mtFRC: depth-dependent resolution quantification of image features in 3D fluorescence microscopy
File(s)vbad182.pdf (1.61 MB)
Published version
Author(s)
Wright, Neil
Rowlands, Christopher J
Type
Journal Article
Abstract
MOTIVATION: Quantifying lateral resolution as a function of depth is important in the design of 3D microscopy experiments. However, for many specimens, resolution is non-uniform within the same optical plane because of factors such as tissue variability and differential light scattering. This precludes application of a simple resolution metric to the image as a whole. In such cases, it can be desirable to analyse resolution only within specific, well-defined features. RESULTS: An algorithm and software are presented to characterize resolution as a function of depth in features of arbitrary shape in 3D samples. The tool can be used to achieve an objective comparison between different preparation methods, imaging parameters, and optical systems. It can also inform the design of experiments requiring resolution of structures at a specific scale. The method is demonstrated by quantifying the improvement in resolution of two-photon microscopy over confocal in the central brain of Drosophila melanogaster. Measurement of image quality increases by tuning a single parameter, laser power, is also shown. An ImageJ plugin implementation is provided for ease of use via a simple Graphical User Interface, with outputs in table, graph, and colourmap formats. AVAILABILITY AND IMPLEMENTATION: Software and source code are available at https://www.imperial.ac.uk/rowlands-lab/resources/.
Date Issued
2023-12-01
Date Acceptance
2023-12-14
Citation
Bioinformatics Advances, 2023, 3 (1)
ISSN
2635-0041
Publisher
Oxford University Press
Journal / Book Title
Bioinformatics Advances
Volume
3
Issue
1
Copyright Statement
© The Author(s) 2023. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which
permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/38146539
PII: vbad182
Publication Status
Published
Coverage Spatial
England
Article Number
vbad182
Date Publish Online
2023-12-18