Computer-assisted surgery (CAS) represents a surgical concept and set of methods, that use computer technology for surgical planning, and for guiding or performing surgical interventions. CAS is also known as computer-aided surgery, computer-assisted intervention, image-guided surgery, digital surgery and surgical navigation, but these are terms that are more or less synonymous with CAS. CAS has been a leading factor in the development of robotic surgery. General principles Creating a virtual image of the patient The most important component for CAS is the development of an accurate model of the patient. This can be conducted through a number of medical imaging technologies including CT, MRI, x-rays, ultrasound plus many more. For the generation of this model, the anatomical region to be operated has to be scanned and uploaded into the computer system. It is possible to employ a number of scanning methods, with the datasets combined through data fusion techniques. The final objective is the creation of a 3D dataset that reproduces the exact geometrical situation of the normal and pathological tissues and structures of that region. Of the available scanning methods, the CT is preferred, because MRI data sets are known to have volumetric deformations that may lead to inaccuracies. An example data set can include the collection of data compiled with 180 CT slices, that are 1 mm apart, each having 512 by 512 pixels. The contrasts of the 3D dataset (with its tens of millions of pixels) provide the detail of soft vs hard tissue structures, and thus allow a computer to differentiate, and visually separate for a human, the different tissues and structures. The image data taken from a patient will often include intentional landmark features, in order to be able to later realign the virtual dataset against the actual patient during surgery. See patient registration. Image analysis and processing Image analysis involves the manipulation of the patients 3D model to extract relevant information from the data. Using the differing contrast levels of the different tissues within the imagery, as examples, a model can be changed to show just hard structures such as bone, or view the flow of arteries and veins through the brain. Diagnostic, preoperative planning, surgical simulation Using specialized software the gathered dataset can be rendered as a virtual 3D model of the patient, this model can be easily manipulated by a surgeon to provide views from any angle and at any depth within