Get Biological Insight by Finding, Measuring and Tracking Image Objects - Kalaimoscope 8.7

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Kalaimoscope finds the position of objects in your bio-images, such as intracellular vesicles, single fluorescent molecules, or cellular structures such as nuclei or mitochondria.

Kalaimoscope searches the image for objects, using information that you provide about the expected size and shape of the biological object at hand. The results of this search for objects are the basis of all following processes.

Finding Image Objects

Finding Objects

Once the objects were found, the software assigns an x-y position and quantifies the intensity profiles of your objects. Knowing the x-y positions and intensities of your biological objects is the first step to answer many important questions, such as:

Motion Tracking allows you to answer many important questions about your biological objects. For example:

Motion Tracking measures the position, size, and intensity of your objects and analyzes the distribution of these properties.

Tracking Image Objects

Tracking Objects

Fully automated trajectory motion tracking links objects in consecutive frames. With these trajecotries the position of the objecs are tracked in time. This powerful feature allows the user to ask:

Statistical Analysis on Image Objects

Statistics

Almost 100 different high level statistical analysis tools are built into the software to make measuring as easy as possible.

Grid Computing

Grid Computing

Although the software runs perfect on PCs or Laptops, it comes with a built-in grid capability. If you want to double, triple, or x-fold processing speed, just buy additional processor modules, e.g for your Intranet. The master software than distributes work load to the slaves and manges the collection of the results. For a user, the only difference is that the speed of application improves almost* e.g. 10 fold if 10 additional processor modules are at work.

Super Computing

The software also runs on super-computers such as linux clusters. At the TU Dresden it runs on a 3000 CPU Linux cluster for the purpose of high-throughput image analysis. Even on 3000 CPUs the software runs as stable as on a laptop computer. For example today in Prof. Zerial's lab Kalaimoscope uses 20.000 CPU hours per day (!) for evaluating state of the art scientific experiments. *not fully due to network communication