Modeling and visualization of empirical data

Many engineering and scientific applications in such diverse disciplines as medicine, biomedical research, geophysics, and robotics depend on the modeling and visualization of empirical data. Although the sources of data for each of these applications differ and considerable domain knowledge may be necessary to interpret the data, there is a great deal of commonality in the required modeling and visualization techniques. In this paper, we explore techniques in registration, segmentation, 3D reconstruction, and rendering, which are common to applications that depend on empirical data. The emphasis is on volumetric data sampled on regular grids, with examples from radiology, neuroscience, embryology, geophysics, and computer vision.

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