Registration of dental tomographic volume data and scan surface data using dynamic segmentation

Keonhwa Jung, Sukwoo Jung, Inseon Hwang, Taeksoo Kim, Minho Chang

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


Over recent years, computer-aided design (CAD) has become widely used in the dental industry. In dental CAD applications using both volumetric computed tomography (CT) images and 3D optical scanned surface data, the two data sets need to be registered. Previous works have registered volume data and surface data by segmentation. Volume data can be converted to surface data by segmentation and the registration is achieved by the iterative closest point (ICP) method. However, the segmentation needs human input and the results of registration can be poor depending on the segmented surface. Moreover, if the volume data contains metal artifacts, the segmentation process becomes more complex since post-processing is required to remove the metal artifacts, and initially positioning the registration becomes more challenging. To overcome these limitations, we propose a modified iterative closest point (MICP) process, an automatic segmentation method for volume data and surface data. The proposed method uses a bundle of edge points detected along an intensity profile defined by points and normal of surface data. Using this dynamic segmentation, volume data becomes surface data which can be applied to the ICP method. Experimentally, MICP demonstrates fine results compared to the conventional registration method. In addition, the registration can be completed within 10 s if down sampling is applied.

Original languageEnglish
Article number1762
JournalApplied Sciences (Switzerland)
Issue number10
Publication statusPublished - 2018 Sept 29

Bibliographical note

Funding Information:
Funding: This research was supported by the Technology Innovation Program (10065150, Development for Low-Cost and Small LIDAR System Technology Based on 3D Laser scanning for 360 Real-time Monitoring), funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea) and the Korea Evaluation Institute of Industrial Technology (KEIT, Korea).

Publisher Copyright:
© 2018 by the authors.


  • Iterative closest points
  • Local registration
  • Multimodal medical image registration

ASJC Scopus subject areas

  • General Materials Science
  • Instrumentation
  • General Engineering
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes


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