Image segmentation

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

The macro will segment nuclei and separate clustered nuclei using a binary watershed. As a result an index-mask image is written for each input image.

TEM ExosomeAnalyzer is a program for automatic and semi-automatic detection of extracellular vesicles (EVs), such as exosomes, or similar objects in 2D images from transmission electron microscopy (TEM). The program detects the EVs, finds their boundaries, and reports information about their size and shape.

The software has been developed in terms of project MUNI/M/1050/2013 and supported by Grant Agency of Masaryk University.

The EVs are detected based on the shape and edge contrast criteria. The exact shapes of the EVs are then segmented using a watershed-based approach.

With proper parameter settings, even images with EVs both lighter and darked than the background, or containing artifacts or precipitated stain can be processed. If the fully-automatic processing fails to produce the correct results, the program can be used semi-automatically, letting the user adjust the detection seeds during the intermediate steps, or even draw the whole segmentation manually.