Analysis

Free-D is a three-dimensional (3D) reconstruction and modeling software. It allows to generate, process and analyze 3D point and surface models from stacks of 2D images. Free-D is an integrated software, offering in a single graphical user interface all the functionalities required for 3D modeling. It runs on Linux, Windows, and MacOS. Free-D is developed by the Modeling and Digital Imaging team of the Institut Jean-Pierre Bourgin, INRA Versailles, France.

Free-D (http://free-d.versailles.inra.fr/) is a 3D reconstruction and modeling software. It is multiplatform, free (but not open source) tool for academic research and teaching.

Here is how to proceed, using Free-D:

1. Segmentation:

* load (a collection of) individual 3d stacks

* (optional for serial sections) perform a 2D registration to align image slices

* segment/reconstruct 3D contours using snakes

* segment 3D spots

2. Construct average cell:

* normalize the contours to compute a average cell, by registering/warping 3D contours/surfaces

3. Quantification:

* project each individual cell to the average one

* build density maps to analyze (cartography)

A few notes for current software version (till 10/2016):

* input file format: tiff (not able to import bioformats)

* currently results are saved in customized format, but there is an exportor to convert this format into fiji readable one

* import already generated contours is on the software's TODO list

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/Fiji plugin provides an analysis of the granulometry inside an image by mathematical morphology. It has sevral option for the structuring element to be used, and the size domain to be tested. The output will be both a curve of the remaining content of the image against the growing size of the structuring element, and the corresponding results table that could be then exported. It can deal with grayscale images directly, no need to segment the image first. This plugin can then be used to compare different texture based on some statistical analysis of the produced curve (for exemple comparison of the geometrical means to discriminate 2 textures). It is macro recordable as well. Programming Language: java Processes: successive erosion, dilation, closing or opening -> ANALYSIS User skills: Life Scientist, developers, analysts

Localization-based super-resolution techniques open the door to unprecedented analysis of molecular organization. This task often involves complex image processing adapted to the specific topology and quality of the image to be analyzed. SR-Tesseler is an open-source segmentation software using Voronoï tessellation constructed from the coordinates of localized molecules. It allows precise, robust and automatic quantification of protein organization at different scales, from the cellular level down to clusters of a few fluorescent markers. SR-Tesseler is insensitive to cell shape, molecular organization, background and noise, allowing comparing efficiently different biological conditions in a non-biased manner, and perform quantifications on various proteins and cell types. SR-Tesseler software comes with a very simple and intuitive graphical user interface, providing direct visual feedback of the results and is freely available under GPLv3 license.