BactImAs

Short Description

Documentation

** Note: see the complete documentation at our wiki site.

 ** Note: BactImAs requires Java 1.6+

BactImAs is an open-source multi platform java application intended to assist the researcher in tracking various organisms in sequences of images and obtaining and visualizing their quantitative data.

Motivation: A common task in today’s synthetic and systems biology studies is the analysis of various features of organisms using movies obtained through time-lapse microscopy. 
This process consists of identifying organisms on a large number of images and measuring their features whilst keeping track of their lineage which is a very cumbersome and error prone task for the researcher. 
To facilitate the analysis, various mostly automated tools and algorithms were developed in recent years but all of them targeting rather specific organisms and/or laboratory setups, since a general purpose automated solution to this detection problem is extremely hard if not impossible. 

Solution: We've designed BactImAs as a “platform”, that is as a collection of somewhat independent well defined modules working together. Such setup facilitates maintenance, customization and upgrades. This property is particularly useful for the tracking algorithms - in BactImAs it is possible to include multiple tracking algorithms (“best-of-breed approach”) and thus use the best fitted algoritm for the problem at hand. 
It is even possible to mix-and-match algorithms in a way to segment one part of the movie with algorithm A and the other part with algorithm B.

BactImAs uses a semi-automated approach: it relies on the user to define the initial cells and all cell divisions. Other than that, the application tracks cells using a our newly developed algorithm. At any point, the user can intervene and correct any unsatisfactory cell detections.

BactImAs provides the following features:

• Easy to use GUI interface
• Frame anlignment algorithm
• Novel mycobacteria segmentation algorithm
• Novel configurable lineage tree visualization
• Automated acquisition of quantitative date
• Relational database storage, SQL interface to data
• Data export (CSV)