title: Illustration-inspired depth enhanced volumetric medical visualization.
abstract: Volume illustration can be used to provide insight into source data from CT/MRI scanners in much the same way as medical illustration depicts the important details of anatomical structures. As such, proven techniques used in medical illustration should be transferable to volume illustration, providing scientists with new tools to visualize their data. In recent years, a number of techniques have been developed to enhance the rendering pipeline and create illustrative effects similar to the ones found in medical textbooks and surgery manuals. Such effects usually highlight important features of the subject while subjugating its context and providing depth cues for correct perception. Inspired by traditional visual and line-drawing techniques found in medical illustration, we have developed a collection of fast algorithms for more effective emphasis/de-emphasis of data as well as conveyance of spatial relationships. Our techniques utilize effective outlining techniques and selective depth enhancement to provide perceptual cues of object importance as well as spatial relationships in volumetric datasets. Moreover, we have used illustration principles to effectively combine and adapt basic techniques so that they work together to provide consistent visual information and a uniform style.
authors.affiliation: Adobe Systems Inc., San Jose, CA 95110, USA. svakhine@adobe.com
authors.forename: Nikolai A
authors.initials: NA
authors.lastname: Svakhine
authors.forename: David S
authors.initials: DS
authors.lastname: Ebert
authors.forename: William M
authors.initials: WM
authors.lastname: Andrews
mesh_terms: D000465:Algorithms; D003196:Computer Graphics; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*