VIPP: A visual image processing pipeline for fluorescence microscopy analysis
Sharratt EL, Vahrmeijer N, Loos B, Theart RP
GloBIAS Symposium 2025 – Open-Source Software Lounge (OSSL), Kobe, Japan,
29 October 2025
Abstract
Fluorescence microscopy datasets pose significant challenges for image analysis due to the complexity of multi-stage processing pipelines and the prevalence of noise and artifacts. Each pipeline stage typically requires careful parameter tuning, and improper configuration can adversely affect downstream analyses, especially in morphology-driven studies that depend on accurate segmentation. Many researchers in the biological sciences—particularly those without a background in image processing—rely on pre-built pipelines that are poorly optimized for their specific data, often leading to suboptimal or misleading results.
We introduce the Visual Image Processing Pipeline (VIPP), a novel, interactive tool designed to simplify and demystify the construction of image analysis pipelines. VIPP provides a modular, node-based interface where each node represents a specific image processing operation with configurable parameters. Unlike traditional tools, VIPP features real-time visual feedback, enabling users to immediately observe the effects of parameter changes. This dynamic interaction fosters a deeper understanding of the relationship between settings and output, guiding users toward better-optimized analyses.
In testing with biologists, VIPP demonstrated clear benefits in both output quality and user comprehension. Users reported improved confidence in parameter selection and a greater appreciation of the nuances of image processing. While VIPP currently offers a streamlined feature set compared to advanced expert tools, its extensibility and usability make it a practical solution for routine tasks in fluorescence microscopy. VIPP represents a step toward democratizing image processing by equipping researchers with a tool that is both powerful and approachable.