Automatic detection and classification of dental fluorosis in vivo using white light and fluorescence imaging

Assessment of dental fluorosis is typically undertaken by clinical examiners in epidemiological studies. The training and calibration of such examiners is complex and time consuming and the assessments are subject to bias - frequently because of the examiner's awareness of the water fluoridation status of subjects. The use of remote scoring using photographs has been advocated but still requires trained examiners. This study has shown that image-processing methodologies applied to white light and fluorescent images could automatically score fluorosis and statistically separate fluoridated and non-fluoridated areas. The system requires further refinement to manage confounding factors such as the presence of non-fluoride opacities and tooth stain.