Cell segmentation

Description

Orbit Image Analysis is a free open source software with the focus to quantify big images like whole slide scans.

It can connect to image servers, e.g. Omero.
Analysis can be done on your local computer or via scaleout functionality in a distrubuted computing environment like a Spark cluster.

Sophisticated image analysis algorithms incl. tissue quantification using machine learning, object segmentation and classification are build in. In addition a versatile API allows you to enhance Orbit and to run your own scripts.

Orbit
Description

automated open-source image acquisition and on-the-fly analysis pipeline (initially developped for analysis of mitotic defects in fission yeast)

maars workflow from publication

 

maars
Description

The Adipocytes Tools help to analyze fat cells in images from histological section. This is a rather general cell segmentation approach. It can be adapted to different situations via the parameters. This means that you have to find the right parameters for your application.

Sample Image: [0178_x5_3.tif](http://dev.mri.cnrs.fr/attachments/190/0178_x5_3.tif)

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Description

Analysis of adipocyte number and size. The original code and example images supposed to be discovered at http://webspace.buckingham.ac.uk/klanglands/ but currently the webpage is missing the code and sample images.

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Description

Vaa3D is a handy, fast, and versatile 3D/4D/5D Image Visualization and Analysis System for Bioimages and Surface Objects. It also provides many unique functions that you may not find in other software. It is Open Source, and supports a very simple and powerful plugin interface and thus can be extended and enhanced easily.

Vaa3D is cross-platform (Mac, Linux, and Windows). This software suite is powerful for visualizing large- or massive-scale (giga-voxels and even tera-voxels) 3D image stacks and various surface data. Vaa3D is also a container of powerful modules for 3D image analysis (cell segmentation, neuron tracing, brain registration, annotation, quantitative measurement and statistics, etc) and data management. This makes Vaa3D suitable for various bioimage informatics applications, and a nice platform to develop new 3D image analysis algorithms for high-throughput processing. In short, Vaa3D streamlines the workflow of visualization-assisted analysis.

Vaa3D can render 5D (spatial-temporal) data directly in 3D volume-rendering mode; it supports convenient and interactive local and global 3D views at different scales... it comes with a number of plugins and toolboxes. Importantly, you can now write your own plugins to take advantage of the Vaa3D platform, possibly within minutes!

 

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