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

Curvilinear Motion: Polar Coordinates01:27

Curvilinear Motion: Polar Coordinates

1.2K
In polar coordinates, the motion of a particle follows a curvilinear path. The radial coordinate symbolized as 'r,' extends outward from a fixed origin to the particle, while the angular coordinate, 'θ,' measured in radians, represents the counterclockwise angle between a fixed reference line and the radial line connecting the origin to the particle.
The particle's location is described using a unit vector along the radial direction. Deriving the particle's position...
1.2K
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

844
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...
844
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
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

922
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
922
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

1.1K
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...
1.1K
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

756
Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
756

You might also read

Related Articles

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

Sort by
Same author

Characterization of Yeast Protein Hydrolysate for Potential Application as a Feed Additive.

Food science of animal resources·2026
Same author

Characterization and Validation of Long-Term Cultured TERT-Immortalized Human Wharton's Jelly-Derived Mesenchymal Stromal Cells.

Stem cell reviews and reports·2026
Same author

Corrigendum: Electron transport phenomena at the interface of Al electrode and heavily doped degenerate ZnO nanoparticles in quantum dot light emitting diode (2019<i>Nanotechnology</i><b>30</b>035207).

Nanotechnology·2026
Same author

[Factors related to burnout of nurses working at intensive care units: A descriptive survey study].

Journal of Korean gerontological nursing·2026
Same author

Performance evaluation of deep learning-based osteoporosis diagnostic models with conventional chest X-ray in a clinical cohort.

Journal of thoracic disease·2025
Same author

Integrated Assessment of Growth and Protein Content in Basidiomycetous Fungi for Mycoprotein Production.

Journal of microbiology and biotechnology·2025
Same journal

Effective contrast-enhanced preprocessing for intracranial artery segmentation in digital subtraction angiography.

Physics in medicine and biology·2026
Same journal

Improving Plan Quality in Adaptive Proton Therapy Using an Interactive Dose Modification Tool.

Physics in medicine and biology·2026
Same journal

Technical Note: Real-Time MLC Control and Latency Measurement Optimization with External Verification.

Physics in medicine and biology·2026
Same journal

Fetus-Specific Hematopoietic Stem Cell Dosimetry Framework for Leukemia-Relevant Target Cells During Prenatal Development.

Physics in medicine and biology·2026
Same journal

Deep learning-based dose prediction to enhance planning efficiency in cervical brachytherapy with hybrid applicators.

Physics in medicine and biology·2026
Same journal

Corrigendum: Referenceless MR thermometry-a comparison of five methods (2017<i>Phys. Med. Biol</i>.<b>62</b>1-16).

Physics in medicine and biology·2026
See all related articles

Related Experiment Video

Updated: May 6, 2026

Sample Drift Correction Following 4D Confocal Time-lapse Imaging
10:04

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Published on: April 12, 2014

15.7K

Data-adapted moving least squares method for 3-D image interpolation.

Sumi Jang1, Haewon Nam, Yeon Ju Lee

  • 1Institute of Mathematical Sciences, Ewha Womans University, Seoul, 120-750, Korea.

Physics in Medicine and Biology
|November 13, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a novel nonlinear 3D interpolation method for medical images, improving accuracy by adapting to local image structures. The new technique enhances both quantitative and visual quality compared to existing methods.

More Related Videos

Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography
06:09

Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography

Published on: March 12, 2021

3.3K
Stereo-Imaging System DLT Calibration to Capture 3D In Situ Displacements of Stretched Peripheral Nerves
06:26

Stereo-Imaging System DLT Calibration to Capture 3D In Situ Displacements of Stretched Peripheral Nerves

Published on: January 12, 2024

890

Related Experiment Videos

Last Updated: May 6, 2026

Sample Drift Correction Following 4D Confocal Time-lapse Imaging
10:04

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Published on: April 12, 2014

15.7K
Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography
06:09

Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography

Published on: March 12, 2021

3.3K
Stereo-Imaging System DLT Calibration to Capture 3D In Situ Displacements of Stretched Peripheral Nerves
06:26

Stereo-Imaging System DLT Calibration to Capture 3D In Situ Displacements of Stretched Peripheral Nerves

Published on: January 12, 2024

890

Area of Science:

  • Medical Imaging
  • Computer Vision
  • Numerical Analysis

Background:

  • Accurate interpolation of medical images is crucial for diagnosis and analysis.
  • Existing linear and some nonlinear interpolation methods have limitations in preserving local image structures.

Purpose of the Study:

  • To develop and evaluate a novel nonlinear three-dimensional (3D) interpolation scheme for gray-level medical images.
  • To improve the accuracy and visual quality of interpolated medical image volumes.

Main Methods:

  • The proposed scheme is based on the moving least squares (MLS) method with a fundamental modification.
  • It employs locally data-adapted least squares methods to reproduce polynomials of a certain degree, enhancing local structure matching.
  • The method was tested on five types of medical imaging data: MR brain, MR foot, MR abdomen, CT head, and CT foot.

Main Results:

  • The new nonlinear interpolation method demonstrated superior performance compared to well-known linear and recent nonlinear methods.
  • Quantitative comparisons, following the Grevera and Udupa (1998) paradigm, showed improved Peak Signal-to-Noise Ratio (PSNR) results.
  • Visual quality assessments also indicated better preservation of image details.

Conclusions:

  • The proposed nonlinear 3D interpolation scheme offers significant improvements in both quantitative and visual quality for medical image interpolation.
  • The locally data-adapted approach effectively captures and reproduces local image structures, outperforming existing techniques.