Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Rigid Body Equilibrium Problems - II

Rigid Body Equilibrium Problems - II

A rigid body is in static equilibrium when the net force and the net torque acting on the system are equal to zero.
Consider two children sitting on a seesaw, which has negligible mass. The first child has a mass (m1) of 26 kg and sits at point A, which is 1.6 meters (r1) from the pivot point B; the second child has a mass (m2) of 32 kg and sits at point C. How far from the pivot point B should the second child sit (r2) to balance the seesaw?

Rigid Body Equilibrium Problems - I

Rigid Body Equilibrium Problems - I

A rigid body is said to be in static equilibrium when the net force and the net torque acting on the system is equal to zero. To solve for rigid body equilibrium problems, do the following steps.

Curvilinear Motion: Rectangular Components

Curvilinear Motion: Rectangular Components

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...

Planar Rigid-Body Motion

Planar Rigid-Body Motion

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...

Improving Translational Accuracy

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

Improving Translational Accuracy

Improving Translational Accuracy

You might also read

Related Articles

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

Sort by

Same author

Lean Unet: a compact model for image segmentation.

International journal of computer assisted radiology and surgery·2026

Same author

Image-based metrics in ultrasound for estimation of global speed of sound.

Ultrasonics·2026

Same author

Pulse-Echo Imaging of Breast Speed of Sound as a Potential Biomarker for Breast Cancer.

Ultrasound in medicine & biology·2025

Same author

Uncertainty estimation for trust attribution to speed-of-sound reconstruction with variational networks.

International journal of computer assisted radiology and surgery·2025

Same author

A study of radiation workers: Dosimetry, chromosomal aberrations, and cancer risk.

Mutation research. Genetic toxicology and environmental mutagenesis·2025

Same author

Joint semi-supervised and contrastive learning enables domain generalization and multi-domain segmentation.

Medical image analysis·2025

Search research articles

Related Experiment Video

Updated: Apr 7, 2026

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

Consistency-based rectification of nonrigid registrations.

Tobias Gass¹, Gábor Székely¹, Orcun Goksel¹

¹ETH Zurich , Department of Information Technology and Electrical Engineering, Computer Vision Lab, Sternwartstr.7, Zurich 8092, Switzerland.

Journal of Medical Imaging (Bellingham, Wash.)

|July 10, 2015

Summary

We developed a new method to improve medical image registration accuracy. This technique enhances group-wise consistency, reducing errors in nonrigid image alignment for better analysis in MRI and CT scans.

Keywords:

consistency group-wise registration least-squares nonrigid registration registration circuits

More Related Videos

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

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

Published on: February 23, 2024

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Published on: April 12, 2014

Related Experiment Videos

Last Updated: Apr 7, 2026

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

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

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

Published on: February 23, 2024

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Published on: April 12, 2014

Area of Science:

Medical imaging
Image registration
Computational anatomy

Background:

Nonrigid image registration is crucial for medical image analysis.
Existing methods often lack group-wise consistency, leading to registration errors.
Group-wise registration can propagate and accumulate errors.

Purpose of the Study:

To present a novel technique for rectifying nonrigid registrations by enhancing group-wise consistency.
To address limitations of pair-wise and traditional group-wise registration methods.
To improve the accuracy and reliability of medical image registration.

Main Methods:

Introduced Consistency-Based Registration Rectification (CBRR).
Employed a regularized least-squares algorithm to minimize group-wise inconsistency.
Incorporated local post-registration similarity for adaptive correction.

Main Results:

Demonstrated reduced average transformation error on simulated data.
Achieved up to 50% improvement in target registration error for 4D MRI motion estimation.
Showcased up to 65% improvement in mean surface distance for 3D CT atlas-based segmentation.

Conclusions:

CBRR effectively improves group-wise consistency and accuracy of nonrigid registrations.
The method shows significant benefits across different imaging modalities, dimensions, and registration algorithms.
CBRR offers a robust solution for enhancing medical image analysis tasks.