Training
Tailored to your expertise level and your needs, these courses allow both users and developers to discover or master the benefit of tools such as CMake, ITK, ParaView, 3D Slicer or VTK.
Training Courses Agenda
| September 29 & 30, 2025 | CMake |
| October 1st, 2025 | 3D Slicer |
| October 2, 2025 | Slicer for developers |
| October 3, 2025 | Introduction to Kitware web technologies |
| October 6, 2025 | ITK |
| October 7, 2025 | MONAI |
| October 8, 2025 | VTK for Data Exploration & Visualization |
| October 9, 2025 | VTK for Application Developers |
| October 10, 2025 | ActiViz |
| October 13, 2025 | ParaView User |
| October 14, 2025 | ParaView Advanced |
| October 15, 2025 | VTK for Medical Imaging |
| October 17, 2025 | VTK for augmented and virtual reality (XR) |
| October 20, 2025 | VTK.js |
| October 21, 2025 | trame |
| October 22, 2025 | LidarView |
| October 23, 2025 | Lidar SLAM |
This course covers in depth how CMake works and how to efficiently write CMake scripts for small to larger projects. The second part of the course covers unit testing with CTest, packaging with CPack and continuous integration with CDash. The training mixes theory and application with a set of tutorials and exercises.
The training mixes theory and application with a set of tutorials and exercises.
This course will introduce trame and go over the basics (reactive state, method calls, custom-widgets, from vue to Python syntax). At the end of the training, each participant will have created, during simple exercises spread along the course, a simple yet powerful trame-based web application with 3D remote and local rendering and with plots and graphical user interface.
The training mixes theory and application with a set of tutorials and exercises.
The Insight Toolkit is a powerful library for image processing and analysis. This course covers the basic architecture of ITK and how to implement algorithms using the framwork.
The objectives of this course will interest users of scientific visualization tools, but also developers willing to customize the interface.
MONAI is a freely available, community-supported, PyTorch-based framework for deep learning in healthcare imaging. It provides domain-optimized foundational capabilities for developing healthcare imaging training workflows in a native PyTorch paradigm. Nvidia is one of the main maintainers of this project.
LidarView performs real-time visualization and processing of LiDAR 3D data captured in real time. It is a ParaView-based application that provides specific real-time network data management for multiple LiDARs brands, as well as post-processing tools related to LiDARs. It also has a specific user interface, focused on real-time visualization and analysis of LiDAR data from leading LiDARs manufacturers.