Use cases

Below are use cases utitlizing PyImageJ and other packages such as scikit-image. These examples are available in the PyImageJ repository.

• Blob detection (interactive)
• Blob detection (headless)
• CellProfiler
• Classic Segmentation
  • Segmentation workflow with original ImageJ functions
  • Segmentation workflow with ImageJ2
• Puncta Segmentation

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More use cases

Here are additional links to some other examples using PyImageJ in other projects.

• The pyimagej-dextr repository uses Deep Extreme Cut (DEXTR) to generate ImageJ ROIs via PyImageJ.

• PoreSpy, a collection of image analysis tools used to extract information from 3D images of porous materials, uses some ImageJ filters via PyImageJ.

• Some projects at LOCI use PyImageJ to invoke the Image Stitching and SIFT-based image registration plugins of Fiji, together with deep learning for multimodal image registration:

  • Image registration based on SIFT feature matching

  • Generate pseudo modality via CoMIR for multimodal image registration

  • Non-disruptive collagen characterization in clinical histopathology using cross-modality image synthesis

  • WSISR - Single image super-resolution for whole slide image using convolutional neural networks and self-supervised color normalization

To add your usage of PyImageJ to this list, please submit a pull request!