Deciphering the details of life from organelle to organism proceeds directly from scientific imaging with laboratory X-ray CT and electron microscopy. Discover how Dragonfly can simplify analyses and extend findings from imaging studies at all relevant length scales of the Life Sciences.

Image source: Dr. Julius Jeiter Postdoc | Plant morphology, evolution and systematics Nees-Institute for Biodiversity of Plants, University of Bonn

Cellular and subcellular imaging

Precise labeling of cellular ultrastructure from EM images has been an unparalleled driver of cellular biology. Dragonfly automates that otherwise painstaking labeling process and couples it with rich analytics of organelle size and spatial distributions.

  • Stack alignment for registration of FIBSEM, SBFSEM and ATUM imaging studies
  • Denoising of short-exposure micrographs translates into quicker and longer imaging experiments
  • Automated AI segmentation reveals 3D cellular organization without the painstaking human effort
CryoEM and CryoTomography
  • Regression deep learning models for state-of-the-art denoising
  • Segmentation for advanced labeling of notoriously noisy image data
  • Online mini-course in YouTube tutorial series
 LM and Correlative
  • Stitch together images for larger fields of view
  • Compute measurements for statistical distributions of sizes and lengths
  • Integrate the scales and findings from light microscopy with electron microscopy.
Before After

Retina cell segmented with deep learning. Data courtesy of Christopher Bleck, NIH

Plant anatomy

The recent growth of X-ray CT in plant anatomy research is driving new findings in plant ultrastructure. Dragonfly's analysis tools for measuring and visualizing grain and other feature size distributions give quantitative descriptions to compliment the abundant qualitative observations revealed in imaging studies.

Animal anatomy

Non-invasive imaging of laboratory and field-collected animals reveals the structural organization of animal life. Dragonfly's tools for visualization and inspection yield insightful answers and impactful visuals.

Dr. Julius Jeiter Postdoc | Plant morphology, evolution and systematics Nees-Institute for Biodiversity of Plants, University of Bonn
Result of applying the ready-to-use ‘UniversalJawSeg’ deep model with classes for enamel, dentin, and bone. Original microCT dataset acquired by Dr. Kornelius Kupczik, Universidad de Chile
Scan of a human vertebra, CT data courtesy of TESCAN, sample courtesy of Rush University

Bone organization

With Dragonfly, users measure key cortical and trabecular bone attributes, critical to characterizing experimental and naturally observed bone samples. Those working on therapeutic implant studies can visually and numerically assess implant bone regrowth interdigitation.


The use of non-destructive X-ray CT in the study of fossils is an especially powerful tool where each specimen is precious. Dragonfly's AI-based processing routines are uniquely capable in handling the nuanced textures - such as fossilized biomatter with low contrast against surrounding rock matrix - found in even poorly preserved natural specimens.

Pharma research and development

Refined manufacturing processes should produce tight tolerances, especially in the health-critical field of pharmaceuticals. Dragonfly's advanced tools let R&D workers extract cracks and other defects at the same time they make precise measurements on the variance of particle shape and size.

Segmented Pawpawsaurus jawbone. Data courtesy of DigiMorph.
Scan of a vitamin C capsule

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