mspacman: A modular python package for three-dimensional (3D) partial volume corrected particle characterization using X-ray computed tomography

Three-dimensional (3D) particle characterization using X-ray Computed Tomography (CT) enables detailed analysis of particle geometry and composition; however, its accuracy is limited by partial volume blur (PVB). To address this challenge, mspacman, an open-source Python package, is developed to model PVB using a linear mixing approach applied to grey value histograms of individual particles. It supports samples containing up to 11 mineral phases and can quantify particles with up to 5 distinct mineral phases. mspacman semi-automates the entire analysis pipeline, including image upload, extraction of geometrical and intensity properties, histogram extraction, phase quantification, and bootstrapped uncertainty estimation. The package provides a scalable solution for high-resolution mineral characterization.