Abstract
BackgroundBiological phenomena usually evolves over time and recent advances in high-throughput microscopy have made possible to collect multiple 3D images over time, generating 3D+t (or 4D) datasets. To extract useful information there is the need to extract spatial and temporal data on the particles that are in the images, but particle tracking and feature extraction need some kind of assistance.ResultsThis manuscript introduces our new freely downloadable toolbox, the Visual4DTracker. It is a MATLAB package implementing several useful functionalities to navigate, analyse and proof-read the track of each particle detected in any 3D+t stack. Furthermore, it allows users to proof-read and to evaluate the traces with respect to a given gold standard. The Visual4DTracker toolbox permits the users to visualize and save all the generated results through a user-friendly graphical user interface. This tool has been successfully used in three applicative examples. The first processes synthetic data to show all the software functionalities. The second shows how to process a 4D image stack showing the time-lapse growth of Drosophila cells in an embryo. The third example presents the quantitative analysis of insulin granules in living beta-cells, showing that such particles have two main dynamics that coexist inside the cells.ConclusionsVisual4DTracker is a software package for MATLAB to visualize, handle and manually track 3D+t stacks of microscopy images containing objects such cells, granules, etc.. With its unique set of functions, it remarkably permits the user to analyze and proof-read 4D data in a friendly 3D fashion. The tool is freely available at https://drive.google.com/drive/folders/19AEn0TqP-2B8Z10kOavEAopTUxsKUV73?usp=sharing
Highlights
Biological phenomena usually evolves over time and recent advances in high-throughput microscopy have made possible to collect multiple 3D images over time, generating 3D + t datasets
Dynamic investigations make use of time-lapse microscopy, where microscope image sequences are recorded and observed at a greater speed to give an accelerated view of the process
The first case is fully presented in the supplementary instruction manual, and it is a step-by-step toy example that guides the user through all the main phases
Summary
Biological phenomena usually evolves over time and recent advances in high-throughput microscopy have made possible to collect multiple 3D images over time, generating 3D + t (or 4D) datasets. Biological phenomena have in general a 3D nature, time-lapse experiments traditionally collect a series of 2D images over time, referred to as 2D + t datasets This approach may lose relevant 3D information and, to overcome this limitation, recent advances in high-throughput microscopy have made possible to image multiple z-positions of the sample in a time that is at least an order of magnitude smaller than the time scale of the biological process. This makes possible to collect 3D image stacks of the sample at different times, generating 3D + t datasets ( referred to as 4D in the following). It overcomes the main limitations of open source tools currently available, as described
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
