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

9.4K
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...
9.4K

You might also read

Related Articles

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

Sort by
Same authorSame journal

Deep Learning Super-Resolution from Normal to Ultra-High Resolution CT: Conditional Diffusion Model Development and Performance Evaluation in Trabecular Bone Radiomics.

Proceedings of SPIE--the International Society for Optical Engineering·2026
Same author

A Conditional Generative Diffusion Model of Trabecular Bone with Tunable Microstructure.

Proceedings of SPIE--the International Society for Optical Engineering·2025
Same author

Robot-Assisted Reduction of the Ankle Joint via Multi-Body 3D-2D Image Registration.

IEEE transactions on medical robotics and bionics·2025
Same author

Effects of non-stationary blur on texture biomarkers of bone using Ultra-High Resolution CT.

Proceedings of SPIE--the International Society for Optical Engineering·2024
Same author

Performance assessment of surgical tracking systems based on statistical process control and longitudinal QA.

Computer assisted surgery (Abingdon, England)·2023
Same author

Multi-Stage Adaptive Spline Autofocus (MASA) with a Learned Metric for Deformable Motion Compensation in Interventional Cone-Beam CT.

Proceedings of SPIE--the International Society for Optical Engineering·2023

Related Experiment Video

Updated: Mar 18, 2026

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
05:05

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

Published on: November 23, 2019

8.6K

Image-Based Motion Compensation for High-Resolution Extremities Cone-Beam CT.

A Sisniega1, J W Stayman1, Q Cao1

  • 1Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA.

Proceedings of Spie--The International Society for Optical Engineering
|June 28, 2016
PubMed
Summary

This study introduces a novel two-step iterative method to correct involuntary patient motion in cone-beam CT (CBCT) extremity imaging. The technique significantly improves image sharpness and reduces artifacts without external tracking, enhancing diagnostic accuracy.

Keywords:
cone-beam CTextremities imagingmotion correctionstatistical reconstruction

More Related Videos

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy
07:43

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

Published on: July 2, 2021

3.7K
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

10.9K

Related Experiment Videos

Last Updated: Mar 18, 2026

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
05:05

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

Published on: November 23, 2019

8.6K
In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy
07:43

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

Published on: July 2, 2021

3.7K
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

10.9K

Area of Science:

  • Medical Imaging
  • Radiology
  • Image Processing

Background:

  • Cone-beam CT (CBCT) offers high spatial resolution for extremity imaging.
  • Involuntary patient motion, even sub-millimeter, can compromise quantitative accuracy in CBCT.
  • External immobilization techniques are often insufficient to eliminate motion artifacts.

Purpose of the Study:

  • To investigate a two-step iterative motion compensation technique for extremities CBCT.
  • To assess the method's effectiveness using a multi-component metric of image sharpness.
  • To evaluate motion correction without requiring a priori motion models, external trackers, or fiducials.

Main Methods:

  • Developed a motion estimation approach based on maximizing a cost function with gradient, entropy, and motion smoothness terms.
  • Implemented a two-step compensation: coarse estimation of gross motion followed by fine-scale displacement estimation.
  • Validated the method using simulations with synthetic motion (1-4 mm) and a real patient scan on a CMOS-based CBCT testbench.

Main Results:

  • Achieved excellent motion correction, with significant visual agreement between compensated and static data.
  • Demonstrated 10-15% improvement in Structural Similarity Index (SSIM) for 2-4 mm motions.
  • Showcased robustness against increasing motion and noise, with significant artifact mitigation in patient data.

Conclusions:

  • The developed image-based motion correction is feasible for extremities CBCT.
  • The method effectively compensates for involuntary motion without external aids.
  • This technique enhances the quantitative accuracy and diagnostic value of extremities CBCT.