3-D Volume Modeling, Feature Identification and Rendering of a Human Skull

J. Meyer (USA)


Volume modeling, feature identification, texture mapping, Haar wavelets, rendering, illumination


Advanced medical imaging technologies have enabled biologists and biomedical researchers to create accurate models and identify features in complex, large-scale data sets. These models, which are typically based on a CT or MRI scan, occupy large amounts of storage space and can no longer be archived on local hard drives. They are also difficult to transmit over currently existing networks. Large scale biomedical image data, which is typically stored in a large data repository, must be preprocessed in order to enable real-time data transmission and interactive rendering. To make the model accessible to researchers at remote locations over the Internet within a reasonable amount of time, we are describing a web-based volume modeling and feature identification system that incorporates a multi resolution rendering technique for transforming large-scale volume models into hierarchical representations. We are using Haar wavelets to decompose the data set into a multi level-of-detail representation that can be transmitted from the server side to the client side in a progressive fashion. The image is rendered using a texture-based visualization technique in Java3D. A new efficient illumination technique has been implemented to improve the image quality of the rendered volumes and to help with the identification of features by using pre-calculated normal vectors for all the surface voxels. The advantage of this method is that the illumination can be calculated on the client side. It does neither affect the data transmission time nor the interactive behavior of the texture-based rendering algorithm.

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