Segmentation and visualization of volume maps


Volume data is a simple and often-used representation for exchanging and processing data in various scientific domains, such as medicine and molecular biology. The segmentation of volume data is an essential part of data interpretation. Researchers have extensively studied the problem of segmentation focusing on efficient algorithms for segmenting and rendering volumes. Our contribution is two-fold. First, we propose a tri-linear classification method that can implemented on the GPU to reduce artifacts and jaggedness along the material boundaries that appear when rendering segmented volumes. Our representation provides sub-voxel accuracy for representing segmented materials. Second, we demonstrate our interactive painting-based segmentation tool, which can be used to rapidly produce an intuitive segmentation. We compare our tool against known results and show that we can generate similar segmentations using a simple and intuitive control scheme

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This paper was published in DSpace at Rice University.

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