2D

This macro is a plugin macro to the "Intelligent Imaging" workflow. It detects the Cytoo patterns (specific fluorsecence channel) and computes the occupancy (number of cells) of each pattern by analyzing the images of the DAPI channel. The analysis function can be easily extended to, for instance, only select the cells that are well spread on the patterns (by analyzing a third channel with a properly chosen marker of the cytoplasm).

The Measure Rosette Area Tool allows to measure the area of the rosettes of arabidopsis plants.

See: http://dev.mri.cnrs.fr/projects/imagej-macros/wiki/Measure_Rosette_Area…

Example data: http://biii.eu/node/1146, http://biii.eu/node/1145

An example macro introduced in the documentation page of the ImageJ plugin Trainable Weka Segmentation (in Fiji, it's bundled). A segmentation protocol based on machine learning. Full macro is available in the "Download" Link. 

This plugin can be trained to learn from the user input and perform later the same task in unknown (test) data. Weka: it makes use of all the powerful tools and classifiers from the latest version of Weka. Segmentation: it provides a labeled result based on the training of a chosen classifier. Trainable Weka Segmentation Complete macro example is at the end of the page.

[as of 20180524, the website is temporary not functioning do to web defacement - please check again later] This tutorial will exemplify basic rapidSTORM usage by showing how to convert an Andor SIF acquisition to a super-resoluted image with rapidSTORM.

A deconvolution component applicable to confocal and STED microscopy. The MATLAB function fo this package implements the SGP method for n-dimensional object deblurring with the option of boundary effects removal. Although this is a preliminary version, results seem to be good from their paper (Zanella et al 2013).