Data handling

This macro builds a stitched image from a muti-position 3D + time hyperstack. The XY positions of the montage should be coded as channels in the input hyperstack. Channel ordering can be configured in the dialog box to adapt to Column/Row and Meander/Comb configurations: The images should appear in this order when browsing the hyperstack with the channel slider. Fine stitching is supported (requires sufficient overlap between the views). The XY displacements of each field of view for stitching are computed for a single reference (Z,T) slice (user configurable) and applied to all slices (Z and T).

An ActionBar is a simple annotated text document that has snippets of Imagej macros or Beanshell arranged into buttons. This tool is very useful when creating custom work flows integrating multiple components. Each component can be linked to a button for a more streamlined and accessible workflow.

**Collaborative Annotation Toolkit for Massive Amounts of Image Data** CATMAID is a Collaborative Annotation Toolkit for Massive Amounts of Image Data. It is designed to navigate, share and collaboratively annotate massive image data sets of biological specimens. The interface is inspired by GoogleMaps, with which it shares basic navigation concepts, enhanced to allow the exploration of 3D biological image data acquired by optical or physical sectioning microscopy techniques. The interface enables seamless sharing of regions of interest through bookmarks and synchronized navigation through multiple registered data sets. With massive biological image data sets it is unrealistic to create a sustainable centralized repository. A unique feature of CATMAID is its partially decentralized architecture where the presented image data can reside on any Internet accessible server and yet can be easily cross-referenced in the central database. In this way no image data are duplicated and the data producers retain full control over their images. CATMAID is intended to serve as data sharing platform for biologists using high-resolution imaging techniques to probe large specimens. Any high-throughput, high-content imaging project such as gene expression pattern screens would benefit from the interface for data sharing and annotation.

OMERO is a free, open source image management software. It is client-server based system which supports 5D images, including big images and high-content screening data. Data are stored on a server using relational database. They are accessed using 3 main clients, a desktop client, a web client and a command line tool. There are bindings from OMERO to other image analysis packages, like FLIMfit, OMERO.searcher. The data in OMERO are organized in groups. A user can be a member of one or more groups. This groups can be collaborative or private, there are 4 levels of permissions to access/edit/annotate/delete the data of other users.

The package is supported not only by community forums, but also by a dedicated team which helps users to solve their problems and deals with the bugs submitted via error submission system.

###Strengths

Open source, scalable software, Supports diverse sets of imaging applications and domains (EM,LM, HCS, DigPath) Cross-platform, Java-based application, API support for Java, Python, C++, Django, On-line Forums, Automatic QA and upload of software errors Multi-dimensional images, Web access, Free Demo-server accounts

Limitations

Enterprise-scale software, so complex install, requires expertise, Actively developing API, Python scripts and functions still developing