Collection

ImJoy is a plugin powered hybrid computing platform for deploying deep learning applications such as advanced image analysis tools.

ImJoy runs on mobile and desktop environment cross different operating systems, plugins can run in the browser, localhost, remote and cloud servers.

With ImJoy, delivering Deep Learning tools to the end users is simple and easy thanks to its flexible plugin system and sharable plugin URL. Developer can easily add rich and interactive web interfaces to existing Python code.

Set of Tools for super resolution microscopy

This suite provides plugins to enhance 3D capabilities of ImageJ.

• 3D Filters (mean, median, max, min, tophat, max local, …) and edge and symmetry filter
• 3D Segmentation (iterative thresholding, spots segmentation, watershed, …)
  • 3D hysteresis thresholding with two thresholds (see 2D hysteresis for explanation).
  • 3D simple segmentation with thresholding to label 3D objects (similar to 3D objects counter).
  • 3D iterative thresholding (find optimal threshold for each object).
  • 3D spot segmentation with various local threshold estimations.
  • 3D Maxima Finder (with noise parameter)
  • 3D seeds-based watershed with automatic local maxima detection for seeds.
• 3D Mathematical Morphology tools (fill holes, binary closing, distance map, …)
• 3D RoiManager (3D display and analysis of 3D objects)
• 3D Analysis (Geometrical measurements, Mesh measurements, Convex hull, …)
  • 3D Geometrical measurements (volume, surface, …) for each labelled object.
  • 3D Centroid, to compute centroids of labelled objects.
  • 3D Intensity measurements (mean, integrated density, …) in a opened image for each labelled object.
  • 3D Shape measurements (compactness, elongation, …) for each labelled object.
  • 3D Mesh Measurements after triangulation (see 3D Viewer for surface mesh computation).
  • 3D fitting by an ellipsoid and main direction computation (details here).
  • 3D convex hull (see http://rsbweb.nih.gov/ij/plugins/3d-convex-hull/index.html).
  • 3D Radial Distance Area Ratio (RDAR)
  • 3D Density, to compute density of dots, based on closest distance analysis (details here).
• 3D MereoTopology (Relationship between objects)
• 3D Tools (Drawing ellipsoids and lines, cropping, …)
  • Drawing 3D line
  • Drawing 3D ellipsoids in any direction
  • Drawing in stacks as volumes
  • Drawing in 3D viewer as surfaces

CRImage a package to classify cells and calculate tumour cellularity

CRImage provides functionality to process and analyze images, in particular to classify cells in biological images. Furthermore, in the context of tumor images, it provides functionality to calculate tumour cellularity.

CLIJ2 is a GPU-accelerated image processing library for ImageJ/Fiji, Icy, Matlab and Java. It comes with hundreds of operations for filtering, binarizing, labeling, measuring in images, projections, transformations and mathematical operations for images. While most of these are classical image processing operations, CLIJ2 also allows performing operations on matrices potentially representing neighborhood relationships between cells and pixels.

CLIJ2 was developed to process images from fluorescence microscopy data of developing cells, tissues, organoids and organisms.