Background Remover -- an effective tool for processing noisy microscopy images

TL;DR

Background Remover is a plugin for ImageJ that effectively denoises fluorescent microscopy images with low signal-to-noise ratios, enabling reliable object detection and intensity measurement.

Contribution

It introduces a novel algorithm integrated into ImageJ for improved analysis of noisy microscopy images, with demonstrated performance.

Findings

Effective noise differentiation preserves signal in low SNR images.

Enables reliable object identification in heterogeneous backgrounds.

Provides intensity measurements for detected objects.

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 characterized 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/