Collection

A collection is a software that encapsulate a set of bioimage components and/or workflows.

Description

Imaris is a software for data visualization, analysis, segmentation and interpretation of 3D and 4D microscopy images. It performs interactive volume rendering that lets users freely navigate even very large datasets (hundreds of GB). It performs both manual and automated detection and tracking of biological “objects” such as cells, nuclei, vesicles, neurons, and many more. ImarisSpots for example is a tool to detect “spherical objects” and track them in time series. Besides the automated detection it gives the user the ability to manually delete and place new spots in 3D space. ImarisCell is a tool to detect nuclei, cell boundaries and vesicles and track these through time. ImarisFilament is a module that lets users trace neurons and detect spines. For any detected object Imaris computes a large set of statistics values such as volume, surface area, maximum intensity of first channel, number of vesicles per cell etc. These values can be exported to Excel and statistics software packages. The measurements can also be analyzed directly within ImarisVantage which is a statistics tool that provides the link back to the 3D objects and the original image data. Strengths: - good visualization - user friendly interface - reads most microscopy file formats - image analysis workflows are very easy to apply - interactive editing of objects to correct errors during automatic detection - large data visualization (hundreds of GB)

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Description
A General purpose image processing toolkit written in C++ based on ITK, VTK, Qt, and Boost. Main features: algorithms for cell segmentation, cell tracing, cell tracking, and vessel tracing. Registration and mosaicing algorithms for large scale datasets. Visualization tools actively linked to inspect and edit results. Strengths: - Open-source, free, multi platform, code is highly parallelized, uses git for version control - Large scale processing, also efficient visualization of such datasets. - Active learning module for classification - Most of the algorithms have been extended to handle 16-bit images, and 3D Images. - Possibility to create complex pipelines thanks to it’s modular architecture - Editing tools are designed to save the editing operation which can later be used to validate the algorithms performance - Advance preprocessing algorithms like curvelets, tensor voting, and wrappers around ITK-algorithms - Multiple viewers included to inspect results such as: Histograms, scatter plots, tables, kymograph, all of them linked together. - Strong emphasis to work on multichannel images (up to 40 channels) - Rich number of cell features included Weakness: - GUI is suboptimal compared to commercial packages. - Tracking module requires an external library CPLEX. - No support for brightfield images - No native interoperability with other software packages - More documentation needed / tutorial needed
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Description
Definiens is a commercial image segmentation and classification tool. The user designs a signal processing workflow by combining built-in filtering, thresholding and object classification modules. Object detection is typically done on hierarchical object levels, e.g cell level for cell objects and organelle level Nucleus and ER obejcts inside a cell object. For each object, a huge set of features (shape-based, intensity based, relations to neighbor objects...) is available and can be used for object classification or merging with neighboring objects. The classical definiens workflow is the so called bottom-up approach: In a first step, the image is segmented in numerous small objects, resulting in a heavy oversegmentation of of the target objects. Objects are then fused step by step on basis of features like “relative border to neighbor object” or “elliptic fit of resulting (fused) object”. Objects can assigned to different classes (like “nucleus” or “cancer cell”), based on their features. Weaknesses: -complex to use -closed (no API) -very expensive -relatively slow (you have to buy one license for each core) -bad 3D-visualization -time lapse analysis is possible but complicated Strengths: -powerful method to classify objects based on multiple features -2D data, especially histological data -good training material to learn software usage -detailed documentation
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Icy

Description

Reproducing an experiment doesn’t stop at the bench when images are concerned. Icy is an open source bioimaging software package that aims to provide a framework for authors to share, and others to reproduce, research once the sample hits the microscope. Icy was released in April 2011 and is being developed at the Quantitative Image Analysis Unit at the Pasteur Institute in France by Jean-Christophe Olivo-Marin and his team. The goal is to provide standardized software architecture, with a visual programming framework and online repository of plugins and protocols, brought together with sophisticated content-management and communication systems for such extended reproducible research. Icy provides intuitive user interfaces for graphical protocol development for image acquisition, analysis and storage that are easy to use for biologists and developers alike. Developers should find that Icy’s ‘EzPlug’ API library, versioning, and auditing tools make creating a custom plugin from most any source easy. Users will find the automatic error reporting, central repository and on-line community hub great for storing and sharing plugins and protocols. Icy is even developing a cloud-computing framework to address the scalability issues of high-content screening. As of this writing there are 207 plug-ins 50 scripts and 14 protocols available for download, including those for microscope control, particle tracking, three dimensional segmentation, and even spot detection using wavelets.

Published in Nature Methods (Nat Methods 9(7):690-6 (2012)). Icy can be downloaded at http://icy.bioimageanalysis.org/ Strength: Open-source. Centralized repository of 205 plugins, 50 scripts and 14 protocols

 

Rate and comment plugins 5D Search and install features directly from Icy Graphical programming with protocols Write scripts in javascript or python Automatic bug reports Native ImageJ integration 100% compatible Native Micro-Manager integration Share your plugins and protocols online Can run headless Intuitive user interface Online management of plugins Connect Icy to Matlab Interactive widgets Build your graphical interface with EzPlug Use the power of your graphic card with OpenCL Loaded with 20 up-to date libs Weaknesses No tutorial for plugins writing..yet See here: http://icy.bioimageanalysis.org/index.php?display=devDoc http://icy.bioimageanalysis.org/index.php?display=detailTag&tagId=29 and here: http://icy.bioimageanalysis.org/index.php?display=startDevWithIcy and also here: http://icy.bioimageanalysis.org/index.php?display=startDevWithIcy Image size limited to 2GigaByte per single 2D channel (means that an image of 40.000x40.000 can be handle by Icy. Still big !) Still you can have a stack of 100000x40Kx40kxUnlimited number of channel if you have RAM. Will be improved

Icy