InSpectr: Multi-Modal Exploration, Visualization, and Analysis of Spectral Data
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Date
2014
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley and Sons Ltd.
Abstract
This paper addresses the increasing demand in industry for methods to analyze and visualize multimodal data involving a spectral modality. Two data modalities are used: high-resolution X-ray computed tomography (XCT) for structural characterization and low-resolution X-ray fluorescence (XRF) spectral data for elemental decomposition. We present InSpectr, an integrated tool for the interactive exploration and visual analysis of multimodal, multiscalar data. The tool has been designed around a set of tasks identified by domain experts in the fields of XCT and XRF. It supports registered single scalar and spectral datasets optionally coupled with element maps and reference spectra. InSpectr is instantiating various linked views for the integration of spatial and non-spatial information to provide insight into an industrial component's structural and material composition: views with volume renderings of composite and individual 3D element maps visualize global material composition; transfer functions defined directly on the spectral data and overlaid pie-chart glyphs show elemental composition in 2D slice-views; a representative aggregated spectrum and spectra density histograms are introduced to provide a global overview in the spectral view. Spectral magic lenses, spectrum probing and elemental composition probing of points using a pie-chart view and a periodic table view aid the local material composition analysis. Two datasets are investigated to outline the usefulness of the presented techniques: a 3D virtually created phantom with a brass metal alloy and a real-world 2D water phantom with insertions of gold, barium, and gadolinium. Additionally a detailed user evaluation of the results is provided
Description
@article{10.1111:cgf.12365,
journal = {Computer Graphics Forum},
title = {{InSpectr: Multi-Modal Exploration, Visualization, and Analysis of Spectral Data}},
author = {Amirkhanov, Artem and Fröhler, Bernhard and Kastner, Johann and Gröller, Eduard and Heinzl, Christoph},
year = {2014},
publisher = {The Eurographics Association and John Wiley and Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.12365}
}