Work

Multispectral Analysis Graphical User Interface for Ratiometric Analysis and Background Correction

Year: 2026

Type: article

Abstract: Chemical imaging is a powerful branch of modern microscopy encumbered by a lack of flexible, high‐throughput analysis tools. Bespoke analytical pipelines typically perform ratiometric analysis on two layers in a multispectral image to describe the relative composition of molecules in a sample. This strategy has been implemented across fields, spanning histopathology, cell biology, environmental science, and materials science. The commercialization of chemical imaging microscopes has facilitated the collection of large multispectral datasets, necessitating accessible ways to process them. This paper describes multispectral analysis graphical user interface (msaGUI), a desktop graphical user interface to analyze individual and batch datasets of multispectral images. Data are loaded as CSV, TSV, or TIFFs and processed through a user‐defined sequence of modular image operations that can be flexibly combined, e.g., to reduce spectral crosstalk or background noise. After analysis, data are visualized as exportable images, histograms, and statistics. To yield publication‐quality figures, output images are fully customizable. Written in Python with open‐source libraries, the msaGUI program is packaged into an executable for Windows and Mac for a fully no‐code application. Other operating systems are supported via the Python source code. In summary, msaGUI provides a rapid, graphical solution for analyzing and visualizing multispectral data.

Source: Chemistry - Methods

DOI: 10.1002/cmtd.70167

Authors: Grayson R. Hoy, Caitlin M. Davis

Institution: Yale University

Language: English

Topic: Cell Image Analysis Techniques

Subfield: Biophysics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,750

Funders: National Science Foundation, Arnold and Mabel Beckman Foundation