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

7.5K
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...
7.5K
Planar Rigid-Body Motion01:22

Planar Rigid-Body Motion

1.4K
Understanding the movement of a rigid body in planar motion involves recognizing that every particle within this body is traversing a path that maintains a consistent distance from a specific plane. This concept is fundamental in the study of physics and mechanical engineering, and it allows us to comprehend better how objects move in space.
Planar motion is typically divided into three distinct categories. The first is rectilinear translation, demonstrated by a subway train that moves along...
1.4K
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

1.6K
Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the...
1.6K
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

869
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...
869
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

1.0K
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
1.0K
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

834
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
834

You might also read

Related Articles

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

Sort by
Same author

Theoretical Prediction of Bias in Model-Based Material Decomposition.

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

One-Step Material Decomposition Using Spectral Diffusion Posterior Sampling in Sparse-View Dual-Layer CT.

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

Joint Estimation of Scatter Distribution and Material Maps in Volumetric Dual-Layer Cone-Beam CT.

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

Evaluation of Fluence Reduction versus Sparsity for Diffusion Posterior Sampling Reconstruction in Low-Dose CT.

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

Diffusion Posterior Sampling for Tomographic Reconstruction with Mixed Resolution Priors.

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

Using a Physics-Based Approach to Standardize Radiomics Values: Experimental Validation in an Anthropomorphic Phantom on a Clinical CT Scanner Using a Range of Dose Levels and Reconstruction Kernels.

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

AVA: Automated Viewability Analysis for Ureteroscopic Intrarenal Surgery.

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

Kidney Endoscopy Video to Preoperative CT Alignment for Depth Estimation.

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

Deep learning‑based cell type prediction in lung tissue from brightfield histology using CODEX-derived labels.

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

Reconstructing physiological signals from fMRI across the adult lifespan.

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

Axially Swept Light-Sheet Microscopy using scattering and fluorescence contrast mechanisms.

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

Analytic Bounds on GAMLSS Model Variability of Normative White Matter Brain Charts.

Proceedings of SPIE--the International Society for Optical Engineering·2026
See all related articles

Related Experiment Video

Updated: Apr 23, 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

7.5K

Joint Cone-Beam CT Reconstruction and Rigid Motion Compensation Using A Differentiable Projector.

Xin Wang1, Xiao Jiang1, Yue Fan1

  • 1Department of Biomedical Engineering, Johns Hopkins University, Baltimore MD, 21205, USA.

Proceedings of Spie--The International Society for Optical Engineering
|April 22, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method for motion compensation in model-based CBCT reconstruction. The technique effectively reduces motion artifacts, significantly improving image quality for clearer anatomical visualization.

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

2.8K
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

1.7K

Related Experiment Videos

Last Updated: Apr 23, 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

7.5K
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

2.8K
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

1.7K

Area of Science:

  • Medical Imaging
  • Image Reconstruction
  • Computational Science

Background:

  • Cone Beam Computed Tomography (CBCT) is crucial for medical imaging, but motion artifacts degrade image quality.
  • Existing reconstruction methods struggle to accurately compensate for complex motion during scanning.
  • Model-based iterative reconstruction (MBIR) offers potential but requires robust motion estimation.

Purpose of the Study:

  • To develop and assess a feasible method for integrating model-based CBCT reconstruction with rigid motion estimation.
  • To utilize a projection-domain data fidelity objective and a differentiable forward projector for joint optimization.
  • To evaluate the effectiveness of the proposed framework in reducing motion artifacts.

Main Methods:

  • A joint image reconstruction and motion estimation framework was developed, integrating motion compensation into MBIR.
  • Six degrees of freedom (DoF) rigid motion was modeled as geometric perturbations.
  • A differentiable forward projector with analytical gradients enabled efficient backpropagation for simultaneous optimization of motion parameters and attenuation volume.

Main Results:

  • The proposed motion compensation method significantly enhanced image quality across various motion amplitudes.
  • In simulations, Structural Similarity Index (SSIM) improved by up to 48% for increasing motion.
  • Physical phantom studies demonstrated restored sharpness and anatomical continuity, confirming efficacy.

Conclusions:

  • The discrepancy between estimated and acquired projections is sufficient for joint image and motion parameter estimation.
  • This approach potentially eliminates the need for image-based sharpness criteria in motion-compensated reconstruction.
  • The method effectively recovers anatomical structures with minimal residual errors, even under significant motion.