본문 바로가기
KERD
논문KCI 등재

치과 교정치료 계획을 위한 파노라마 영상을 이용한 자동 개별 치아 영역 분류 방법

Automatic Individual Tooth Region Separation using Accurate Tooth Curve Detection for Orthodontic Treatment Planning

0

조회

0

다운로드

0

인용

0

참고문헌

키워드

주제분류컴퓨터학

초록

In this paper, we propose the automatic detection method for individual region separation using panorama image. Finding areas that contain individual teeth is one of the most important tasks in automating 3D models through individual tooth separation. In the conventional method, the maxillary and mandibular teeth regions are separated using a straight line or a specific CT slide, and the tooth regions are separated using a straight line in the vertical direction. In the conventional method, since the teeth are arranged in a curved shape, there is a problem that each tooth region is incorrectly detected in order to generate an accurate tooth region. This is a major obstacle to automating the creation of individual tooth models. In this study, we propose a method to find the correct tooth curve by using the jawbone curve which is very similar to the tooth curve in order to overcome the problem of finding the area containing the existing tooth. We have proposed a new method to accurately set individual tooth regions using the feature that individual teeth are arranged in a direction similar to the normal direction of the tooth alignment curve. In the proposed method, the maxillary and mandibular teeth can be more precisely separated than the conventional method, and the area including the individual teeth can be accurately set. Experiments using real dental CT images demonstrate the superiority of the proposed method.

Abstract

In this paper, we propose the automatic detection method for individual region separation using panorama image. Finding areas that contain individual teeth is one of the most important tasks in automating 3D models through individual tooth separation. In the conventional method, the maxillary and mandibular teeth regions are separated using a straight line or a specific CT slide, and the tooth regions are separated using a straight line in the vertical direction. In the conventional method, since the teeth are arranged in a curved shape, there is a problem that each tooth region is incorrectly detected in order to generate an accurate tooth region. This is a major obstacle to automating the creation of individual tooth models. In this study, we propose a method to find the correct tooth curve by using the jawbone curve which is very similar to the tooth curve in order to overcome the problem of finding the area containing the existing tooth. We have proposed a new method to accurately set individual tooth regions using the feature that individual teeth are arranged in a direction similar to the normal direction of the tooth alignment curve. In the proposed method, the maxillary and mandibular teeth can be more precisely separated than the conventional method, and the area including the individual teeth can be accurately set. Experiments using real dental CT images demonstrate the superiority of the proposed method.

참고문헌 (11)

  1. K. D. P. Barnfather, "Restoration of the upper dental arch using Lava™ all-ceramic crown and bridgework", British Dental Journal, 202(12), pp.731~735 (2007), Springer Nature[DOI]
  2. R. Bryan Bell, "Computer Planning and Intraoperative Navigation in Cranio-Maxillofacial Surgery", Oral and Maxillofacial Surgery Clinics of North America, 22(1), pp.135~156 (2010), Elsevier BV[DOI]
  3. Omaima Nomir, "A system for human identification from X-ray dental radiographs", Pattern Recognition, 38(8), pp.1295~1305 (2005), Elsevier BV[DOI]
  4. H. Gao, "Automatic tooth region separation for dental CT images", Third International Conference on Convergence and Hybrid Information Technology, 2008. ICCIT'08, 1, pp.897~901 (2008), IEEE
  5. Yangzhou Gan, "Tooth and Alveolar Bone Segmentation from Dental Computed Tomography Images", IEEE Journal of Biomedical and Health Infomatics, 22, pp.194~204 (2017)
  6. Hosntalab, "Segmentation of teeth in CT volumetric dataset by panoramic projection and variational level set", international Journal of Computer Assisted Radiology and Surgery (2008)
  7. Mahsa Sepehrian, "Individual Teeth Segmentation in CBCT and MSCT Dental Images Using Watershed", Proceedings of 20th Iranian Conference on Biomedical Engineering(ICME 2013), pp.27~30 (2013)
  8. CJ. Zhou, "Automatic human identification based on dental X-ray images", Biometric Technology for Human Identification, pp.373~380 (2004)
  9. Parinaz Mortahheb, "Automatic dental CT image segmentation using mean shift algorithm", 2013 8th Iranian Conference on Machine Vision and Image Processing(MVIP), pp.121~126 (2013)
  10. Hao Wang, "Tooth Separation from Dental Model Using Segmentation Field", Engineering in Medicine and Biology Society(EMBC), 2016 IEEE 38th Annual Conference, pp.5616~5619 (2016)
  11. H. Akhoondali, "Fully Automatic Extraction of Panoramic Dental Images from CT-Scan Volumetric Data of the Head", Jounal of Applied Sciences, 9(11), pp.2106~2114 (2009)[DOI]

관련 논문AI추천

이 간행물의 다른 논문 (21건)