ORS Dragonfly 2025 (also referred to as Dragonfly 3D World 2025) is the latest iteration of Object Research Systems (ORS)’ flagship scientific image processing and analysis software. Designed for researchers, engineers, and scientists, it provides advanced tools for 2D/3D/4D imaging workflows, including segmentation, visualization, and quantitative analysis of data from sources like X-ray CT, SEM, FIB-SEM, confocal microscopy, and hyperspectral imaging. This release emphasizes AI-powered deep learning enhancements, community collaboration, and streamlined workflows to accelerate discoveries in fields such as materials science, biology, and engineering.

Key Features

  • Deep Learning Integration: Commercially supported engine for training and executing custom neural networks, enabling rapid segmentation and feature extraction (e.g., porosity analysis, fiber orientation, or object labeling).
  • Image Processing Tools: Supports import of stacks in formats like TIFF and DICOM; includes noise reduction, contrast enhancement, cropping, stitching, and registration.
  • Segmentation and Analysis: Advanced algorithms for phase separation, object indexing (e.g., watershed transformation), and quantitative metrics like volume fraction, size, shape, and orientation.
  • Visualization: Interactive 3D rendering, arbitrary cross-sections, and export options for presentations or QA documentation.
  • Automation and Extensibility: Macros, Python scripting, and plug-ins for custom tools; handles large datasets efficiently.
  • Community Features: Integration with Dragonfly Social for sharing trained models, datasets, tutorials, and insights.

What’s New in 2025

Released in early 2025, this version introduces productivity-boosting updates focused on collaboration and efficiency:

  • Model Sharing on Dragonfly Social: Upload and download community-trained segmentation models directly in the software, fostering shared workflows.
  • Enhanced Documentation Tools: Improved export for high-quality visuals, ideal for reports or publications.
  • Workflow Optimizations: Faster processing for complex datasets, with better support for AI-driven tasks and real-time previews.