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

Entropy02:39

Entropy

Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
State Space Representation01:27

State Space Representation

The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and reduce chemical noise during analyte detection. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...

You might also read

Related Articles

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

Sort by
Same author

Kinematic tracking of the small bones of the wrist in sequential 3DCT and dynamic 4DCT volume images using open-source Hierarchical 3D Registration, a module within SlicerAutoscoper<sup>M</sup>.

Biomedical engineering online·2026
Same author

BIBSNet: A deep learning baby image brain segmentation network for MRI scans.

Developmental cognitive neuroscience·2026
Same author

Infant subcortical brain volumes associated with maternal obesity and diabetes: a large multicohort human study.

BMC medicine·2026
Same author

Increased CSF volume, altered brain development and emotional reactivity after postnatal Zika virus infection in infant rhesus macaques.

bioRxiv : the preprint server for biology·2026
Same author

Long-term associations between perinatal factors and white matter microstructure at 8-10 years.

Frontiers in human neuroscience·2026
Same author

Maternal depression with and without a history of childhood maltreatment and newborn white matter microstructure.

Psychological medicine·2026
Same journal

From Geometry to Intensity: A Coarse-to-Fine Pipeline for Unsupervised 3D Ultrasound Stitching.

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
See all related articles

Related Experiment Video

Updated: May 8, 2026

Assembly and Characterization of Polyelectrolyte Complex Micelles
08:44

Assembly and Characterization of Polyelectrolyte Complex Micelles

Published on: March 2, 2020

Combined SPHARM-PDM and entropy-based particle systems shape analysis framework.

Beatriz Paniagua1, Lucile Bompard, Josh Cates

  • 1University of North Carolina at Chapel Hill, Department of Psychiatry;

Proceedings of Spie--The International Society for Optical Engineering
|September 13, 2013
PubMed
Summary
This summary is machine-generated.

This study combines SPHARM-PDM and entropy-based particle systems for improved 3D shape analysis. The new framework enhances correspondence accuracy for complex biological shapes, benefiting morphometry studies.

Keywords:
3DSlicerSpherical harmonic representationentropy-based particle systemsshape analysis frameworkstatistical shape analysis

More Related Videos

High-resolution Single Particle Analysis from Electron Cryo-microscopy Images Using SPHIRE
13:28

High-resolution Single Particle Analysis from Electron Cryo-microscopy Images Using SPHIRE

Published on: May 16, 2017

Related Experiment Videos

Last Updated: May 8, 2026

Assembly and Characterization of Polyelectrolyte Complex Micelles
08:44

Assembly and Characterization of Polyelectrolyte Complex Micelles

Published on: March 2, 2020

High-resolution Single Particle Analysis from Electron Cryo-microscopy Images Using SPHIRE
13:28

High-resolution Single Particle Analysis from Electron Cryo-microscopy Images Using SPHIRE

Published on: May 16, 2017

Area of Science:

  • Medical imaging analysis
  • Computational anatomy
  • Biomedical engineering

Background:

  • Statistical shape analysis is crucial for understanding biological structures.
  • Existing methods like SPHARM-PDM struggle with complex biological shapes due to parameterization limitations.
  • Entropy-based particle systems offer an alternative but are sensitive to initial conditions.

Purpose of the Study:

  • To develop a robust method for computing reliable correspondences in topologically challenging biological shapes.
  • To integrate SPHARM-PDM and entropy-based particle systems for enhanced shape analysis.
  • To provide an accessible, end-to-end solution for shape analysis.

Main Methods:

  • Utilized MR brain images of diverse subcortical structures.
  • Employed SPHARM-PDM to generate point-based correspondent models for initialization.
  • Integrated SPHARM-PDM models with entropy-based particle systems within a Slicer3 module.

Main Results:

  • The combined SPHARM-PDM-Particle framework significantly improved correspondence accuracy compared to conventional SPHARM-PDM.
  • Demonstrated enhanced performance on an example dataset of subcortical structures.
  • The integrated module functions as an end-to-end shape analysis solution.

Conclusions:

  • The novel framework successfully addresses correspondence challenges in complex biological shapes.
  • This advancement facilitates morphometry studies by enabling accurate analysis of spherically topological shapes.
  • The user-friendly module lowers the barrier for researchers lacking specialized computational expertise.