Biomedical subjects

Kelvin W C Foong

Publications and source records attributed to Kelvin W C Foong.

3 recordsLinked to original sources

PubMed2005

Analysis of esthetic smiles by using computer vision techniques.

Properly aligned teeth and a beautiful smile are the twin goals of orthodontic treatment. Unfortunately, a change in the smile arc is sometimes an unintended consequence of proper alignment. We used 3-dimensional dental models and visualization techniques, including curve-fitting and image-processing algorithms, to analyze smile arcs with respect to different parameters. The results show that smile consonance depends greatly on the conversational distance and the angle of elevation between the viewer and the smile.

Esthetics, Dental↗

PubMed2004

Computer-based extraction of the inferior alveolar nerve canal in 3-D space.

Computed tomography (CT) is increasingly employed in orthodontic treatment. One of the most successful applications is in dental implantology, in which an artificial root is surgically inserted into the jawbone to provide anchorage for a dental prosthesis. For successful implant surgery, it is crucial to locate internal structures such as the inferior alveolar nerve canal (IAC). This paper presents a computerized technique for extracting the IAC. To facilitate the extraction, we first generate panoramic CT images (panoramics) by reformatting the original CT images. The panoramics are a series of cross-sectional images along curved planes through the mandible (lower jawbone). Hollow canals are subsequently detected by analyzing the voxel intensities and 3-D gradient orientations in the panoramics. The axis of the IAC is then traced out by a novel 3-D line-tracking technique. The method is effective for extracting the IAC despite the open structure of the surrounding bone.

Algorithms↗

PubMed2004

Tooth segmentation of dental study models using range images.

The accurate segmentation of the teeth from the digitized representation of a dental study model is an important component in computer-based algorithms for orthodontic feature detection and measurement and in the simulation of orthodontic procedures such as tooth rearrangement. This paper presents an automated method for tooth segmentation from the three-dimensional (3-D) digitized image captured by a laser scanner. We avoid the complexity of directly processing 3-D mesh data by proposing the innovative idea of detecting features on two range images computed from the 3-D image. The dental arch is first obtained from the plan-view range image. Using the arch as the reference, a panoramic range image of the dental model can be computed. The interstices between the teeth are detected separately in the two range images, and results from both views are combined for a determination of interstice locations and orientations. Finally, the teeth are separated from the gums by delineating the gum margin. The algorithm was tested on 34 dental models representing a variety of malocclusions and was found to be robust and accurate.

Algorithms↗