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This paper introduces importance-driven volume rendering as a novel technique for automatic focus and context display of volumetric data. Our technique is a generalization of cut-away views, which ¿ depending on the viewpoint ¿ remove or suppress less important parts of a scene to reveal more important underlying information. We automatize and apply this(More)
This paper introduces a concept for automatic focusing on features within a volumetric data set. The user selects a focus, i.e., object of interest, from a set of pre-defined features. Our system automatically determines the most expressive view on this feature. A characteristic viewpoint is estimated by a novel information-theoretic framework which is(More)
In this paper, we present a novel technique which simulates directional light scattering for more realistic interactive visualization of volume data. Our method extends the recent directional occlusion shading model by enabling light source positioning with practically no performance penalty. Light transport is approximated using a tilted cone-shaped(More)
In this paper we present a framework to define transfer functions from a target distribution provided by the user. A target distribution can reflect the data importance, or highly relevant data value interval, or spatial segmentation. Our approach is based on a communication channel between a set of viewpoints and a set of bins of a volume data set, and it(More)
This tutorial presents recent and important research and developments from academia in illustrative, non-photorealistic rendering (NPR) focusing on its use for medical/science subjects. Lectures are organized within a comprehensive illustration framework, focusing on three main components: • Traditional and computerized illustration techniques and(More)
This paper presents importance-driven feature enhancement as a technique for the automatic generation of cut-away and ghosted views out of volumetric data. The presented focus+context approach removes or suppresses less important parts of a scene to reveal more important underlying information. However, less important parts are fully visible in those(More)
Dense clinical data like 3D Computed Tomography (CT) scans can be visualized together with real-time imaging for a number of medical intervention applications. However, it is difficult to provide a fused visualization that allows sufficient spatial perception of the anatomy of interest, as derived from the rich pre-operative scan, while not occluding the(More)
Current graphics hardware offers only very limited support for con-volution operations, which is primarily intended for image processing. The input and output sample grids have to coincide, making it impossible to use these features for more general filtering tasks such as image or texture resampling. Furthermore, most hardware employs linear interpolation(More)