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

9.2K
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...
9.2K
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

495
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...
495
Imaging Studies I: CT and MRI01:14

Imaging Studies I: CT and MRI

1.0K
Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...
1.0K

You might also read

Related Articles

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

Sort by
Same author

Neutron-Multiplicity Measurement in Muon Capture on Oxygen Nuclei in the Gadolinium-Loaded Super-Kamiokande Detector.

Physical review letters·2026
Same author

[Analysis of the clinical characteristics of dry eye patients with type 2 diabetes mellitus at different disease durations].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology·2026
Same author

[Establishing LC-MS/MS-based cutoffs for the confirmatory testing for primary aldosteronism: a prospective multi-center study].

Zhonghua nei ke za zhi·2026
Same author

Precision Measurement of Neutrino Oscillation Parameters with 10 Years of Data from the NOvA Experiment.

Physical review letters·2026
Same author

The Remineralization Potential of Resveratrol and Cucurbit[<i>n</i>]uril.

Journal of dental research·2025
Same author

Night shifts and sleep among Chinese nursing students on internship.

Occupational medicine (Oxford, England)·2025

Related Experiment Video

Updated: Mar 2, 2026

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

1.6K

WE-G-217BCD-06: Fully Incorporated Scanning Geometry for Improved Accuracy in C-Arm CBCT Image Reconstruction.

X Han1,2,3, M Silver1,2,3, S Oishi1,2,3

  • 1The University of Chicago, Chicago, IL.

Medical Physics
|May 19, 2017
PubMed
Summary
This summary is machine-generated.

An innovative iterative algorithm improves C-arm cone-beam CT (CBCT) imaging by correcting for gantry tilting and wobbling. This enhanced method reconstructs clearer images, improving visualization of small blood vessels for better clinical utility.

Keywords:
BrainCalibrationComputed tomographyCone beam computed tomographyImage reconstructionMedical image artifactsMedical image contrastMedical image qualityMedical image reconstructionMedical imaging

More Related Videos

Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads
07:58

Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads

Published on: July 25, 2025

938
Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision
07:57

Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision

Published on: April 29, 2014

14.1K

Related Experiment Videos

Last Updated: Mar 2, 2026

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

1.6K
Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads
07:58

Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads

Published on: July 25, 2025

938
Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision
07:57

Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision

Published on: April 29, 2014

14.1K

Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Radiology

Background:

  • C-arm cone-beam CT (CBCT) is vital in interventional procedures, but gantry instability causes image artifacts.
  • Tilting and wobbling motions during C-arm CBCT rotation degrade image quality, impacting clinical diagnosis.
  • Accurate scanning geometry is crucial for high-fidelity CBCT reconstruction.

Purpose of the Study:

  • To investigate and demonstrate image quality improvements in C-arm CBCT.
  • To develop and apply an iterative algorithm that incorporates accurate scanning geometry.
  • To overcome artifacts caused by C-arm gantry instability.

Main Methods:

  • Utilized a clinical C-arm CBCT system to acquire brain vasculature projection data.
  • Modified the ASD-POCS iterative algorithm to integrate actual scanning geometry data.
  • Compared image reconstructions using the standard FDK algorithm and the modified ASD-POCS algorithm.

Main Results:

  • FDK reconstructions without motion correction showed artifacts, disrupting vessel continuity.
  • FDK reconstructions incorporating system geometry improved vessel continuity.
  • ASD-POCS reconstructions with accurate geometry calibration yielded superior results, enhancing visualization of small vascular branches.

Conclusions:

  • Iterative algorithms that fully incorporate scanning geometry significantly enhance C-arm CBCT image quality.
  • This approach can enable demanding, high-resolution imaging applications previously limited by the FDK algorithm.
  • Improved C-arm CBCT imaging holds potential for advanced interventional procedures.