2D +t all in focus movie

March 9, 2020 added by Guillaume Allio

This macro works with 3D+t data from live microscopy. It opens the file, stitches the tiles, corrects the drift in all the dimensions, performs a best focus projection to get a 2D+t all in focus movie automatically saved in a specific folder. Needs BioFormat, Stack Focuser, ImageD, Correct 3D Drifts plugIns.


Dec. 16, 2019 added by christian rouviere

The plugin is write from informations get in FibrilTool by Arezki Boudaoud et al. Nature Protocols. A Results tab gives the average properties of each region scanned in open image -image title -x,y coordinates of region centroid -nematic tensor average orientation (angle in range -90:90 in degrees) -quality of the orientation (score between 0 and 1) Results : An overlay with a colored line on each region is shown on original image, a plot of orientations distribution and a "Results" table with orientation angles and a quality parameter.

Automatic Measure nucleus

Nov. 21, 2019 added by brice ronsin

These is an assistant macro allowing to count and measure automatically nucleus that contain 2 fluorochromes (2 channels) and avoid to count nucleus with one color

new origin

Nov. 13, 2019 added by brice ronsin

this is a tool macro that allow to user to change origin of image. With ImageJ origin is always in the upper left of picture. The tool ask to the user to chose a point in the picture with two line and this point will become the new origin of the image. This tool is very usefull for measure distance in simetric system

colocalisation and line profile in bacteria

Nov. 6, 2019 added by brice ronsin

Open all multichannel images in a folder make for all image a threeshold and skeletonize from the light image. Then all skeletons are analysed to found those wich has only 2 ends and 1 branch and are saved it in a folder. After that macro analyse the colocalization with Jacop between the 2 fluorescence channels of all individual bacteria and save it. Finaly macro make a plot profile along the skeleton of individual bacteria and show the plot profile for the 2 fluorescence channels plugins to install: Jacop and Analyse Skeleton (2D/3D) tested on imageJ


Oct. 16, 2019 added by christian rouviere

Open a multichannel image and Find Maximun along a user's line profil from 2 selected channels of a multi channel fluorescent or RGB image. Gives in the opened file directory, a plot showing maximas and ".cls" files with datas and inter distances in real scale.

Cell shape and substrate influence

July 29, 2019 added by Alain Kamgoué

The influence of the substrate on the organization of the cytoskeleton is observed under three different substrate conditions. A basic parameter like eccentricity is strongly influenced.

Correspondance by maxima

July 22, 2019 added by christian rouviere

The macro ask to select two images from 2 channels (the first one is rename 488nm and the second 561nm). It’s attend that the first image (488nm) contain ARN sticked on the coverglass, the second image contains a countermark directed to the RNA strand. The purpose is to count the number of correspondances between the two images and also give a « quality » index in the localisation by measuring the precision in distance. (gives graph and plot of that distance limited by a parameter : l=5 pixels arround).


July 3, 2019 added by christian rouviere

The macro use the method of Delaunay triangulation with the goal to get the area of each triangle. IJ1 language.

Z Explorer

July 3, 2019 added by christian rouviere

Z explorer This plugin let you choose manually the best interest plane in a 4D sequence. Arrow keys to move in t/z Space to select z in the current t . Note that moving to the next t will automaticaly select the last z. Enter to rendering the sequence (do not forget to select the last z image by pressing the Space bar)


July 3, 2019 added by christian rouviere

Analyzes the angles of curvature of a selection. This selection can be the outline of a cell which will be treated by a spline fiting. The result is an overlay on the image, of the curvatures, color encoded .


July 2, 2019 added by christian rouviere

This tool will help to do measurement on roi's selected by magic wand tool. Interactively user can change the tolerance and so, get objects with high intensity differences (wheel mouse botton)

Sum Length assistant

May 20, 2019 added by christian rouviere

This macro consist on measuring the average intensity under a set of 5 vertical and equidistant lines accross the opened image. User can choose the line length in µm , the line width and the channel to be computed.

Python and Bacteria

March 18, 2019 added by Alain Kamgoué

The images of bacteria in our laboratory are taken in two modes. A phase contrast mode called phase and a fluorescence mode still called signal. These images include biological, biochemical, computer (image analysis) and mechanical information. Biologically, segmentation of the phase image makes it possible to have the physical envelope of the bacterium; as for the signal image, it makes it possible to follow the dynamics of a protein. Combining the segmentation of the phase and the signal, we can precisely follow the spatio-temporal dynamics of the protein. On an image analysis point, the challenges are numerous. How to segment accurately when you have an agglomeration of bacteria? Theoretically, tracking, morphology and machine learning techniques can provide solutions. Mechanistically, characterizing the rheology of a bacterium can be a significant contribution to understanding the underlying biological phenomena. We have developed a Python module consisting of functions to review the approaches mentioned above.


