Anthony Sherbondy
Stanford University |
Mike Houston
Stanford University |
Sandy Napel
Stanford University |
To appear in IEEE Visualization 2003
Abstract
Segmentation of structures from measured volume data, such as anatomy in medical imaging, is a challenging data-dependent task. In this paper, we present a segmentation method that leverages the parallel processing capabilities of modern programmable graphics hardware in order to run significantly faster than previous methods. In addition, collocating the algorithm computation with the visualization on the graphics hardware circumvents the need to transfer data across the system bus, allowing for faster visualization and interaction. This algorithm is unique in that it utilizes sophisticated graphics hardware functionality (i.e., floating point precision, render to texture, computational masking, and fragment programs) to enable fast segmentation and interactive visualization.
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These four volume renderings utilize a fully opaque transfer function, but are segmented using the method discussed in this paper. The segmented volumes show: (a) abdominal aortic branch vessels, (b) an aortic aneurysm, (c) an aorta, and (d) peripheral blood vessels in the lung. The yellow arrows indicate the location of the user's initial seeds that were evolved to form the presented segmentations.
Paper