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 Concept Videos

You might also read

Related Articles

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

Sort by
Same author

AI-augmented thyroid scintigraphy for robust classification of disease.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2026
Same author

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

Biomedical physics & engineering express·2026
Same author

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

Biomedical physics & engineering express·2026
Same author

Kernel-based Maximum likelihood reconstruction of attenuation and activity (MLAA) in SPECT imaging for improved attenuation correction and activity quantification: Simulation, phantom and patient validation studies.

Physics in medicine and biology·2026
Same author

A clinically anchored radiomics dictionary for explainable TI-RADS-based thyroid nodule classification in ultrasound; dictionary version TU1.0.

European journal of radiology·2026
Same author

Microenvironment at a Distance: Multi-Endocrine-Organ Radiomics to Identify Systemic Signatures in PSMA-Negative Prostate Cancer.

Cancers·2026
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

Related Experiment Video

Updated: May 20, 2026

Studying Metabolic Brain Connectivity Using 2-Deoxy-2-[18F]Fluoro-D-Glucose Dynamic Positron Emission Tomography at the Single-subject Level
07:28

Studying Metabolic Brain Connectivity Using 2-Deoxy-2-[18F]Fluoro-D-Glucose Dynamic Positron Emission Tomography at the Single-subject Level

Published on: January 24, 2025

3.5D dynamic PET image reconstruction incorporating kinetics-based clusters.

Lijun Lu1, Nicolas A Karakatsanis, Jing Tang

  • 1School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong 510515, People’s Republic of China.

Physics in Medicine and Biology
|July 19, 2012
PubMed
Summary
This summary is machine-generated.

A novel 3.5D dynamic positron emission tomographic (PET) reconstruction method improves quantitative accuracy of parametric images by using cluster-based priors derived from voxel kinetics. This approach enhances noise-bias performance for distribution volume and ratio images.

More Related Videos

High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals
11:09

High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals

Published on: December 16, 2022

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions
13:43

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions

Published on: June 24, 2013

Related Experiment Videos

Last Updated: May 20, 2026

Studying Metabolic Brain Connectivity Using 2-Deoxy-2-[18F]Fluoro-D-Glucose Dynamic Positron Emission Tomography at the Single-subject Level
07:28

Studying Metabolic Brain Connectivity Using 2-Deoxy-2-[18F]Fluoro-D-Glucose Dynamic Positron Emission Tomography at the Single-subject Level

Published on: January 24, 2025

High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals
11:09

High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals

Published on: December 16, 2022

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions
13:43

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions

Published on: June 24, 2013

Area of Science:

  • Medical Imaging
  • Nuclear Medicine
  • Image Reconstruction

Background:

  • Dynamic PET imaging typically reconstructs frames independently, limiting quantitative accuracy.
  • Emerging 4D PET reconstruction aims to integrate multi-frame information during reconstruction.
  • Current methods struggle with noise and bias in parametric PET images.

Purpose of the Study:

  • To introduce a novel '3.5D' PET reconstruction framework using cluster-based priors.
  • To enhance the quantitative accuracy of parametric images in dynamic PET.
  • To improve the noise-bias performance of distribution volume (DV) and DV ratio (DVR) images.

Main Methods:

  • Developed a 3.5D reconstruction framework incorporating priors based on voxel kinetics.
  • Utilized clustering of preliminary dynamic images to define neighborhoods with similar kinetics.
  • Employed maximum a posteriori (MAP) reconstruction with novel cluster-based priors (CP-U-MAP, CP-W-MAP).
  • Compared performance against MLEM, QP-MAP, and GP-MAP using simulated and real (11)C-raclopride data.

Main Results:

  • The proposed 3.5D reconstruction significantly improved visual and quantitative accuracy of parametric DV and DVR images.
  • Cluster-based priors demonstrated superior noise-bias performance compared to conventional priors.
  • Tested on simulated data and a 90-minute (11)C-raclopride patient study, the method outperformed standard reconstruction.

Conclusions:

  • The novel 3.5D dynamic PET reconstruction with cluster-based priors enhances quantitative accuracy.
  • This method offers substantial improvements in noise-bias performance for parametric PET imaging.
  • The approach shows promise for more precise quantitative analysis in dynamic PET studies.