Segmentation of the visible human for high-quality volume-based visualization.
This article describes a combination of interactive classification and super-sampling visualization algorithms that greatly enhances the realism of 3-D reconstructions of the Visible Human data sets. Objects are classified on the basis of ellipsoidal regions in RGB space. The ellipsoids are used for super-sampling in the visualization process.
Schiemann
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Institute of Mathematics and Computer Science in Medicine (IMDM), University Hospital Hamburg-Eppendorf, Germany. schiemann@uke.uni-hamburg.de
Tiede
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Höhne
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KH
D000005:Abdomen / Q000033:anatomy & histology*; D000465:Algorithms; D019412:Anatomy, Cross-Sectional; D003198:Computer Simulation; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008953:Models, Anatomic; D009141:Musculoskeletal System / Q000033:anatomy & histology*; D014057:Tomography, X-Ray Computed