Cone-Beam Computed Tomography Image Pretreatment and Segmentation

Jia Zheng, Dinghua Zhang, Kuidong Huang, Yuanxi Sun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Segmentation accuracy is critical in CBCT (cone-beam computed tomography) nondestructive detection. And it is influenced by the segmentation accuracy of CBCT serial slice images. However, the noise and artifacts in CBCT images make it hard to segment CBCT images precisely. To increase CBCT image segmentation accuracy, the 3D information in CBCT images should be fully used. We proposed and compared four connection models for CBCT images pretreatment. They can decrease the noise in CBCT images. Moreover, we propose a 3D CBCT image segmentation method based on the accumulated FCM-S. In the experiment, CBCT slice images of a workpiece are segmented by our proposed method and comparing methods. The segmentation results certified the effectiveness of our method.

Original languageEnglish
Title of host publicationProceedings - 2018 11th International Symposium on Computational Intelligence and Design, ISCID 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages25-28
Number of pages4
ISBN (Electronic)9781538685266
DOIs
StatePublished - 2 Jul 2018
Event11th International Symposium on Computational Intelligence and Design, ISCID 2018 - Hangzhou, China
Duration: 8 Dec 20189 Dec 2018

Publication series

NameProceedings - 2018 11th International Symposium on Computational Intelligence and Design, ISCID 2018
Volume1

Conference

Conference11th International Symposium on Computational Intelligence and Design, ISCID 2018
Country/TerritoryChina
CityHangzhou
Period8/12/189/12/18

Keywords

  • CBCT
  • image processing
  • segmentation

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