• Webinar
  • July 23, 2026
  • 12-1pm ET

What’s new in VTK 9.7.0

Explore the latest performance, Python integration, modern C++, and web visualization capabilities in VTK.

As datasets continue to grow in size and complexity, efficiently processing data, integrating with modern Python workflows, and supporting browser-based visualization have become increasingly important. VTK 9.7 introduces performance improvements, expanded Python interoperability, modern C++ enhancements, and new WebGPU and WebXR capabilities that address these challenges.

In this webinar, we’ll explore the latest capabilities in VTK 9.7, including:

  • High-performance processing improvements, including multithreaded Delaunay and Voronoi algorithms and optimized edge extraction filters.
  • NumPy-compatible implicit arrays, zero-copy data access, and streamlined conversion to pandas and xarray.
  • Modern C++ enhancements and build system improvements.
  • New WebGPU and WebXR capabilities for browser-based visualization applications.

We’ll also demonstrate these new capabilities and discuss how they support high-performance processing, Python workflows, modern C++ development, and browser-based visualization.

Whether you’re interested in performance, Python integration, or web visualization, this session will provide a practical overview of the newest capabilities in VTK 9.7.

A live Q&A session will follow the presentation.

Key Takeaways

  • Learn how to accelerate mesh generation and analysis using the latest high-performance filtering improvements.
  • Explore Python API enhancements, including zero-copy NumPy buffers and implicit array mixins.
  • Understand modern C++ and build system improvements that simplify maintenance and improve code quality.
  • Discover new WebGPU and WebXR capabilities for browser-based visualization applications.

Who Should Attend

  • Developers building visualization applications with VTK.
  • Researchers and engineers working with large-scale scientific datasets.
  • Clinical and medical users who use VTK for visualization and analysis.
  • Python users integrating VTK with NumPy, pandas, and xarray.
  • Teams interested in modern C++ development and browser-based visualization technologies.
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