Scalismo - Scalable Image Analysis and Shape Modelling

Scalismo is a library for statistical shape modeling and model-based image analysis in Scala, developed by the Graphics and Vision Research Group at the University of Basel.

The vision of the project is to provide an environment for modelling and image analysis which

• makes it easy and fun to try out ideas and build research prototypes
• is powerful enough to build full-scale industrial applications
• makes it feasible to deploy it in complex, distributed imaging pipelines.

Documentation

• The Scalismo website contains comprehensive documentation including a series of tutorials, API doc and links to further ressources and papers.

How can I help?

While scalismo is already fully usable for shape modeling and simple image processing task, its functionality is currently targeted to support the needs that arise in the research at the Gravis and Vision research group. If you find that a feature is missing, please let us know about it by opening an issue and describing the missing feature.

We welcome contributions to scalismo. Please check the Contributor's guide for instructions how to contribute to Scalismo.

We are also always grateful if you report bugs or if give us feedback on how you use scalismo in your work and how you think we can improve it.

Maintainers

The project is developed and maintained by the University of Basel in collaboration with Shapemeans GmbH. The current maintainers of the project (people who can merge pull requests) are:

• Ghazi Bouabene
• Thomas Gerig
• Marcel Luethi
• Andreas Forster
• Dennis Madsen
• Dana Rahbani
• Patrick Kahr

Related Projects

Scalismo is closely related to the statismo project, and some of the scalismo developers are also actively working on statismo. In fact, scalismo had been started as an attempt to provide the core functionality of Statismo and the ITK registration toolkit, but without the complexity that is induced by these toolkits.

The design of the registration approach used in scalismo is strongly influenced by ITK and Elastix.

Copyright and License

All code is available to you under the Apache license, version 2, available at http://www.apache.org/licenses/LICENSE-2.0.

Copyright, University of Basel, 2023.