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Optical stereo matching for digitizing edentulous jaws.

Identifieur interne : 005F38 ( Main/Exploration ); précédent : 005F37; suivant : 005F39

Optical stereo matching for digitizing edentulous jaws.

Auteurs : M. Busch ; B. Kordass

Source :

RBID : pubmed:19216308

Descripteurs français

English descriptors

Abstract

So far, CAD/CAM technology has not yet made any noteworthy inroads into removable dentures. One of the possible reasons for this may be the lack of a tried-and-tested and economically acceptable scanner technology. Our motivation for developing our own 3D digitization method was therefore to develop a really low-cost scanner under exclusive use of standard industrial components. The method presented here for spatial acquisition of edentulous jaws is based on the evaluation of the optical structure inherent in jaw impressions themselves. For this purpose, an optimized method of Dense Stereo Matching on three images (Fig 1), acquired from three different perspectives, is used.

PubMed: 19216308


Affiliations:


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Le document en format XML

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<term>Image Processing, Computer-Assisted (instrumentation)</term>
<term>Imaging, Three-Dimensional (instrumentation)</term>
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<term>Algorithmes</term>
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<term>Imagerie tridimensionnelle ()</term>
<term>Imagerie tridimensionnelle (instrumentation)</term>
<term>Modèles dentaires</term>
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<term>Mâchoire édentée</term>
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<term>Imaging, Three-Dimensional</term>
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<div type="abstract" xml:lang="en">So far, CAD/CAM technology has not yet made any noteworthy inroads into removable dentures. One of the possible reasons for this may be the lack of a tried-and-tested and economically acceptable scanner technology. Our motivation for developing our own 3D digitization method was therefore to develop a really low-cost scanner under exclusive use of standard industrial components. The method presented here for spatial acquisition of edentulous jaws is based on the evaluation of the optical structure inherent in jaw impressions themselves. For this purpose, an optimized method of Dense Stereo Matching on three images (Fig 1), acquired from three different perspectives, is used.</div>
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