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...
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...

You might also read

Related Articles

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

Sort by
Same author

The Need for Demonstrated Clinical Translational Evidence in Submissions to the IEEE Journal of Translational Engineering in Health and Medicine.

IEEE journal of translational engineering in health and medicine·2026
Same author

Ambulatory Blood Pressure Thresholds and Left Ventricular Hypertrophy in Children Aged 6-12 Years: A Pediatric Nephrology Research Consortium Study.

The Journal of pediatrics·2026
Same author

Fortification of Daqu with the soy sauce-functional fungus Aspergillus oryzae CICC 2339: investigations into Daqu properties and Baijiu brewing outcomes.

Scientific reports·2026
Same author

Dual-focal-spot single-detector CT: A simulation study to assess cone-beam artifacts and noise.

Journal of applied clinical medical physics·2025
Same author

Optimization-based image reconstruction regularized with inter-spectral structural similarity for limited-angle dual-energy cone-beam CT.

Physics in medicine and biology·2025
Same author

Optimization-Based Image Reconstruction Regularized with Inter-Spectral Structural Similarity for Limited-Angle Dual-Energy Cone-Beam CT.

ArXiv·2025

Related Experiment Video

Updated: Jun 26, 2026

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images
05:49

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images

Published on: February 23, 2024

3D weighting in cone beam image reconstruction algorithms: ray-driven vs. pixel-driven.

Xiangyang Tang1, Roy A Nilsen, Alex Smolin

  • 1Molecular Imaging&Computed Tomography, GE Healthcare, Waukesha, WI 53188, USA. xiangyang.tang@med.ge.com

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|January 24, 2009
PubMed
Summary

This study compares ray-driven and pixel-driven 3D weighting for CT image reconstruction. Both methods enhance diagnostic image quality, with pixel-driven approaches expected to dominate future volumetric CT scanners.

More Related Videos

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography
07:01

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography

Published on: October 24, 2019

Related Experiment Videos

Last Updated: Jun 26, 2026

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images
05:49

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images

Published on: February 23, 2024

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography
07:01

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography

Published on: October 24, 2019

Area of Science:

  • Medical Imaging
  • Computed Tomography (CT)

Background:

  • 3D weighting schemes are crucial for image reconstruction in volumetric CT scanners.
  • Implementations exist as either ray-driven or pixel-driven, based on computational resources.

Purpose of the Study:

  • To experimentally evaluate and compare ray-driven and pixel-driven 3D weighting implementations.
  • To analyze the image quality and computational complexity of both methods for diagnostic imaging.

Main Methods:

  • Utilized computer-simulated data and phantoms (helical body, humanoid chest).
  • Conducted experimental studies on image quality and theoretical analysis of computational complexity.

Main Results:

  • Both ray-driven and pixel-driven 3D weighting significantly improve image quality for diagnostic CT imaging.
  • Demonstrated superior performance for both implementations in clinical applications.

Conclusions:

  • Pixel-driven 3D weighting is anticipated to become the dominant method in advanced volumetric CT scanners.
  • Increasing computational power favors the adoption of pixel-driven implementations for enhanced CT imaging.