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Soft Tissue Surface Scanning - A comparison of commercial 3D object scanners for surgical simulation content creation and medical education applications

Avis, Nicholas John, Kleinermann, Frederic and McClure, John 2004. Soft Tissue Surface Scanning - A comparison of commercial 3D object scanners for surgical simulation content creation and medical education applications. Lecture Notes in Computer Science 3078 , pp. 211-220. 10.1007/978-3-540-25968-8_24

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Abstract

he construction of surgical simulators requires access to visually and physically realistic 3D virtual organs. Whilst much work is currently underway to address the physically based modeling of soft tissues, the visual representations and methods of “virtual organ” creation are lagging behind. Existing 3D virtual organ models are often “hand crafted” in their topology and visual appearance using polygonal modeling and texture mapping techniques. For a surgical simulator to be truly integrated within the educational framework requires the ability of the simulator to present a variety of 3D virtual organs to allow trainee exposure to biological variability and disease pathology. The surface scanning of preserved biological specimens offers the opportunity to digitally recreate these “gold standard” teaching resources within the simulator or other medical education software. Seven commercially available 3D object scanners employing a range of surface acquisition techniques (photogrammetry, structured light and laser scanning) have been tested on a number of test objects including preserved porcine and human organs. In all cases the scanners were able to reconstruct rigid objects with matt surfaces. However, when scanning human or animal organs which are both deformable and posses highly reflective surfaces the majority of systems failed to acquire sufficient data to effect a full reconstruction. Of the techniques investigated, systems based on laser scanning appear most promising. However, most of these techniques require significant post-processing effort with the exception of the Arius3D scanner which also allows the quantitative recovery of specimen color.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA76 Computer software
Publisher: Springer
ISSN: 0302-9743
Last Modified: 19 Mar 2016 23:13
URI: http://orca.cf.ac.uk/id/eprint/43183

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