# New Extension: MassVision

**URL:** <https://discourse.slicer.org/t/new-extension-massvision/44540>\
**Category:** Support\
**Tags:** feature, extensions\
**Created:** [September 21, 2025, 2:28am UTC](https://discourse.slicer.org/t/new-extension-massvision/44540 "2025-09-21T02:28:12Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![Amoon](https://sea2.discourse-cdn.com/flex002/user_avatar/discourse.slicer.org/amoon/32/81160_2.png) [@Amoon](https://discourse.slicer.org/u/Amoon)\
**Post date:** [September 21, 2025, 2:28am UTC](https://discourse.slicer.org/t/new-extension-massvision/44540/1 "2025-09-21T02:28:12Z")

</div>

🚀 Happy to announce the official release of **MassVision** extension v 1.0, now available through the 3D Slicer Extension Manager (compatible with the latest stable release, v5.8.1).

💡 **MassVision** is an end-to-end platform for AI-driven exploration and analysis of mass spectrometry imaging (MSI) data.

[![](https://raw.githubusercontent.com/jamzad/SlicerMassVision/refs/heads/main/MassVision/Resources/Icons/UI_logoM.png) ](https://raw.githubusercontent.com/jamzad/SlicerMassVision/refs/heads/main/MassVision/Resources/Icons/UI_logoM.png)

## Key Features:

- Data compatibility: imzML, structured CSV, hierarchical HDF5, DESI TXT images
- Visualization: targeted (single-ion heatmap, multi-ion colormap), untargeted (global/local contrast PCA, UMAP, t-SNE), multi-pixel spectrum plotting
- Exploration: clustering, segmentation, correlation analysis
- Dataset generation: spatial co-localization with pathology annotations, pathology-guided spatial annotation, spectrum labeling and extraction
- Multi-slide merge: feature alignment, peak matching
- Preprocessing: normalization (TIC, TSC, single-ion, mean, median, RMS), spectral filtering, spatial pixel aggregation
- Statistical analysis: ANOVA, volcano plots, boxplots
- AI model training/validation:
  - Feature ranking (PLS-DA, Linear SVC, LDA)
  - Feature selection (automated, manual)
  - Data stratification (random, patient-based, cross-validation)
  - Data balancing (oversampling, undersampling)
  - Model training (PCA-LDA, Linear SVM, Random Forest, PLS-DA)

- Whole-slide AI deployment: feature matching, global or masked deployment

## Useful Links:

- 💻[Codebase](https://github.com/jamzad/SlicerMassVision)
- 📄[User Manual](https://slicermassvision.readthedocs.io/en/latest/)
- 📕[Publication](https://doi.org/10.1021/acs.analchem.5c04018)

## Demonstrations:

Visualization and exploration

[![](https://raw.githubusercontent.com/jamzad/SlicerMassVision/refs/heads/main/docs/source/Images/visualization.gif) ](https://raw.githubusercontent.com/jamzad/SlicerMassVision/refs/heads/main/docs/source/Images/visualization.gif)

Spatial colocalization

[https://raw.githubusercontent.com/jamzad/SlicerMassVision/refs/heads/main/docs/source/Images/colocalization.gif](https://raw.githubusercontent.com/jamzad/SlicerMassVision/refs/heads/main/docs/source/Images/colocalization.gif)

Pathology guided ROI dataset curation

[https://raw.githubusercontent.com/jamzad/SlicerMassVision/refs/heads/main/docs/source/Images/roi.gif](https://raw.githubusercontent.com/jamzad/SlicerMassVision/refs/heads/main/docs/source/Images/roi.gif)

Statustucal analysis

[![](https://raw.githubusercontent.com/jamzad/SlicerMassVision/refs/heads/main/docs/source/Images/statistical.gif) ](https://raw.githubusercontent.com/jamzad/SlicerMassVision/refs/heads/main/docs/source/Images/statistical.gif)

## Citation

Please use the following citations if you use **MassVision** in your research

A Jamzad, J Warren, A Syeda, M Kaufmann, N Iaboni, C JB Nicol, J F Rudan, K YM Ren, D Hurlbut, S Varma, G Fichtinger, and P Mousavi; "MassVision: An Open-Source End-to-End Platform for AI-Driven Mass Spectrometry Imaging Analysis, _Analytical Chemistry_ 2025, [DOI: 10.1021/acs.analchem.5c04018](https://doi.org/10.1021/acs.analchem.5c04018).