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Erschienen in:
2012 | OriginalPaper | Buchkapitel
An Evaluation of Peak Finding for DVR Classification of Biological Data
verfasst von : Aaron Knoll, Rolf Westerteiger, Hans Hagen
Erschienen in: Visualization in Medicine and Life Sciences II
Verlag: Springer Berlin Heidelberg
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In medicine and the life sciences, volume data are frequently entropic, containing numerous features at different scales as well as significant noise from the scan source. Conventional transfer function approaches for direct volume rendering have difficulty handling such data, resulting in poor classification or undersampled rendering. Peak finding addresses issues in classifying noisy data by explicitly solving for isosurfaces at desired peaks in a transfer function. As a result, one can achieve better classification and visualization with fewer samples and correspondingly higher performance. This paper applies peak finding to several medical and biological data sets, particularly examining its potential in directly rendering unfiltered and unsegmented data.