Reshaping medical volumetric data for enhanced visualization

Three dimensional volume datasets are now commonly produced in the medical sciences. These datasets are generated by observational equipment such as CT, MRI, and ultrasound. There is a significant amount of research in techniques to render these datasets quickly and more realistically. However, there is little or no work on intuitive methods to manipulate volume datasets and volume models. For example, one may want to view a colon stretched out or unraveled. While techniques exist to transform polygonal models, similar techniques are not available for volumetric data. In this work, we describe our methodology to "reshape volumes" and remap existing volumetric datasets using volumetric skeletons. We demonstrate our results by unraveling a 3D colon dataset and discuss the many potential uses of this new visualization methodology.