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

Potential Due to a Polarized Object01:29

Potential Due to a Polarized Object

738
A neutral atom consists of a positively charged nucleus surrounded by a negatively charged electron cloud. When placed in an external electric field, the external electric force pulls the electrons and nucleus apart, opposite to the intrinsic attraction between the nucleus and the electrons. The opposing forces balance each other with a slight shift between the center of masses of the nucleus and the electron cloud, resulting in a polarized atom. On the other hand, a few molecules, like water,...
738
Potential Due to a Magnetized Object01:24

Potential Due to a Magnetized Object

768
Magnetic dipoles in magnetic materials are aligned when placed under an external magnetic field. For paramagnets and ferromagnets, dipole alignment occurs in the direction of the magnetic field. However, the dipoles align opposite to the field in the case of diamagnets. This state of magnetic polarization due to the external field is called magnetization. Magnetization is defined as the dipole moment per unit volume. It plays a similar role to polarization in electrostatics.
The vector...
768
Two-Dimensional (2D) NMR: Overview01:12

Two-Dimensional (2D) NMR: Overview

1.5K
The 1D NMR spectrum of large and complex molecules like natural products has complicated splitting patterns and overlapping signals, which can be easily interpreted using 2-dimensional (2D) NMR. Unlike 1D NMR, 2D NMR has two frequency axes that provide the coupling information between the nucleus A and nucleus B in a molecule. The process from which 2D spectra are obtained has four steps.
The first step is the preparation period, during which nucleus A is excited with a radiofrequency pulse....
1.5K
Moment of Inertia of Compound Objects01:07

Moment of Inertia of Compound Objects

7.5K
The moment of inertia is a quantitative measure of the rotational inertia of an object. It is defined as the sum of the products obtained by multiplying the mass of each particle of matter in a given body by the square of its distance from the axis. The total moment of inertia for compound objects can be found by determining and adding the moment of inertia of individual components together.
Consider a child of mass (mc) 25 kg standing at a distance (rc) of 1 m from the axis of a rotating...
7.5K
Gravitational Potential Energy for Extended Objects01:07

Gravitational Potential Energy for Extended Objects

1.9K
Consider a system comprising several point masses. The coordinates of the center of mass for this system can be expressed as the summation of the product of each mass and its position vector divided by the total mass:
1.9K
2D NMR: Overview of Homonuclear Correlation Techniques01:16

2D NMR: Overview of Homonuclear Correlation Techniques

626
Homonuclear correlation spectroscopy (COSY) is a powerful technique used in Nuclear Magnetic Resonance (NMR) spectroscopy to study the correlations between nuclei of the same type within a molecule. It provides information about scalar couplings between adjacent nuclei, which helps determine connectivity and structural information. There are several COSY variants, each with its unique strengths and experimental parameters.
COSY90 is the standard two-dimensional (2D) COSY experiment that...
626

You might also read

Related Articles

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

Sort by
Same author

Emergent Surface Multiferroicity.

Physical review letters·2025
Same author

Longitudinal Assessment of Abnormal Cortical Folding in Fetuses and Neonates With Isolated Non-Severe Ventriculomegaly.

Brain and behavior·2025
Same author

Deep cascaded registration and weakly-supervised segmentation of fetal brain MRI.

Heliyon·2025
Same author

Spectroscopic signatures and origin of hidden order in Ba<sub>2</sub>MgReO<sub>6</sub>.

Nature communications·2024
Same author

On the sign of the linear magnetoelectric coefficient in Cr<sub>2</sub>O<sub>3</sub>.

Journal of physics. Condensed matter : an Institute of Physics journal·2024
Same author

Effects of Mediterranean diet or mindfulness-based stress reduction on fetal and neonatal brain development: a secondary analysis of a randomized clinical trial.

American journal of obstetrics & gynecology MFM·2023

Related Experiment Video

Updated: Jan 20, 2026

Author Spotlight: Insights into the Analysis of Human Interaction with 3D Virtual Objects
06:36

Author Spotlight: Insights into the Analysis of Human Interaction with 3D Virtual Objects

Published on: October 18, 2024

1.4K

2D + Time Object Tracking Using Fiji and ilastik.

Andrea Urru1, Miguel Angel González Ballester1,2, Chong Zhang3

  • 1BCN-MedTech, DTIC, Universitat Pompeu Fabra, Barcelona, Spain.

Methods in Molecular Biology (Clifton, N.J.)
|August 22, 2019
PubMed
Summary
This summary is machine-generated.

We present two cell tracking methods using Fiji and ilastik software. These approaches simplify cell detection and tracking in microscopy images, addressing challenges like low signal-to-noise ratio and numerous cells.

Keywords:
Cell trackingClassificationFijiSegmentationilastik

More Related Videos

Author Spotlight: Quantifying Rough Eye Phenotypes in Drosophila Models of Amyotrophic Lateral Sclerosis with Frontotemporal Dementia
05:25

Author Spotlight: Quantifying Rough Eye Phenotypes in Drosophila Models of Amyotrophic Lateral Sclerosis with Frontotemporal Dementia

Published on: October 4, 2024

1.6K
Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
07:31

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

7.2K

Related Experiment Videos

Last Updated: Jan 20, 2026

Author Spotlight: Insights into the Analysis of Human Interaction with 3D Virtual Objects
06:36

Author Spotlight: Insights into the Analysis of Human Interaction with 3D Virtual Objects

Published on: October 18, 2024

1.4K
Author Spotlight: Quantifying Rough Eye Phenotypes in Drosophila Models of Amyotrophic Lateral Sclerosis with Frontotemporal Dementia
05:25

Author Spotlight: Quantifying Rough Eye Phenotypes in Drosophila Models of Amyotrophic Lateral Sclerosis with Frontotemporal Dementia

Published on: October 4, 2024

1.6K
Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
07:31

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

7.2K

Area of Science:

  • * Cell biology and microscopy image analysis.
  • * Bioimage informatics and computational biology.

Background:

  • * Accurate cell tracking in biological research is crucial but challenging due to time-consuming manual annotations and low signal-to-noise ratios in microscopy images.
  • * Large numbers of cells in images further complicate automated detection and tracking processes.
  • * Existing methods often require significant manual intervention, limiting throughput and reproducibility.

Purpose of the Study:

  • * To introduce two distinct, open-source methods for automated cell detection and tracking in time-lapse microscopy.
  • * To provide step-by-step guidance for implementing these methods using Fiji and ilastik.
  • * To offer practical solutions for overcoming common challenges in cell tracking, such as low image quality and cell merging.

Main Methods:

  • * **Fiji Method:** A straightforward approach involving image pre-processing, segmentation, and object-based tracking through overlapping analysis in image sequences.
  • * **Ilastik Method:** A machine learning-based approach where a classifier is trained via manual annotations to detect cells, identify false positives, and manage merging events.
  • * Both methods were exemplified using a time-lapse microscopy dataset of HeLa cells.

Main Results:

  • * Demonstrated the efficacy of both Fiji and ilastik frameworks for cell detection and tracking.
  • * Provided a reproducible, step-by-step protocol for each method.
  • * Showcased the ability of the ilastik method to handle complex scenarios like false detections and cell merging through classifier training.

Conclusions:

  • * The Fiji and ilastik frameworks offer accessible and effective solutions for automated cell tracking in biological research.
  • * These methods can significantly reduce the time and effort required for cell tracking compared to manual annotation.
  • * The presented protocols facilitate the adoption of advanced image analysis techniques in microscopy-based studies.