Improved classification and visualization of healthy and pathological hard dental tissues by modeling specular reflections in NIR hyperspectral images

Peter Usenik; Miran Bürmen; Aleš Fidler; Franjo Pernuš; Boštjan Likar

doi:10.1117/12.911623

23 February 2012 Improved classification and visualization of healthy and pathological hard dental tissues by modeling specular reflections in NIR hyperspectral images

Peter Usenik, Miran Bürmen, Aleš Fidler, Franjo Pernuš, Boštjan Likar

Author Affiliations +

Proceedings Volume 8315, Medical Imaging 2012: Computer-Aided Diagnosis; 83152N (2012) https://doi.org/10.1117/12.911623
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

Despite major improvements in dental healthcare and technology, dental caries remains one of the most prevalent chronic diseases of modern society. The initial stages of dental caries are characterized by demineralization of enamel crystals, commonly known as white spots, which are difficult to diagnose. Near-infrared (NIR) hyperspectral imaging is a new promising technique for early detection of demineralization which can classify healthy and pathological dental tissues. However, due to non-ideal illumination of the tooth surface the hyperspectral images can exhibit specular reflections, in particular around the edges and the ridges of the teeth. These reflections significantly affect the performance of automated classification and visualization methods. Cross polarized imaging setup can effectively remove the specular reflections, however is due to the complexity and other imaging setup limitations not always possible. In this paper, we propose an alternative approach based on modeling the specular reflections of hard dental tissues, which significantly improves the classification accuracy in the presence of specular reflections. The method was evaluated on five extracted human teeth with corresponding gold standard for 6 different healthy and pathological hard dental tissues including enamel, dentin, calculus, dentin caries, enamel caries and demineralized regions. Principal component analysis (PCA) was used for multivariate local modeling of healthy and pathological dental tissues. The classification was performed by employing multiple discriminant analysis. Based on the obtained results we believe the proposed method can be considered as an effective alternative to the complex cross polarized imaging setups.

Citation Download Citation

Peter Usenik, Miran Bürmen, Aleš Fidler, Franjo Pernuš, and Boštjan Likar "Improved classification and visualization of healthy and pathological hard dental tissues by modeling specular reflections in NIR hyperspectral images", Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 83152N (23 February 2012); https://doi.org/10.1117/12.911623

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