SPC-Clean: A napari Plugin for Reducing Speckle and Isolated Pixel Noise in Fluorescence Microscopy Images
Year: 2026
Type: preprint
Abstract: Summary Speckle artifacts and isolated foreground pixels are common in fluorescence microscopy and can interfere with segmentation and subsequent quantitative image analysis. Conventional denoising methods often modify image intensities through filtering or smoothing, potentially altering biologically relevant fluorescence signals. We introduce Sparse Pixel Cluster Cleaning (SPC-Clean), a topology-aware method that removes poorly supported foreground pixels through iterative neighborhood analysis of a thresholded mask. SPC-Clean is deterministic, training-free, preserves original fluorescence intensities for practical microscopy workflows. Availability and implementation SPC-Clean is available as an open-source Python Napari plugin for microscopy image processing. Source code, documentation, and example data are available at: https://github.com/MergenthalerLab/SPC-Clean.git . Contact [email protected] or [email protected]
Language: English
Subfield: Biophysics
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7204459829