m2aia/pym2aia-examples-msi-self-supervised-clustering

Autonomous and accurate clustering of co-localized ion images in a self-supervised manner.

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M²aia: a mass spectrometry imaging applications for interactive analysis in MITK

M²aia is open source software, based on the well-known Medical Imaging Interaction Toolkit (MITK). The software enables interactive visualization, signal-processing, 3D reconstruction and multi-modal image registration of mass spectrometry imaging (MSI) datasets.

More information

github.io/m2aia
Build instructions (windows/Linux)
Protocols

Cite M²aia

Cordes J; Enzlein T; Marsching C; Hinze M; Engelhardt S; Hopf C; Wolf I (July, 2021): M²aia - Interactive, fast and memory efficient analysis of 2D and 3D multi-modal mass spectrometry imaging data https://doi.org/10.1093/gigascience/giab049

biotools:m2aia

Docker

To use M²aia in a browser run:

docker pull ghcr.io/m2aia/m2aia:latest
docker run --rm -v /local/data/path:/data -p 8888:80 ghcr.io/m2aia/m2aia:latest

with password:

docker run --rm -v /local/data/path:/data -e VNC_PASSWORD=<password> -p 8888:80 ghcr.io/m2aia/m2aia:latest

Start M²aia by accessing http://localhost:8888

The container will shut down if M²aia is closed (File->Exit). The results written to the mapped volume have root user ownership

Python

We provide ImzML Reader and the Signal Processing utilities for Python.

https://github.com/m2aia/pym2aia
https://github.com/m2aia/pym2aia-examples

Contact

If you have questions about the application or if you would like to give us feedback, don't hesitate to open a new issue or contact me directly.