Book chapter
Automatic detection of inferior alveolar nerve canal from cone-beam computed tomography images for dental surgery planning
Medicine Meets Virtual Reality 21, pp.61-65
Studies in health technology and informatics, v. 196, IOS Press
2014
DOI: 10.3233/978-1-61499-375-9-61
PMID: 24732481
Abstract
The inferior alveolar nerve canal is an important nerve canal in the jaw bone, and any damage to this canal can cause pain or fatal complications. Since such damage can be caused by a wrong surgical procedure or surgery plan, accurate surgery planning is necessary. Cone-beam computed tomography (CBCT) is a three-dimensional medical imaging method that is mainly used in dental treatment; however, identifying the nerve canal is difficult in CBCT images as compared to conventional CT images. This paper proposes a new concept of a panoramic curve for nerve canal detection and a detection algorithm that is usually applied to facial recognition was introduced in this study for the automatic detection of nerve canal in CBCT images.
Details
- Title: Subtitle
- Automatic detection of inferior alveolar nerve canal from cone-beam computed tomography images for dental surgery planning
- Creators
- Jin Hyeok Choi - Center for Bionics, Korea Institute of Science and Technology, Republic of KoreaSeung-Yeob Baek - Department of Mechanical and Aerospace Engineering, Seoul National University, Republic of KoreaYoungjun Kim - Center for Bionics, Korea Institute of Science and Technology, Republic of KoreaTae-Geun Son - Department of Mechanical and Aerospace Engineering, Seoul National University, Republic of KoreaSehyung Park - Center for Bionics, Korea Institute of Science and Technology, Republic of KoreaKunwoo Lee - Department of Mechanical and Aerospace Engineering, Seoul National University, Republic of Korea
- Resource Type
- Book chapter
- Publication Details
- Medicine Meets Virtual Reality 21, pp.61-65
- Publisher
- IOS Press; Netherlands
- Series
- Studies in health technology and informatics; v. 196
- DOI
- 10.3233/978-1-61499-375-9-61
- PMID
- 24732481
- ISSN
- 0926-9630
- eISSN
- 1879-8365
- Language
- English
- Date published
- 2014
- Academic Unit
- Electrical and Computer Engineering; Industrial and Systems Engineering; Radiation Oncology
- Record Identifier
- 9984046901202771
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