Dr. Qingyu Zhao Profile

Dr. Qingyu Zhao

at Stanford Univ. School of Medicine

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Proceedings Article | 4 April 2022 Poster + Paper

Thin shell demons for dental scan registration

Pranjal Sahu, Samuel Gerber, Qingyu Zhao, Tung Nguyen, Matt McCormick, Beatriz Paniagua, Jared Vicory

Proceedings Volume 12032, 120322U (2022) https://doi.org/10.1117/12.2611514

KEYWORDS: Teeth, Image registration, Image segmentation, Computed tomography, Surgery, 3D modeling, X-ray computed tomography, Skull, Scanners

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We demonstrate the application of the Thin Shell Demons (TSD) surface registration algorithm in registering the dental scans obtained from intra-oral scanners (IOS) and Cone Beam Computed Tomography (CBCT) in a semi-automatic manner. The reconstructed dentition obtained from CBCT lacks the accuracy for diagnosis and appliance fabrication that IOS provides. Current methods to register IOS to CBCT typically use Iterative Closest Point (ICP) but suffer from a lack of precision and accuracy. TSD registration has previously been shown to produce superior registration results in presence of missing patches and holes. In this work, for the first time we share its application in dental scan registration. We perform experiments on dental surface meshes obtained from CBCT and IOS for two patients who have undergone orthognathic surgery. Our method first registers the IOS mesh with the CBCT mesh using ICP. To obtain tight alignment of the tooth surface, we perform a refinement using the TSD registration. We quantify the improvement in registration by measuring the distance between the closest points present on the surface of six teeth in the IOS and CBCT meshes. Compared to using only ICP registration, TSD decreases the mean surface distance between patches and significantly improves the alignment. We also share qualitative results that clearly demonstrate the improvement due to TSD. For wide adoption and ease of access, we also share a publicly available Thin Shell Demons implementation in C++ under the open source image processing library Insight Toolkit (ITK). Python wrapping of the code is also made available. The code is available at the url: https://github.com/InsightSoftwareConsortium/ITKThinShellDemons.

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