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Segmentation of teeth in CT volumetric dataset by panoramic projection and variational level set

Hosntalab, M ; Sharif University of Technology | 2008

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  1. Type of Document: Article
  2. DOI: 10.1007/s11548-008-0230-9
  3. Publisher: Springer Verlag , 2008
  4. Abstract:
  5. Purpose: Quantification of teeth is of clinical importance for various computer assisted procedures such as dental implant, orthodontic planning, face, jaw and cosmetic surgeries. In this regard, segmentation is a major step. Methods: In this paper, we propose a method for segmentation of teeth in volumetric computed tomography (CT) data using panoramic re-sampling of the dataset in the coronal view and variational level set. The proposed method consists of five steps as follows: first, we extract a mask in a CT images using Otsu thresholding. Second, the teeth are segmented from other bony tissues by utilizing anatomical knowledge of teeth in the jaws. Third, the proposed method is followed by estimating the arc of the upper and lower jaws and panoramic re-sampling of the dataset. Separation of upper and lower jaws and initial segmentation of teeth are performed by employing the horizontal and vertical projections of the panoramic dataset, respectively. Based the above mentioned procedures an initial mask for each tooth is obtained. Finally, we utilize the initial mask of teeth and apply a Variational level set to refine initial teeth boundaries to final contours. Results: The proposed algorithm was evaluated in the presence of 30 multi-slice CT datasets including 3,600 images. Experimental results reveal the effectiveness of the proposed method. Conclusion: In the proposed algorithm, the variational level set technique was utilized to trace the contour of the teeth. In view of the fact that, this technique is based on the characteristic of the overall region of the teeth image, it is possible to extract a very smooth and accurate tooth contour using this technique. In the presence of the available datasets, the proposed technique was successful in teeth segmentation compared to previous techniques. © CARS 2008
  6. Keywords:
  7. Accuracy ; Algorithm ; Artifact reduction ; Data base ; Image display ; Image processing ; Image quality ; Mandible ; Maxilla ; Multidetector computed tomography ; Panoramic radiography ; Priority journal ; Tooth radiography ; Volumetry
  8. Source: International Journal of Computer Assisted Radiology and Surgery ; Volume 3, Issue 3-4 , 2008 , Pages 257-265 ; 18616410 (ISSN)
  9. URL: https://link.springer.com/article/10.1007/s11548-008-0230-9