information device construction plaque detection
Rapid Detection and Segmentation of Dental Plaque
With Low-Cost Fluorescent Imaging Systems
Keith Angelino*, Pratik Shah*, David Edlund, Mrinal Mohit, and Gregory Yauney
* These authors contributed equally to this work.
Corresponding author: pratiks@media.mit.edu
Background: Significant numbers of adults and children have untreated plaque due to poor oral hygiene and consequently suffer from associate dental and systemic diseases.
Methods: A handheld device equipped with 405 nm light-emitting diodes was constructed to examine the prevalence of red fluorescence signatures associated with dental plaque. This device was used for in vivo imaging of all eight incisors and all four canines of twenty-eight consenting human subjects. The same areas were further imaged under white light illumination with a commercial image-processing based plaque-imaging device, and evaluated by a hygienist and dentist. A custom computer vision algorithm using pixel information was developed to calculate plaque coverage ratios ranging from 0 (no plaque) to 1 (complete plaque coverage) for images captured by both devices.
Results: The algorithm calculated red fluorescence-based plaque coverage ratios ranging from 0.011 to 0.211 for the subjects imaged. Clinical assessment and statistical analyses of associated plaque ratios of the 405 nm device images indicated high sensitivity and specificity in detecting dental plaque by the experimental device compared to the commercial reference device.
Conclusions: Our low-cost and open source 405 nm device and associated computer vision algorithm successfully captured red fluorescence signatures associated with dental plaque and demonstrated comparable performance to an expensive commercially available device. We thus provide a proof of concept validation for the construction and application of a sensitive cost effective plaque-detecting device. We also provide a miniaturized mobile adaptable version of the device. We also share a step-by-step guide for device assembly and webhost the associated software to facilitate open-source access to cost-effective at-home, in-clinic oral care technologies.
May 2017
Visualization by Sonali Patel.