Audience

Scientific researchers and industrial engineers interested in a tool for visualizing, analyzing, and sharing multidimensional imaging data across disciplines

About Dragonfly 3D World

Dragonfly 3D World by Object Research Systems (ORS) is a comprehensive software platform for multidimensional image visualization, analysis, and collaboration in scientific and industrial fields. It provides powerful tools to visualize, process, and interpret 2D, 3D, and 4D imaging data acquired through modalities such as CT, MRI, electron microscopy, and more. Dragonfly supports real-time volume rendering, surface rendering, and orthogonal slicing, allowing users to explore complex structures interactively. With its AI integration, users can apply deep learning for image segmentation, classification, and object detection. It offers advanced quantitative analysis tools, including region-of-interest analysis, measurements, and statistical evaluations. Its intuitive graphical user interface enables researchers to build reproducible workflows and perform batch processing.

Pricing

Free Trial:
Free Trial available.

Integrations

Ratings/Reviews

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Company Information

Dragonfly
Founded: 2004
Canada
dragonfly.comet.tech/en/product-overview/dragonfly-3d-world

Videos and Screen Captures

Dragonfly 3D World Screenshot 1
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Product Details

Platforms Supported
Windows
Linux
Training
Documentation
Webinars
Support
Online

Dragonfly 3D World Frequently Asked Questions

Q: What kinds of users and organization types does Dragonfly 3D World work with?
Q: What languages does Dragonfly 3D World support in their product?
Q: What kind of support options does Dragonfly 3D World offer?
Q: What other applications or services does Dragonfly 3D World integrate with?
Q: What type of training does Dragonfly 3D World provide?
Q: Does Dragonfly 3D World offer a free trial?

Dragonfly 3D World Product Features

Deep Learning

Visualization
Image Segmentation
Document Classification
ML Algorithm Library
Self-Learning
Neural Network Modeling
Model Training
Convolutional Neural Networks