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 Video

Updated: Nov 21, 2025

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

299

Improved PET quantification and harmonization by adaptive denoising.

Mauro Namías1, Robert Jeraj2

  • 1Medical physics department, Fundación Centro Diagnóstico Nuclear, Buenos Aires, Argentina.

Biomedical Physics & Engineering Express
|January 13, 2021
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

Illustration of transfer learning from breast cancer detection to risk prediction: adaptation to local data and local objectives.

Journal of medical imaging (Bellingham, Wash.)·2026
Same author

Integrating biomarker-derived individual treatment response assessment into Bayesian trial design for personalized cancer treatment.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology·2026
Same author

Probabilistic clinical target definition with nearest neighbor correlation.

Physics in medicine and biology·2025
Same author

Early assessment of treatment response in AML using FLT PET/cT: a trial of the ECOG-ACRIN Cancer Research Group (EAI141).

Leukemia & lymphoma·2025
Same author

Deep learning-based PSMA PET segmentation repeatability: A post-hoc analysis of a single-center, prospective, test-retest trial.

La Radiologia medica·2025
Same author

InfoOOD: information bottleneck optimization for post hoc medical image out-of-distribution detection.

Physics in medicine and biology·2025
Same journal

Influence of storage temperature and humidity on entrance window deformations of phantoms for a horizontal beam geometry.

Biomedical physics & engineering express·2026
Same journal

Metamaterial-loaded waveguide antenna with integrated gradient-index cooling lens for abdominal subcutaneous adipose ablation.

Biomedical physics & engineering express·2026
Same journal

Adaptive deformation decomposition network for unsupervised medical image registration.

Biomedical physics & engineering express·2026
Same journal

Beyond the tumor: Recurrence-prone radiomics for prognostication in negative PSMA PET/CT scans of prostate cancer.

Biomedical physics & engineering express·2026
Same journal

Cycle-dependent variation of tumor absorbed dose rates in 177Lu-DOTATATE therapies.

Biomedical physics & engineering express·2026
Same journal

Evaluation of revised TRS398 dosimetry protocol for pencil beam scanning proton therapy systems.

Biomedical physics & engineering express·2026
See all related articles

A new adaptive filter improves positron emission tomography (PET) quantification by reducing bias and enhancing image quality. This method achieves better harmonization across scanners, crucial for multicenter clinical trials.

Area of Science:

  • Medical Imaging
  • Nuclear Medicine
  • Image Processing

Background:

  • Positron Emission Tomption (PET) quantification suffers from bias due to scanner limitations.
  • Quantitative harmonization is essential for multicenter clinical trials, ensuring comparable measurements.
  • Current European Association of Nuclear Medicine (EANM) guidelines recommend harmonized reconstructions but can introduce biases.

Purpose of the Study:

  • To improve quantitative harmonization in PET imaging.
  • To develop a novel adaptive filtering scheme for PET reconstructions.
  • To achieve both low quantification bias and high peak signal-to-noise ratio (PSNR) simultaneously.

Main Methods:

  • Implemented a three-stage adaptive denoising filter.
  • Optimized filter parameters using digital brain and NEMA PET phantoms.

More Related Videos

Quantifying Intermembrane Distances with Serial Image Dilations
07:45

Quantifying Intermembrane Distances with Serial Image Dilations

Published on: September 28, 2018

6.6K
Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases
09:55

Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases

Published on: January 5, 2024

1.6K

Related Experiment Videos

Last Updated: Nov 21, 2025

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

299
Quantifying Intermembrane Distances with Serial Image Dilations
07:45

Quantifying Intermembrane Distances with Serial Image Dilations

Published on: September 28, 2018

6.6K
Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases
09:55

Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases

Published on: January 5, 2024

1.6K
  • Applied optimal filter settings across different PET/CT scanners for training and testing datasets.

    • Main Results:

    • Achieved average contrast recovery coefficient (CRCmax) values close to unity (± 5%) for spheres ≥ 13 mm.
    • Demonstrated PSNR values comparable to state-of-the-art filters.
    • Showed improved lesion conspicuity on clinical scans without artifacts compared to EANM reconstructions.

    Conclusions:

    • The novel adaptive filter offers state-of-the-art quantitative performance in PET imaging.
    • Achieved harmonization tolerances with lower bias and variance than EANM guidelines.
    • Reduced quantification variability and improved CRCmax accuracy across various scanner models.