Early detection of disease-oriented state from hyperspectral tongue images with principal component analysis and vector rotation.

Abstract

In this article, we propose an effective colorprocessing algorithm to analyze the hyperspectral image of the tongue and its application to preventive medicine by the concept of Japanese traditional herbal medicine (Kampo medicine). Kampo medicine contains a number of concepts useful for preventive medicine such as "Mibyou" - disease-oriented state - signs of abnormalities. Hyperspectral images of the tongue were taken with the system with an integrating sphere, and tongue area without coating was eliminated automatically. Then, spectral information of the tongue area without coating was analyzed by principal component analysis, and the component vector best representing the clinical symptom was found by rotating the vector on a plane spanned by two arbitrary principal component vectors.

DOI: 10.1109/IEMBS.2010.5626147

Cite this paper

@article{Yamamoto2010EarlyDO, title={Early detection of disease-oriented state from hyperspectral tongue images with principal component analysis and vector rotation.}, author={Satoshi Yamamoto and Norimichi Tsumura and Keiko Ogawa-Ochiai and Toshiya Nakaguchi and Yuji Kasahara and Takao Namiki and Yoichi Miyake}, journal={Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference}, year={2010}, volume={2010}, pages={3025-8} }