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

Iterative reconstruction of PET images using a high-overrelaxation single-projection algorithm

P Schmidlin1, M E Bellemann, G Brix

  • 1Deutsches Krebsforschungszentrum, Forschungsschwerpunkt Radiologie, Heidelberg, Germany. schmidlin@dkfz-heidelberg.de

Physics in Medicine and Biology
|March 1, 1997
PubMed
Summary
This summary is machine-generated.

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

[Scientific assessment and regulatory approval of radiological screening examinations in Germany].

Der Radiologe·2020
Same author

Diagnostic reference levels for diagnostic and interventional X-ray procedures in Germany: update and handling - Answer to the comments of members of the chest radiology workshop of the German Roentgen Society.

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin·2019
Same author

[Radiation protection in medical research : Licensing requirement for the use of radiation and advice for the application procedure].

Der Radiologe·2017
Same author

[Magnetic resonance imaging : Recent studies on biological effects of static magnetic and high‑frequency electromagnetic fields].

Der Radiologe·2017
Same author

[Frequency and doses of diagnostic and interventional X‑ray applications : Trends between 2007 and 2014].

Der Radiologe·2017
Same author

Radiation exposure of patients undergoing whole-body FDG-PET/CT examinations: an update pursuant to the new ICRP recommendations.

Nuklearmedizin. Nuclear medicine·2014
Same journal

Effective contrast-enhanced preprocessing for intracranial artery segmentation in digital subtraction angiography.

Physics in medicine and biology·2026
Same journal

Improving Plan Quality in Adaptive Proton Therapy Using an Interactive Dose Modification Tool.

Physics in medicine and biology·2026
Same journal

Technical Note: Real-Time MLC Control and Latency Measurement Optimization with External Verification.

Physics in medicine and biology·2026
Same journal

Fetus-Specific Hematopoietic Stem Cell Dosimetry Framework for Leukemia-Relevant Target Cells During Prenatal Development.

Physics in medicine and biology·2026
Same journal

Deep learning-based dose prediction to enhance planning efficiency in cervical brachytherapy with hybrid applicators.

Physics in medicine and biology·2026
Same journal

Corrigendum: Referenceless MR thermometry-a comparison of five methods (2017<i>Phys. Med. Biol</i>.<b>62</b>1-16).

Physics in medicine and biology·2026
See all related articles

This study introduces an iterative image reconstruction method using adaptive overrelaxation parameters to enhance image quality rapidly. Optimized parameters accelerate reconstruction, proving effective across different datasets for improved imaging.

Area of Science:

  • Medical imaging
  • Computational imaging
  • Image processing

Background:

  • Iterative image reconstruction is crucial for high-quality medical imaging.
  • Optimizing reconstruction parameters can significantly improve efficiency and accuracy.
  • Current methods may require extensive computation for large datasets.

Purpose of the Study:

  • To develop a novel iterative image reconstruction procedure for enhanced precision.
  • To accelerate the reconstruction process using optimized overrelaxation parameters.
  • To demonstrate the generalizability of the derived parameters across various datasets.

Main Methods:

  • Implemented an iterative image reconstruction algorithm.
  • Utilized high initial overrelaxation parameters that decrease during iteration.

Related Experiment Videos

  • Determined parameters pragmatically to maximize image quality gains.
  • Validated the method with simulated and measured data.

    • Main Results:

    • Achieved high-precision images within eight iterative steps.
    • Demonstrated that parameters derived from one dataset are applicable to others.
    • Showcased significant acceleration of iterative reconstruction.
    • Confirmed the method's effectiveness for large datasets and 3D reconstruction.

    Conclusions:

    • The proposed iterative reconstruction method offers rapid, high-precision image calculation.
    • Adaptive overrelaxation parameters effectively accelerate reconstruction and improve image quality.
    • The parameter estimation strategy is robust and widely applicable, particularly for large-scale 3D imaging applications.