A geoscientific tool to interpret mineral phase maps elaborated with modern microcopy image analysis pipelines.
Version: 1 (beta)
Author: Dr Marco Acevedo Z. (maaz.geologia@gmail.com)
Affiliation: School of Earth and Atmospheric Sciences, Queensland University of Technology
Date: November 2025
Citation: Acevedo Zamora & Kamber 2023
Previous versions: Original repository
Phase interpreter assists researchers in saving mineral phase maps and performing basic image analysis that are essential to study geological processes. It generates a structured output folder with files corresponding to the selected analyses for each 'Trial tag' (see interface) to support findings and encourage future (or retrospective) reuse of research data (thin sections, polished blocks, resin mounts).
The tool is useful for users wanting to combine the capabilities of light microscopy and X-ray/electron microscope imaging systems using a much larger image analysis pipeline (see citations at the bottom of page). Previous image analysis (segmentation) is done in QuPath (Bankhead et al., 2017) using the pixel classifier tool.
- Graphical User Interface (GUI) following three steps for reprocessing the input maps from QuPath
- Seamless selection of trained classifier outputs for each run
- Removal of the background class using the original names that are excluded from the analysis (e.g. hole, epoxy, cracks, mixed phases)
- Basic image processing to allow creating sample the foreground mask (e.g. dilation, rotation, mirroring) and checking the Preview
- Menu for editing mineral names of the ranked phases following a desired nomenclature (and resorting the targets)
- Focus the analysis on a region of interest (ROI) to avoid analysing uninteresting areas and reducing computational cost
- Varied pool of textural analysis: phase map, modal mineralogy, association, granulometry
- Automatic metadata extraction from input QuPath project containing:
- Saved pixel classifier - Process metadata and machine learning model saved in the QuPath > Classify > Pixel classification > Train pixel classifier
- Saved predicted map - File with the same basename as the classifier and often saved after classifying the entire sample (*.ome.tif) .
- Steps metadata - CSV files are saved tracking the semantic and numerical outputs from each processing step within the GUI and allow reproducibility.
- Grid design - adapts to the window size
- MatLab R2024b
- MatLab App Designer
- Additional libraries for metadata extraction:
*The standanlone App can be produced from:
Operating System: Microsoft Windows 11 Enterprise Version 10.0 (Build 22631) Java Version: Java 1.8.0_202-b08 with Oracle Corporation Java HotSpot(TM) 64-Bit Server VM mixed mode
- MATLAB Version 24.2 (R2024b)
- Computer Vision Toolbox Version 24.2 (R2024b)
- Curve Fitting Toolbox Version 24.2 (R2024b)
- Deep Learning Toolbox Version 24.2 (R2024b)
- Fixed-Point Designer Version 24.2 (R2024b)
- Global Optimization Toolbox Version 24.2 (R2024b)
- Image Processing Toolbox Version 24.2 (R2024b)
- MATLAB Compiler Version 24.2 (R2024b)
- Mapping Toolbox Version 24.2 (R2024b)
- Optimization Toolbox Version 24.2 (R2024b)
- Parallel Computing Toolbox Version 24.2 (R2024b)
- Signal Processing Toolbox Version 24.2 (R2024b)
- Statistics and Machine Learning Toolbox Version 24.2 (R2024b)
- Symbolic Math Toolbox Version 24.2 (R2024b)
- Wavelet Toolbox Version 24.2 (R2024b)
- Graphical user interface (GUI)
- Development script that allows trialling new implementation ideas before editing the GUI
- Open MatLab > App Designer
- Open "Phaseinterpreterv1.prj".
- Go to App Designer > Share > Standalone Desktop App
- Within Apps required for your application to run, add the folders of the additional libraries (living within your PC)
- Click "Package" button while having selected "Runtime included in package" (for future users not having MatLab runtime)
- A folder "Phaseinterpreterv1" will appear containing:
- for_redistribution: installer that can be shared with others (users not having MatLab runtime)
- for_redistribution_files_only: executable (when having the runtime)
- for_testing: executable (when having the runtime)
- Contact me if:
- Requiring an example dataset to operate the software
- Having issues to compile or wanting to make a new branch/pull request that I need to revise
- This is a beta version that will soon be improved with user feedback
- If you are not familiar to coding but have a bunch of ideas, contact me
- I had in mind:
- Making TESCAN TIMA mineral liberation maps compatible with Phase interpreter
- Rewriting "Phase interpreter" in Python and enabling whole-slide imaging to match the capabilities of Cube converter, Chemistry simplifier, and QuPath
- I have not tried this software in Mac or Linux yet but it might be an easy fix
This software depends on vibrant open-source software components and scientific citations/feedback. The following research papers already have contributed to its evolution directly or indirectly:
- Acevedo Zamora, M. A., & Kamber, B. S. (2023). Petrographic Microscopy with Ray Tracing and Segmentation from Multi-Angle Polarisation Whole-Slide Images. Minerals, 13(2), 156. https://doi.org/10.3390/min13020156
- Acevedo Zamora, M. A., Kamber, B. S., Jones, M. W. M., Schrank, C. E., Ryan, C. G., Howard, D. L., Paterson, D. J., Ubide, T., & Murphy, D. T. (2024). Tracking element-mineral associations with unsupervised learning and dimensionality reduction in chemical and optical image stacks of thin sections. Chemical Geology, 650, 121997. https://doi.org/10.1016/j.chemgeo.2024.121997
- Acevedo Zamora, M. (2024). Petrographic microscopy of geologic textural patterns and element-mineral associations with novel image analysis methods [Thesis by publication, Queensland University of Technology]. Brisbane. https://eprints.qut.edu.au/248815/
- Ubide, T., Murphy, D. T., Emo, R. B., Jones, M. W. M., Acevedo Zamora, M. A., & Kamber, B. S. (2025). Early pyroxene crystallisation deep below mid-ocean ridges. Earth and Planetary Science Letters, 663, 119423. https://doi.org/10.1016/j.epsl.2025.119423
- Kamber, B. S., Acevedo Zamora, M. A., Rodrigues, R. F., Li, M., Yaxley, G. M., & Ng, M. (2025). Exploring High PT Experimental Charges Through the Lens of Phase Maps. Minerals, 15(4), 355. https://doi.org/10.3390/min15040355
- Rodrigues, R. F., Yaxley, G. M., & Kamber, B. S. (2025). Phase relations and solidus temperature of garnet lherzolite at 5 GPa revisited. Contributions to Mineralogy and Petrology, 180(9), 57. https://doi.org/10.1007/s00410-025-02250-4
Thank you. Marco