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

Computed Tomography01:10

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...

You might also read

Related Articles

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

Sort by
Same author

Immunosuppressive therapies adversely affect blood biochemical parameters in patients with inflammatory bowel disease: a meta-analysis.

The Journal of international medical research·2019
Same author

Facile synthesis of Ag-CuO/SBA-15 for aerobic epoxidation of olefins with high activity.

Nanotechnology·2019
Same author

Reinforcement of Polylactic Acid for Fused Deposition Modeling Process with Nano Particles Treated Bamboo Powder.

Polymers·2019
Same author

Comparison of deep learning and human observer performance for detection and characterization of simulated lesions.

Journal of medical imaging (Bellingham, Wash.)·2019
Same author

Bending Flexibility of Moso Bamboo (<i>Phyllostachys Edulis</i>) with Functionally Graded Structure.

Materials (Basel, Switzerland)·2019
Same author

CT Super-Resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble (GAN-CIRCLE).

IEEE transactions on medical imaging·2019
Same journal

BrainCL: Transformer-Based Brain Network Contrastive Learning with Multi-Order Topology and Salience Masking.

IEEE transactions on medical imaging·2026
Same journal

LLM-enhanced Neuron Segmentation and Reconstruction in Complex Mouse Brain Images.

IEEE transactions on medical imaging·2026
Same journal

Matrixed-Spectrum Decomposition Accelerated Linear Boltzmann Transport Equation Solver for Fast Scatter Correction in Multi-Spectral CT.

IEEE transactions on medical imaging·2026
Same journal

The Ritz Adjoint Method for MRI Pulse Design.

IEEE transactions on medical imaging·2026
Same journal

Physiology-guided Self-supervised Learning for Simultaneous Dual-Tracer PET Separation.

IEEE transactions on medical imaging·2026
Same journal

Informed-Exploration Reinforcement Learning for Automated Virtual Coronary Intervention Planning.

IEEE transactions on medical imaging·2026
See all related articles

Related Experiment Video

Updated: Jun 25, 2026

Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization
09:49

Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization

Published on: December 2, 2013

A filtered backprojection algorithm for triple-source helical cone-beam CT.

Jun Zhao1, Yannan Jin, Yang Lu

  • 1Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China. junzhao@sjtu.edu.cn

IEEE Transactions on Medical Imaging
|February 27, 2009
PubMed
Summary
This summary is machine-generated.

A new filtered-backprojection algorithm for triple-source helical cone-beam CT offers exact and efficient image reconstruction. This advance promises faster, high-quality cardiac imaging and contrast-enhanced studies.

More Related Videos

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

High Resolution 3D Imaging of Ex-Vivo Biological Samples by Micro CT
08:57

High Resolution 3D Imaging of Ex-Vivo Biological Samples by Micro CT

Published on: June 21, 2011

Related Experiment Videos

Last Updated: Jun 25, 2026

Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization
09:49

Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization

Published on: December 2, 2013

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

High Resolution 3D Imaging of Ex-Vivo Biological Samples by Micro CT
08:57

High Resolution 3D Imaging of Ex-Vivo Biological Samples by Micro CT

Published on: June 21, 2011

Area of Science:

  • Medical Imaging
  • Computed Tomography
  • Image Reconstruction

Background:

  • Multisource cone-beam CT (CBCT) is crucial for high temporal resolution in cardiac and contrast-enhanced imaging.
  • Existing reconstruction algorithms may lack efficiency for advanced CBCT configurations.

Purpose of the Study:

  • To develop an exact and efficient filtered-backprojection (FBP) algorithm for triple-source helical cone-beam CT.
  • To extend the FBP algorithm to a general (2N+1)-source helical CBCT system.

Main Methods:

  • Developed an exact FBP algorithm utilizing data from triple-helix PI-arcs and specific geometric relations.
  • Leveraged parallel computing for significant speed improvements over prior methods.
  • Validated the algorithm through simulation studies.

Main Results:

  • The proposed FBP algorithm provides exact and efficient image reconstruction for triple-source helical CBCT.
  • Simulation results confirm the algorithm's validity and accuracy.
  • The algorithm demonstrates potential for faster reconstruction compared to backprojection-filtration methods.

Conclusions:

  • The developed FBP algorithm is a promising tool for triple-source helical CBCT applications.
  • This method enhances the feasibility of high-temporal-resolution imaging, particularly for cardiac applications.
  • The algorithm's efficiency and scalability make it suitable for advanced multisource CT systems.