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  • Mark Sutton (a1), Imran Rahman (a2) and Russell Garwood (a3)


Virtual paleontology is the study of fossils through three-dimensional digital visualizations; it represents a powerful and well-established set of tools for the analysis and dissemination of fossil data. Techniques are divisible into tomographic (i.e., slice-based) and surface-based types. Tomography has a long predigital history, but the recent explosion of virtual paleontology has resulted primarily from developments in X-ray computed tomography (CT), and of surface-based technologies (e.g., laser scanning). Destructive tomographic methods include forms of physical-optical tomography (e.g., serial grinding); these are powerful but problematic techniques. Focused Ion Beam (FIB) tomography is a modern alternative for microfossils; it is also destructive but is capable of extremely high resolutions. Nondestructive tomographic methods include the many forms of CT, which are the most widely used data-capture techniques at present, but are not universally applicable. Where CT is inappropriate, other nondestructive technologies (e.g., neutron tomography, magnetic resonance imaging, optical tomography) can prove suitable. Surface-based methods provide portable and convenient data capture for surface topography and texture, and might be appropriate when internal morphology is not of interest; technologies include laser scanning, photogrammetry, and mechanical digitization. Reconstruction methods that produce visualizations from raw data are many and various; selection of an appropriate workflow will depend on many factors, but is an important consideration that should be addressed prior to any study. The vast majority of three-dimensional fossils can now be studied using some form of virtual paleontology, and barriers to broader adaptation are being eroded. Technical issues regarding data sharing remain problematic. Technological developments continue; those promising tomographic recovery of compositional data are of particular relevance to paleontology.



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  • Mark Sutton (a1), Imran Rahman (a2) and Russell Garwood (a3)


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