<i>Background Remover</i> – An effective tool for processing noisy microscopy images

Background Remover (BGR) is a novel software tool developed as a plugin to the well-known ImageJ program and designed to address the challenges of analysing fluorescent microscopy images characterised by low signal-to-noise ratios and heterogeneous backgrounds. The used algorithm effectively differentiates between signal and noise pixels, preserving the signal while eliminating noise. This functionality enables the analysis of images with objects of varying intensities, allowing for reliable identification even in low signal-to-noise ratio conditions. Furthermore, BGR offers the capability to determine the intensity of identified objects, enhancing its utility for researchers in the field. The paper describes the algorithm and the program functioning, as well as the carried out tests of its performance. The program is freely downloadable from the website https://kilianna.github.io/background-remover/.

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Publication Details

Journal
Journal of Microscopy
Published
2025-06-24
DOI
https://doi.org/10.1111/jmi.70002
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Background Remover – An effective tool for processing noisy microscopy images

Małgorzata Sankowska, P. Bilski, A. Kilian
Journal of Microscopy
Cell Image Analysis Techniques
article

Background Remover – An effective tool for processing noisy microscopy images

Małgorzata Sankowska, P. Bilski, A. Kilian
article en

Abstract

Background Remover (BGR) is a novel software tool developed as a plugin to the well-known ImageJ program and designed to address the challenges of analysing fluorescent microscopy images characterised by low signal-to-noise ratios and heterogeneous backgrounds. The used algorithm effectively differentiates between signal and noise pixels, preserving the signal while eliminating noise. This functionality enables the analysis of images with objects of varying intensities, allowing for reliable identification even in low signal-to-noise ratio conditions. Furthermore, BGR offers the capability to determine the intensity of identified objects, enhancing its utility for researchers in the field. The paper describes the algorithm and the program functioning, as well as the carried out tests of its performance. The program is freely downloadable from the website https://kilianna.github.io/background-remover/.

Journal of MicroscopyVol. 300(1)
Institute of Nuclear Physics, Polish Academy of Sciences (PL)
Narodowym Centrum Nauki
Openalex Percentile: Top 89%
Cell Image Analysis Techniques
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