Jan. 2, 2019 added by Alain Kamgoué

ImagePy is a project whose goal is to provide an image analysis application with a graphical interface and other subtleties. Designed 100% in Python, the goal is to allow the simple use of Python image analysis modules. The Python world knows two big image analysis modules. Scikit-Learn and Open-cv. Mastering a minimum Python is a prerequisite for taking control of these two modules. In an effort to break down this barrier of mastery of Python, ImagePy brings us a graphical interface to bypass the mastery of Python. For pythonists, ImagePy will provide easy access to other Python modules. This project under development has seen the participation of young students of Lycée d'Ozenne

Live tools

March 1, 2018 added by christian rouviere

Based on ImageJ software, we offer a group of functions frequently used for image analysis with quick and intuitive access. The goal is to avoid the user getting lost in the various menus of the application to activate these commonly used features. We called them Live Tools. These funstions are installed by addingLive_Tools.jar to your plugins folder, then "Live on your images!"

rDNA Structure

Jan. 18, 2018 added by Alain Kamgoué

How can we extract the 3D rDNA structure in living cell from a 3D map of fluorescent microscopy. To begin, we convert the fluorescent microscopy 3D output into MRC format. This convertion gives us the oppurtinity to use Segger. Segger is an extension of UCSF Chimera using 3d watershed segmentation. This segmentation allows us to obtain different regions with their local maxima. At this stage, we have two possibilities to build the first support points of our reconstruction. For each region, we can choose the local extrema as the first support point; the other option is to choose the centers of mass of each region as the first support points of our reconstruction. Note that for very homogeneous structures, the two possibilities merge. At this stage, the 3d reconstruction of the rDNA can be done naïve way by connecting the points obtained previously. This approximation is also called first level approximation. In order to improve our reconstruction, we have introduced secondary points. For two adjacent regions, the two points that minimize the distance between the two regions are chosen. By adding these points in our reconstruction, we are talking about second-level reconstruction. All connection points obtained, the next question is that of their connection. For this, we will consider the graph whose set of nodes consists of all the points defined above. By traversing the graph in depth, we build all the possible paths. Of all these paths, which one approaches our 3d structure? To answer this question, we calculated the lengths of all paths. The shortest path is considered the one that best approaches the 3d structure.


May 10, 2016 added by Alain Kamgoué

L'enveloppe nucléaire est organe clé dans le processus de vie de la cellule. Sa rigidité optimale permet de préserver le matériel génétique du reste de la cellule. d'autres part au cœur de cette enveloppe une série d'événements se déroulent pour préserver l'intégrité de la cellule. On peut citer la synthèse des protéines. Ainsi, selon le cycle cellulaire, l'enveloppe nucléaire va adapter sa forme afin de permettre le déroulement de ces processus. La reconstruction de la forme exacte de cette enveloppe reste un défi computationel. Chez la levure levure saccharomyces cerevisiae des études ont tantôt fait l'approche de forme elliptique pure ou dégénéré en sphère. D'autres études font une reconstruction plan par plan de l'image fluorescente. En microscopie fluorescente, le choix de l'élément à taguer est capital dans la précision souhaitée. Les pores nucléaires forment un complexe mécano sensible qui permet à l'espace extra nucléaire de communiquer avec le noyau. Nucquant pour nuclear quantification est une série de codes développés sous MATLAB qui permet de reconstruire plus finement l'enveloppe nucléaire. La première étape consiste à clustériser tous les NPCs d'une cellule. Dans la deuxième étape nous choisissons les meilleurs NPCs pour une reconstruction par splines et régulation.

Polymer model DNA organization and genetic inverse problem

Oct. 17, 2015 added by Alain Kamgoué

Three points (loci) on a chromosome with a specific dynamic; dynamic that influences said chromosome. This can be reminiscent of the famous mechanical problem of the three bodies. Just to emphasize the non-triviality of the problem. To solve this problem, we started by formulating a new polymer model. By introducing the notion of survival zone for each locus, we were able to find, from the data of the coordinates of a population of nuclei, the interactions between the different zones of survival. The problem is solved by parallel computing by injecting the experimental data into a billion combinations. Of the one billion combinations tested, the top one hundred are kept for statistical treatment. The icing on the cake, to find these zones of survival makes it possible to infer certain genetic properties of the strains analyzed. This is the case of Mating type switching in Saccharomyces cerevisiae.

Digital image correlation (The Swiss knife of Image Analysis)

Jan. 20, 2009 added by Alain Kamgoué

Coming soon