Combining Wavelet Transform and Graph Theory for Feature Extraction and Visualization
In the process of visualizing 3D MRI or CT data using techniques such as isosurfacing or direct volume rendering, one is confronted with two problems. The first one is that there is no distinction between important and unimportant data. The second one is the difficulty to find a meaningful mapping of the measured scalar values to the graphical attributes used for the visualization. These problems are addressed by the special segmentation procedure presented in this paper. The basic idea is to apply graph algorithms to find important structures and to assign multidimensional information to these structures with the help of wavelets. This additional information can be used to generate graphical attributes for rendering. Several aspects emerge from the interaction of both theoretical concepts.
KeywordsFeature Vector Wavelet Transformation Wavelet Coefficient Minimal Span Tree Continuous Wavelet Transformation
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