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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

438
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
438
Navier–Stokes Equations01:28

Navier–Stokes Equations

2.8K
For incompressible Newtonian fluids, where density remains constant, stresses show a linear relationship with the deformation rate, defined by normal and shear stresses. Normal stresses depend on the pressure exerted on the fluid and the rate of deformation in specific directions, which determines how fluid flows under varying pressures. Shear stresses, on the other hand, act tangentially across fluid layers. They explain how adjacent fluid layers slide relative to one another, connecting...
2.8K
Newtonian Fluid: Problem Solving01:18

Newtonian Fluid: Problem Solving

1.1K
Newtonian fluids exhibit a constant viscosity, meaning their shear stress and shear strain rate are directly proportional. This property ensures a predictable and stable response to applied forces, maintaining a linear relationship between force and flow. Examples include water, air, and light oils, consistently demonstrating this proportional behavior regardless of external conditions.
A velocity gradient forms within the fluid when a Newtonian fluid is placed between two parallel plates, with...
1.1K
Control Volume and System Representations01:16

Control Volume and System Representations

1.4K
Two key frameworks are employed to analyze mass, energy, and momentum transfer: the control volume approach and the system approach. These frameworks offer different perspectives, depending on whether the focus is on a specific region in space (control volume approach) or a defined mass of fluid (system approach).
The control volume approach considers a stationary region in space through which fluid flows. This region is bounded by a control surface.  For instance, in the case of water...
1.4K
Typical Model Studies01:30

Typical Model Studies

842
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
842
Implicit Differentiation: Problem Solving01:29

Implicit Differentiation: Problem Solving

183
Curves defined implicitly, where variables cannot be separated algebraically, require specialized techniques for analysis. The conchoid of Nicomedes exemplifies such a case. Its equation links x and y in a way that prevents isolation of one variable, making implicit differentiation essential to determine the slope and behavior at any point on the curve.The implicit form of the conchoid can be expressed as:To differentiate this equation, y is treated as a function of x, and the chain rule is...
183

You might also read

Related Articles

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

Sort by
Same author

A single-cell transcriptomic atlas of inner ear morphogenesis in zebrafish.

bioRxiv : the preprint server for biology·2025
Same author

Tissue fluidity mediates a trade-off between the speed and accuracy of multicellular patterning by cell sorting.

Biophysical journal·2025
Same author

Tissue Fluidity Mediates a Trade-off Between the Speed and Accuracy of Multicellular Patterning by Cell Sorting.

bioRxiv : the preprint server for biology·2025
Same author

A Knock-in Zebrafish Reporter Line for Live Visualization of Endogenous Olig2 Protein Dynamics.

Zebrafish·2025
Same author

Microtubules regulate tissue-level navigation in skin-resident macrophages.

Journal of cell science·2025
Same author

Formation control between leader and migratory follower tissues allows coordinated growth.

Science advances·2025

Related Experiment Video

Updated: May 3, 2026

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization
08:03

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Published on: November 12, 2014

9.9K

An efficient, scalable, and adaptable framework for solving generic systems of level-set PDEs.

Kishore R Mosaliganti1, Arnaud Gelas1, Sean G Megason1

  • 1Department of Systems Biology, Harvard Medical School Boston, MA, USA.

Frontiers in Neuroinformatics
|February 7, 2014
PubMed
Summary

A new software design in the Insight Toolkit (ITK) v4 simplifies level-set methods for medical image analysis. This flexible framework streamlines development for image registration, segmentation, and tracking, reducing code duplication and enhancing algorithm customization.

Keywords:
Insight Toolkitdesignimplementationlevel-setsoftware

Related Experiment Videos

Last Updated: May 3, 2026

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization
08:03

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Published on: November 12, 2014

9.9K

Area of Science:

  • Medical image analysis
  • Computational imaging
  • Scientific visualization

Background:

  • Level-set methods are crucial for image registration, segmentation, tracking, and reconstruction.
  • Existing toolkits present software logistics challenges due to rigid designs, hindering algorithm development and requiring extensive code duplication.
  • Lack of integrative design limits flexibility in implementing various partial differential equations (PDEs), stopping criteria, and reinitialization strategies.

Purpose of the Study:

  • To introduce a flexible and integrative level-set software design within the Insight Toolkit (ITK) v4 architecture.
  • To overcome the limitations of current toolkits by enabling easier customization and extension of level-set algorithms.
  • To optimize the development process for complex image analysis tasks.

Main Methods:

  • Implemented a container-based software design for level-set methods, allowing dynamic addition or deletion of PDE terms.
  • Supported diverse numerical representations (continuous, discrete, sparse) and grid types (point, mesh, image-based).
  • Optimized computations by eliminating redundant calculations of common intensity functions and enabled multithreading for large datasets and multiple level-sets.

Main Results:

  • The new ITK v4 framework offers flexibility in customizing level-set equations at compile-time.
  • Achieved optimized performance by eliminating repeated computations of gradient and Hessian functions.
  • Enabled multi-object segmentation and processing of large datasets through domain restriction and multithreading.
  • Developed a real-time visualization tool to aid algorithm development and parameter tuning.

Conclusions:

  • The ITK v4 level-set framework provides a flexible and efficient solution for advanced medical image analysis.
  • This design facilitates easier exploration and customization of level-set algorithms, accelerating research and development.
  • Demonstrated effectiveness using confocal microscopy images of zebrafish embryo cells for segmentation and analysis.