Contents

The research goal of this paper was to provide unbiased counts of labeled astrocytes and to estimate the area they cover, further to develop tools for defining the orientation of coupling within astrocyte networks under different stimuli.

André Dias, Marco Werner, Kevin R. Ward, Jean-Baptiste Fleuryd and Vladimir A. Baulin

It has become increasingly clear that astrocytes modulate neuronal function not only at the synaptic and single-cell levels, but also at the network level. Astrocytes are strongly connected to each other through gap junctions and coupling through these junctions is dynamic and highly regulated. An emerging concept is that astrocytic functions are specialized and adapted to the functions of the neuronal circuit with which they are associated.

Diagnosing illnesses, developing and comparing treatment methods, and conducting research on the organization of the peripheral nervous system often require the analysis of peripheral nerve images to quantify the number, myelination, and size of axons in a nerve. Current methods that require manually labeling each axon can be extremely time-consuming as a single nerve can contain thousands of axons.

We have developed WormScan, an automated image acquisition system that allows quantitative analysis of each of these four phenotypes on standard NGM plates seeded with E. coli. This system is very easy to implement and has the capacity to be used in high-throughput analysis.

online image data management systemwhich supports authenticated image upload, cloud-based storage, project-based management and viewing of standard and whole slide images. One can use different annotation tools to highlight important objects or areas within images. It is the first basic version and new features such as sharing for easy collaboration with your colleagues or first automated analysis applications based on artificial intelligence will be added soon.

Ikosa Portal: multi user image data management

Protein array is used to analyze protein expressions by screening simultaneously several protein-molecule interactions such as protein-protein and protein-DNA interactions. In most cases, the detection of interactions leads to an image containing numerous lines of spots that will be analyzed by comparing tables of intensity values.

Datasets originate from internal test runs at ACQUIFER on the Imaging Machine (see also application note on "The ACQUIFER PlateViewer: A tool for visualizing high content screening data and supervised feedback microscopy")

102 hpf medaka embryos in 96 well plate (4 embryo/well) - brightfield - 2X magnification - ACQUIFER Imaging Machine

Gierten, Jakob, et al. "Automated high-throughput heart rate measurement in medaka and zebrafish embryos under physiological conditions." bioRxiv (2019): 548594.

Used as benchmark dataset for Multi-Template-Matching by Thomas and Gehrig 

See implementation in Fiji https://github.com/LauLauThom/MultipleTemplateMatching

Multi-template matching can be used to localize multiple objects using one or a set of template images.

Contrary to previous implementations that allow to use only one template, here a set of templates can be used or the initial template(s) can be transformed by rotation/flipping.

Multiple objects detection without redundant detections is possible thanks to a Non-Maxima Supression relying on the degree of overlap between detections.

FPBioimage is a volumetric visualization tool which runs in all modern web browsers. Try the tool yourself at our example site here.

The PYthon Microscopy Environment is an open-source package providing image acquisition and data analysis functionality for a number of microscopy applications, but with a particular emphasis on single molecule localisation microscopy (PALM/STORM/PAINT etc ...). The package is multi platform, running on Windows, Linux, and OSX.

It comes with 3 main modules:

• PYMEAcquire - Instrument control and simulation
• dh5view - Image Data Analysis and Viewing
• VisGUI - Visualising Localization Data Sets

MATLAB, for advanced analysts. Slides, Scripts, Reproduction of results & deconstruction. Uniquely designed analtical approaches towards understanding cell cluster movements, based on stress / cell migration analysis.

Fiji plugin for detecting, tracking and quantifying filopodia

ImageJ & R, for advanced analysts. Slides, Scripts, Reproduction of results & deconstruction. Segmentation of filopodia (thin filamentous structure) and analysis of their shape and movements to characterize phenotypes.

MATLAB, CellProfiler, Advanced Cell Classifier, for advanced analysts. Slides, Scripts, Reproduction of results & deconstruction. We aim to implement an image-based analysis of a biological system by profiling the phenotipic response of a cancer cell line following perturbation with a small-molecule compound library

ImageJ, for those with GUI knowledge but without scripting knowledge

ImageJ, for those with GUI knowledge but without scripting knowledge

ImageJ, GUI training for beginners, Count and Measure 2D nuclei,Count number of foci on 3D image , compare 2D, 2.5D, 3D results (simple workflows)