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Related Experiment Video

Updated: Nov 18, 2025

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Published on: April 12, 2014

Visual4DTracker: a tool to interact with 3D + t image stacks.

Ermanno Cordelli¹, Paolo Soda², Giulio Iannello²

¹Unit of Computer Systems and Bioinformatics, Department of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy. e.cordelli@unicampus.it.

BMC Bioinformatics

|February 9, 2021

Summary

This summary is machine-generated.

Visual4DTracker is a new MATLAB toolbox for analyzing 4D microscopy image datasets. It aids in particle tracking and feature extraction, enabling detailed analysis of biological phenomena over time.

Keywords:

Blobs Image proofreading MATLAB package Tracking

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Last Updated: Nov 18, 2025

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Area of Science:

Biophysics
Cell Biology
Microscopy Imaging

Background:

High-throughput microscopy generates 4D (3D + time) datasets.
Extracting spatial and temporal data from these datasets is crucial.
Particle tracking and feature extraction require advanced tools.

Purpose of the Study:

Introduce Visual4DTracker, a MATLAB toolbox.
Provide functionalities for navigating, analyzing, and validating particle tracks in 4D image stacks.
Facilitate user-friendly visualization and evaluation of tracking data.

Main Methods:

Developed a MATLAB package with a graphical user interface.
Implemented tools for particle tracking, data navigation, and manual correction.
Validated the software with synthetic data, Drosophila cell growth, and insulin granule dynamics.

Main Results:

Visual4DTracker enables visualization and analysis of 4D microscopy data.
The toolbox allows users to proof-read and evaluate particle traces against a gold standard.
Successfully applied to diverse biological datasets, including cell dynamics and granule analysis.

Conclusions:

Visual4DTracker is a valuable MATLAB software for handling 4D microscopy image stacks.
It offers a user-friendly interface for analyzing and manually tracking objects like cells and granules.
The freely available tool enhances the analysis of spatio-temporal biological data.