Evaluation of 3D Modeling Workflows Using Dental CBCT Data for Periodontal Regenerative Treatment.
Styliani VerykokouCharalabos IoannidisChristos AngelopoulosPublished in: Journal of personalized medicine (2022)
The cone beam computed tomography (CBCT) technology is nowadays widely used in the field of dentistry and its use in the treatment of periodontal diseases has already been tackled in the international literature. At the same time, advanced segmentation methods have been introduced in state-of-the-art medical imaging software and well-established automated techniques for 3D mesh cleaning are available in 3D model editing software. However, except for the application of simple thresholding approaches for the purposes of 3D modeling of the oral cavity using CBCT data for dental applications, which does not yield accurate results, the research that has been conducted using more specialized semi-automated thresholding in dental CBCT images using existing software packages is limited. This article aims to fill the gap in the state-of-the-art research concerning the usage of CBCT data for 3D modeling of the hard tissues of the oral cavity of patients with periodontitis using existing software tools, for the needs of designing and printing 3D scaffolds for periodontal regeneration. In this context, segmentation and 3D modeling workflows using dental CBCT data that belong to a patient with periodontitis are evaluated, comparisons between the 3D models of the teeth and the alveolar bone generated through the experiments that yielded the most satisfactory results are made, and an optimal and efficient methodology for creating 3D models of teeth and alveolar bone, especially for being used as the basis for generating bioabsorbable 3D printed scaffolds of personalized treatment against periodontitis, is discussed.
Keyphrases
- cone beam computed tomography
- deep learning
- image quality
- electronic health record
- stem cells
- data analysis
- big data
- convolutional neural network
- oral health
- high resolution
- machine learning
- systematic review
- gene expression
- magnetic resonance
- bone mineral density
- high throughput
- computed tomography
- artificial intelligence
- soft tissue
- mass spectrometry
- smoking cessation