Patient specific color texture mapping of CT-based anatomical surface models utilizing cryosection data

In traditional medical imaging modalities, color and texture information can add considerable information for diagnostics. Presently, multimodal images of a patient are unregistered and referenced independent of each other, or registered and fused into a single hybrid volume. Doctors and other medical professionals need to be able to visualize and interrogate, on a per-patient basis, a wide variety of 2D and 3D data representations that can be created from non-invasive imaging modalities, such as MRI and CT. In addition, any colorization that may be applied to the image data is strictly based on tissue density, radiation emission, or magnetic signature, and not on any physiological foundation. In order for "true-to-life" color information to be incorporated with non-invasive imaging techniques, and for it to be of consistent quality across the entire body, a single whole-body cryosection specimen with associated medical image data is needed. The National Library of Medicine's Visible Human Project offers just such a specimen. Using the full-body medical image data along with the cryosection images of the Visible Human subject, a set of color lookup tables for all visually well defined structures and organs can be created. As a result, patient-specific colorization based on real tissue color and characteristics can be incorporated into traditional intensity-based imaging modalities. The primary goal of this work has been to create CT color lookup tables for all visually well-defined structures in the Visible Human male cryosection data set. The subsequent goal has been to develop a method for stripping textures from a volumetric data set for polygonal models and non-uniform rational B-spline (NURBS) models, also generated from the volumetric data.