Automatic extraction of mandibular bone geometry for anatomy-based synthetization of radiographs
| Autor: | Jyrki Lötjönen, Mikko Lilja, Martti Kalke, Kari Antila |
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| Rok vydání: | 2009 |
| Předmět: |
Computer science
Radiography 02 engineering and technology Mandible 030218 nuclear medicine & medical imaging Pattern Recognition Automated 03 medical and health sciences 0302 clinical medicine Imaging Three-Dimensional stomatognathic system Artificial Intelligence 0202 electrical engineering electronic engineering information engineering Radiography Dental Humans Segmentation image segmentation Bone geometry business.industry biomedical image X-ray imaging Anatomy Radiographic Image Enhancement Radiographic Image Interpretation Computer-Assisted 020201 artificial intelligence & image processing processing Tomography business Tomography X-Ray Computed Algorithms |
| Zdroj: | Antila, K, Lilja, M, Kalke, M & Lötjönen, J 2008, Automatic extraction of mandibular bone geometry for anatomy based synthetization of radiographs . in 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society . IEEE Institute of Electrical and Electronic Engineers, pp. 490-493, 30th Annual International IEEE EMBS Conference 2008, Vancouver, Canada, 20/08/08 . https://doi.org/10.1109/IEMBS.2008.4649197 |
| ISSN: | 2375-7477 |
| DOI: | 10.1109/IEMBS.2008.4649197 |
| Popis: | We present an automatic method for segmenting Cone-Beam Computerized Tomography (CBCT) volumes and synthetizing orthopantomographic, anatomically aligned views of the mandibular bone. The model-based segmentation method was developed having the characteristics of dental CBCT, severe metal artefacts, relatively high noise and high variability of the mandibular bone shape, in mind. First, we applied the segmentation method to delineate the bone. Second, we aligned a model resembling the geometry of orthopantomographic imaging according to the segmented surface. Third, we estimated the tooth orientations based on the local shape of the segmented surface. These results were used in determining the geometry of the synthetized radiograph. Segmentation was done with excellent results: with 14 samples we reached 0.57 ± 0.16 mm mean distance from hand drawn reference. The estimation of tooth orientations was accurate with error of 0.65 ± 8.0 degrees. An example of these results used in synthetizing panoramic radiographs is presented. |
| Databáze: | OpenAIRE |
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