Mass Spectrometry Imaging (MSI) generates large datasets that require efficient computational solutions for data handling and visualization. While R and Python are commonly used for MSI analysis, their limited performance can hinder Big Data workflows. Julia is a high-performance programming language widely adopted in computationally demanding fields such as physics and economics. Here, we present JuliaMSI, a graphical user interface (GUI) developed in Julia for reading and analyzing MSI data in open formats (.imzML, .ibd, .mzML). JuliaMSI accelerates data loading, preprocessing, and visualization, with benchmarks showing up to 4.2-fold faster processing on Windows/macOS and 5.2-fold on Linux compared to R-based tools. Beyond speed, JuliaMSI enables interactive analysis through features such as contrast-enhancing filters (TrIQ, median filter), 3D topographic visualizations of ion intensity landscapes, and overlays of ion images with optical reference images. Users can inspect mass spectra linked to ion images, select regions of interest (ROI), and export results in publication-ready formats (.png, .jpg, .bmp). The platform supports seamless integration with downstream workflows via open data standards and provides a computationally efficient, user-friendly environment for large-scale MSI analysis. JuliaMSI is cross-platform (Linux, macOS, Windows) and available under the MIT license at https://codeberg.org/LabABI/JuliaMSI

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