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Open Access 17-06-2024

Image Analysis Using the Fluorescence Imaging of Nuclear Staining (FINS) Algorithm

Authors: Laura R. Bramwell, Jack Spencer, Ryan Frankum, Emad Manni, Lorna W. Harries

Published in: Journal of Imaging Informatics in Medicine

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Abstract

Finding appropriate image analysis techniques for a particular purpose can be difficult. In the context of the analysis of immunocytochemistry images, where the key information lies in the number of nuclei containing co-localised fluorescent signals from a marker of interest, researchers often opt to use manual counting techniques because of the paucity of available tools. Here, we present the development and validation of the Fluorescence Imaging of Nuclear Staining (FINS) algorithm for the quantification of fluorescent signals from immunocytochemically stained cells. The FINS algorithm is based on a variational segmentation of the nuclear stain channel and an iterative thresholding procedure to count co-localised fluorescent signals from nuclear proteins in other channels. We present experimental results comparing the FINS algorithm to the manual counts of seven researchers across a dataset of three human primary cell types which are immunocytochemically stained for a nuclear marker (DAPI), a biomarker of cellular proliferation (Ki67), and a biomarker of DNA damage (γH2AX). The quantitative performance of the algorithm is analysed in terms of consistency with the manual count data and acquisition time. The FINS algorithm produces data consistent with that achieved by manual counting but improves the process by reducing subjectivity and time. The algorithm is simple to use, based on software that is omnipresent in academia, and allows data review with its simple, intuitive user interface. We hope that, as the FINS tool is open-source and is custom-built for this specific application, it will streamline the analysis of immunocytochemical images.

Graphical Abstract

In this paper, we describe a new tool—the Fluorescence Imaging of Nuclear Staining (FINS) algorithm. This tool can automatically count images of cells that are immunocytochemically stained with a nuclear protein of interest, producing a spreadsheet of counts and a user interface for review.
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Metadata
Title
Image Analysis Using the Fluorescence Imaging of Nuclear Staining (FINS) Algorithm
Authors
Laura R. Bramwell
Jack Spencer
Ryan Frankum
Emad Manni
Lorna W. Harries
Publication date
17-06-2024
Publisher
Springer International Publishing
Published in
Journal of Imaging Informatics in Medicine
Print ISSN: 2948-2925
Electronic ISSN: 2948-2933
DOI
https://doi.org/10.1007/s10278-024-01097-8