title: Context-preserving rendering of medical segmentation data.
abstract: We present a context-preserving visualisation method for segmented volumetric medical images. A segmented volumetric image contains a number of anatomical objects which are important features to be visualised. Our context-preserving rendering utilises the curvature at the surfaces of the segmentation objects to modulate the opacity contribution during rendering. This results in the areas of high curvature, typically the most important features, being opaque and visible while everything else being transparent.
authors.affiliation: School of Computer Science, University of Wales Bangor, Dean Street, Bangor, UK, LL57 1UT.
authors.forename: David
authors.initials: D
authors.lastname: Hughes
authors.forename: Ik Soo
authors.initials: IS
authors.lastname: Lim
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008953:Models, Anatomic; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique