Abstract

Segmentation of teeth in Cone-Beam Computed Tomography (CBCT) images is challenging problem due to its noise and the similar grayscale intensity of bone and teeth element. In this paper we proposed a new method based on three-dimensional (3D) region merging and histogram thresholding for automatic segmentation of teeth on CBCT images. The proposed 3D region merging algorithm can recognized the teeth element that have similar intensity with the bone element based on the three-dimensional (3D) information of the neighboring slices of the CBCT image. Merging the teeth region will lead to more homogenous grayscale intensity distribution inside the teeth. Then histogram thresholding that utilized the characteristic of CBCT images is performed to binarize the grayscale images and obtain the teeth object. The average accuracy, sensitivity, and specificity of the proposed method are 97.75%, 80.22%, and 98.31%, respectively. The proposed method is fully automatic, therefore lead to more objective and reproducible results.

Original languageEnglish
Title of host publicationProceedings - 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages341-345
Number of pages5
ISBN (Electronic)9781538626337
DOIs
Publication statusPublished - 2 Jul 2018
EventJoint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2018 - Toyama, Japan
Duration: 5 Dec 20188 Dec 2018

Publication series

NameProceedings - 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2018

Conference

ConferenceJoint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2018
Country/TerritoryJapan
CityToyama
Period5/12/188/12/18

Keywords

  • Cone-beam computed tomography
  • Region merging
  • Teeth segmentation
  • Three-dimensional image

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