This advanced course is designed for those who have a solid foundation in 3D Slicer and aim to deepen their knowledge and skills.
This beginner course will introduce participants to the fundamental aspects of 3D Slicer, a free and open source software package for image analysis and scientific visualization. The course will guide participants in understanding the software interface, data loading and visualization functionality, and segmentation and registration capabilities.
This course will focus on teaching the fundamental concepts of Computational Model Builder (CMB) and the Simulation Model ToolKit (SMTK) which (along with ParaView and VTK) CMB applications are based on. In the course you will learn how to model and export information required by simulations, mesh generators, or other pre-processing tools using SMTK’s attribute resource, views, and operation infrastructure.
This CMake training covers how to efficiently write CMake scripts for small to larger projects along with best practices. This training also provides an overview of unit testing with CTest, packaging with CPack and continuous integration with CDash.
This course shows how to create or wrap an image processing or ML workflow so that it can be used by the HistomicsTK / Digital Slide Archive platform, generating editable annotations that can be accessed and used in other tools.
This course guides attendees on cutting-edge, advanced methods to utilize ITK in WebAssembly, apply deep learning methods, and extend the toolkit with custom methods through hands-on exercises explained by the toolkit's authors.
This course provides an introduction to the toolkit's purpose, functionality, and architecture through hands-on exercises explained by the toolkit's authors.
This is an intensive course intended to give clinicians, biomedical researchers, and medical industry professionals practical knowledge to help them determine how to incorporate medical image AI into their practice, research, processes, and products. Special emphasis is placed on MONAI, the freely available, open-source platform for medical image AI research and product development.
This course will allow you to look “under the hood” of the ParaView application and provide you with a detailed understanding of ParaView’s framework as well as how to customize it in order to better suit your visualization needs.
This course provides an overview of ParaView, including how to visualize and process data. The examples are based on use cases from several scientific domains.
This course provides a practical, hands-on introduction to building custom image-guided and robotic surgery systems using 3D Slicer, with a focus on Kitware’s proven workflows for research-to-commercial translation.
This course provides a practical, hands-on exploration of real-world issues and best practices in working with DICOM medical imaging data.
Are you managing complex software stacks, struggling with inconsistent builds, or spending too much time wrangling dependencies? Spack was built to solve exactly these challenges—and this live course will teach you how to make the most of it.
The advanced course builds upon the knowledge gained from the beginner course. It offers in-depth training on writing filters, composite data pipelines and advanced rendering approaches with VTK.
The beginner course offers a firsthand look at the Visualization Toolkit for users/developers coming from different backgrounds. The course is structured to introduce the students to VTK, teach the most fundamental concepts and set up a working environment and explore simple visualization pipelines.
This course will introduce the Visualization Toolkit for the web, VTK.js, for users and developers interested in bringing their 3D visualizations to the web. This course focuses on building and exploring simple interactive visualizations, while introducing core VTK.js concepts and architecture.
This course will introduce trame and go over the basics (reactive state, method calls, custom-widgets, from vue to Python syntax). We'll cover VTK and ParaView in the context of trame. Then we'll explore the various deployment options from a single code base (local, desktop, jupyter, cloud, ondemand). Finally we live 30 minutes for open questions.
*If you don’t see your platform listed on our schedule, please contact us.