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TitleSegmentation of Bony Tissues from CBCT Images
Creator
Date Issued2018
Conference Name23rd IEEE International Conference on Digital Signal Processing (DSP)
Source Publication2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)
ISBN9781538668115
Conference DateNOV 19-21, 2018
Conference PlaceShanghai, China
Abstract

A segmentation algorithm of the jawbones and spinal cords is developed from cone beam computed tomographic (CBCT) data sets. Our segmentation algorithm was tested on five CBCT data sets and compared with manual segmentation results. The jawbones are bony tissues consisting of the upper jaw and the lower mandible. The procedure is based on the intensity distribution and space growing to separate the jawbones and cervical spine from their neighboring tissues. The segmentation procedure is to grow and preserve the shapes of these bony tissues. The developed segmentation algorithm separated the jawbones and cervical spine successfully. The results were quite accurate comparable with those by hand. Further, the method was robust and efficient.

KeywordCBCT segmentation space growing
DOI10.1109/ICDSP.2018.8631804
URLView source
Indexed ByCPCI-S
Language英语English
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000458909600185
Scopus ID2-s2.0-85062797811
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/6763
CollectionResearch outside affiliated institution
Affiliation
Department of Electronic and Electrical Engineering,Southern University of Science and Technology,SUSTC,Shenzhen,China
Recommended Citation
GB/T 7714
He, Siyu,Shi, Hongjian. Segmentation of Bony Tissues from CBCT Images[C], 2018.
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