Abstract

Dental caries is a disease characterized by demineralization of enamel crystals leading to the penetration of bacteria into the dentin and pulp. If left untreated, the disease can lead to pain, infection and tooth loss. Early detection of enamel demineralization resulting in increased enamel porosity, commonly known as white spots, is a difficult diagnostic task. Several papers reported on near infrared (NIR) spectroscopy to be a potentially useful noninvasive spectroscopic technique for early detection of caries lesions. However, the conducted studies were mostly qualitative and did not include the critical assessment of the spectral variability of the sound and carious dental tissues and influence of the water content. Such assessment is essential for development and validation of reliable qualitative and especially quantitative diagnostic tools based on NIR spectroscopy. In order to characterize the described spectral variability, a standardized diffuse reflectance hyper-spectral database was constructed by imaging 12 extracted human teeth with natural lesions of various degrees in the spectral range from 900 to 1700 nm with spectral resolution of 10 nm. Additionally, all the teeth were imaged by digital color camera. The influence of water content on the acquired spectra was characterized by monitoring the teeth during the drying process. The images were assessed by an expert, thereby obtaining the gold standard. By analyzing the acquired spectra we were able to accurately model the spectral variability of the sound dental tissues and identify the advantages and limitations of NIR hyper-spectral imaging.

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