances·2025

Area of Science:

  • Medical Imaging
  • Nuclear Medicine
  • Image Reconstruction

Background:

  • Positron Emission Mammography (PEM) systems require accurate image reconstruction.
  • Scatter events in PEM imaging degrade image quality and quantitative accuracy.
  • Existing reconstruction algorithms often struggle with effective scatter correction.

Purpose of the Study:

  • To develop and present a novel scatter correction method for regularized list mode maximum likelihood (LMM) reconstruction algorithms used in PEM.
  • To enhance the accuracy and reduce computational load of PEM image reconstruction.

Main Methods:

  • Scatter events are modeled as additive Poisson random variables within the LMM forward model.
  • Mean scatter sinograms are estimated using Monte Carlo (MC) simulations.

Related Experiment Videos

  • Crystal scatter is treated as shift-invariant blurring for deconvolution in high-resolution images.

    • Main Results:

    • The MC scatter simulation requires running only once per PEM configuration under uniform background assumption, saving computation time.
    • Theoretical analysis of noise propagation from scatter estimation to reconstruction is provided.
    • A method to calculate required MC events for a desired noise level is presented.

    Conclusions:

    • The proposed scatter correction method improves PEM image reconstruction accuracy.
    • The approach offers computational efficiency by optimizing MC simulations.
    • The noise analysis is applicable to various scatter estimation techniques with available covariance data.