The aim of volume visualization in medicine is to create precise and realistic views of objects from medical volume data. The resulting images, even though they are of course two-dimensional (2D), are often called 3D images or 3D reconstructions to distinguish them from 2D cross sections or conventional radiographs. The first attempts date back to the late 1970s, with the first clinical applications reported on the visualization of bone from CT in craniofacial surgery and orthopedics. Methods and applications have since been extended to other subjects and imaging modalities. The same principles are also applied to sampled and simulated data from other domains, such as fluid dynamics, geology, and meteorology. Preprocessing of large data sets requires several minutes of computing, reduces the flexibility to interactively adjust visualization parameters, and aliases the original data. An important goal in image processing of medical images, in addition to the analysis of the images, is the reconstruction and visualization of the scanned objects.