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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Joseph N. Mait
  • Vol. 49, Iss. 11 — Apr. 10, 2010
  • pp: 2006–2013

Tongue fissure extraction and classification using hyperspectral imaging technology

Qingli Li, Yiting Wang, Hongying Liu, Zhen Sun, and Zhi Liu  »View Author Affiliations


Applied Optics, Vol. 49, Issue 11, pp. 2006-2013 (2010)
http://dx.doi.org/10.1364/AO.49.002006


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Abstract

Tongue fissures, an important feature on the tongue surface, may be pathologically related to some diseases. Most existing tongue fissure extraction methods use tongue images captured by traditional charge coupled device cameras. However, these conventional methods cannot be used for an accurate analysis of the tongue surface due to limited information from the images. To solve this, a hyperspectral tongue imager is used to capture tongue images instead of a digital camera. New algorithms for automatic tongue fissure extraction and classification, based on hyperspectral images, are presented. Both spectral and spatial information of the tongue surface is used to segment the tongue body and extract tongue fissures. Then a classification algorithm based on a hidden Markov model is used to classify tongue fissures into 12 typical categories. Results of the experiment show that the new method has good performance in terms of the classification rates of correctness.

© 2010 Optical Society of America

OCIS Codes
(100.2000) Image processing : Digital image processing
(100.2960) Image processing : Image analysis
(170.4580) Medical optics and biotechnology : Optical diagnostics for medicine
(170.4730) Medical optics and biotechnology : Optical pathology

ToC Category:
Image Processing

History
Original Manuscript: October 13, 2009
Revised Manuscript: February 19, 2010
Manuscript Accepted: March 9, 2010
Published: April 1, 2010

Virtual Issues
Vol. 5, Iss. 8 Virtual Journal for Biomedical Optics

Citation
Qingli Li, Yiting Wang, Hongying Liu, Zhen Sun, and Zhi Liu, "Tongue fissure extraction and classification using hyperspectral imaging technology," Appl. Opt. 49, 2006-2013 (2010)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-49-11-2006

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