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Hepatitis Diagnosis Using Facial Color Image

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Book cover Medical Biometrics (ICMB 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4901))

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Abstract

Facial color diagnosis is an important diagnostic method in traditional Chinese medicine (TCM). However, due to its qualitative, subjective and experi-ence-based nature, traditional facial color diagnosis has a very limited application in clinical medicine. To circumvent the subjective and qualitative problems of facial color diagnosis of Traditional Chinese Medicine, in this paper, we present a novel computer aided facial color diagnosis method (CAFCDM). The method has three parts: face Image Database, Image Preprocessing Module and Diagnosis Engine. Face Image Database is carried out on a group of 116 patients affected by 2 kinds of liver diseases and 29 healthy volunteers. The quantitative color feature is extracted from facial images by using popular digital image processing techni-ques. Then, KNN classifier is employed to model the relationship between the quantitative color feature and diseases. The results show that the method can properly identify three groups: healthy, severe hepatitis with jaundice and severe hepatitis without jaundice with accuracy higher than 73%.

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© 2007 Springer-Verlag Berlin Heidelberg

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Liu, M., Guo, Z. (2007). Hepatitis Diagnosis Using Facial Color Image. In: Zhang, D. (eds) Medical Biometrics. ICMB 2008. Lecture Notes in Computer Science, vol 4901. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77413-6_21

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  • DOI: https://doi.org/10.1007/978-3-540-77413-6_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77410-5

  • Online ISBN: 978-3-540-77413-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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