ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both.

The following are key features of the toolkit design philosophy.

The toolkit provides data representation and algorithms for performing segmentation and registration. The focus is on medical applications; although the toolkit is capable of processing other data types.

The toolkit provides data representations in general form for images (arbitrary dimension) and (unstructured) meshes.

The toolkit does not address visualization or graphical user interface. These are left to other toolkits (such as VTK, VisPack, 3DViewnix, MetaImage, etc.)
The toolkit provides minimal tools for file interface. Again, this is left to other toolkits/libraries to provide.
Multi-threaded (shared memory) parallel processing is supported.
The development of the toolkit is based on principles of extreme programming. That is, design, implementation, and testing is performed in a rapid, iterative process. Testing forms the core of this process. In Insight, testing is performed continuously as files are checked in, and every night across multiple platforms and compilers. The ITK testing dashboard, where testing results are posted, is central to this process.