Automatic analysis algorithm for acquiring standard dental and mandibular shape data using cone-beam computed tomography.
Jae Joon HwangSang-Sun HanChena LeeYun-Hoa JungPublished in: Scientific reports (2018)
This study aims to introduce a new algorithm developed using retrospective cone-beam computed tomography (CBCT) data to obtain a standard dental and mandibular arch shape automatically for an optimal panoramic focal trough. A custom-made program was developed to analyze each arch shape of randomly collected 30 CBCT images. First, volumetric data of the mandible were binarized and projected in the axial direction to obtain 2-dimensional arch images. Second, 30 patients' mandibular arches were superimposed on the center of the bilateral distal contact points of the mandibular canines to generate an average arch shape. Third, the center and boundary of a panoramic focal trough were obtained using smoothing splines. As a result, the minimum thickness and transition of the focal trough could be obtained. If this new algorithm is applied to big data of retrospective CBCT images, standard focal troughs could be established by race, sex, and age group, which would improve the image quality of dental panoramic radiography.
Keyphrases
- cone beam computed tomography
- big data
- deep learning
- artificial intelligence
- machine learning
- convolutional neural network
- image quality
- optical coherence tomography
- electronic health record
- aortic dissection
- oral health
- end stage renal disease
- newly diagnosed
- computed tomography
- cross sectional
- chronic kidney disease
- ejection fraction
- quality improvement
- climate change
- neural network
- prognostic factors
- peritoneal dialysis
- case report
- dual energy
- patient reported