plugin

The MorphoLeaf application allows you to extract the contour of multiple leaf images and identify their biologically-relevant landmarks. These landmarks are then used to quantify morphological parameters of individual leaves and to reconstruct average leaf shapes. MorphoLeaf is developed by the Modeling and Digital Imaging and the Transcription Factors and Architecture teams of the Institut Jean-Pierre Bourgin, INRA Versailles, France, and the Biophyscis and Development group at RDP, Lyon.

ThunderSTORM is an open-source, interactive, and modular plug-in for ImageJ designed for automated processing, analysis, and visualization of data acquired by single molecule localization microscopy methods such as PALM and STORM. Our philosophy in developing ThunderSTORM has been to offer an extensive collection of processing and post-processing methods so that users can easily adapt the process of analysis to their data.

This is an ImageJ plugin to analyze bacterial cells. It provides a user-friendly interface and a powerful suite of detection, analysis and data presentation tools. It works with individual phase or fluorescence images as well as stacks, hyperstacks, and folders of any of these types. Even large image sets are analyzed rapidly generating raw tabular data that can either be saved or copied as is, or have additional statistical analysis performed and graphically represented directly from within MicrobeJ, making it an all-in-one image analysis solution.

This ImageJ plugin aligns the slices of a stack just like the stackreg plugin on which it is built. It allows to save the transformations and to apply them to another stack. It furthermore allows to register two stacks.

In this workflow, you can use MorphoLibJ to generate accurate morphometric measurements

• First the fibers are segmented by mathematical morphology:
  • for example by using MorphoLibJ:
    • Create a marker image by creating a rough mask with extended regional maxima (similar to Find Max), such that you have one max per fiber
    • Use the marker controlled watershed (in MorpholLibJ/ Segmentation/ marker controlled watershed) : indicate the original grayscale image as the input, Marker will be your maxima image, select None for mask
    • it will create a label mask of your fibers
•  In MorphoLibJ /analyze/ select Region Morphometry: this will compute different shape factors which are more robust than the ones implemented by default in ImageJ
• Export the result table created to a csv file
• Then for example in Matlab or R, you can apply a PCA analysis (Principal component analysis) followed by a k-means with the number of class (clusters) (different fibers type) you want to separate.
• You can then add this class as a new feature to your csv file.
• From this you can sort your labelled fibers into these clusters for a visual feedback or further spatial analysis

It is a tool to visualize and annotate volume image data of electron microscopy. Users can annotate objects (e.g. neurons) and skeleton structures. It provides the ability to overlaying the image data with user annotations, representing the spatial structure and the connectivity of labeled objects, and displaying a three dimensional model of it. It can be extended by plugins written in python. A similar, web-based implementation is being developed at webknossos.info. Example datasets are also available.

MorphoLibJ is a library of plugin for ImageJ with functionalities for image processing such as filtering, reconstructing, segmenting, etc... Tools are based on Mathematical morphology with more rigorous mathematical approach than in the standard tools of ImageJ in particular for surface (or perimeter) measurements which are usually based on voxel counting.  

http://imagej.net/MorphoLibJ#Measurements

Among the features:

Morphological operations :  Dilation, Erosion, Opening,  Closing , Top hat (white and black), Morphological gradient (aka Beucher Gradient), Morphological Laplacian, Morphological reconstruction, Maxima/Minima , Extended Maxima/Minima -Watershed (classic or controlled) -Image overlay -Image labelling -Geodesic diameter -Region Adjacency Graph -Granulometry curves, morphological image analysis.

Calculate the Fourier ring correlation (FRC). The FRC can be used as a resolution criterion for super resolution microscopy. The Plugin can display a plot of the FRC curve, along with the LOESS smoothed version of the curve. Finally it displays the threshold method used and the intersection of the FRC with the threshold, providing the FIRE number. It can be used on two open images or on pairs of images in batch mode. 2654 2655

to be completed

This plugin applies the Hough Transform for Circles to an 8-Bit image, shows the resulting Hough Space in a new window and marks the centers of the found circles.