DocumentCode :
2377615
Title :
Medical Biometrics-Computerized TCM Diagnosis
Author :
Zhang, David
Author_Institution :
Biometrics Technol. Centre (UGC/CRC), Hong Kong Polytech. Univ., Hong Kong, China
fYear :
2010
fDate :
18-18 Dec. 2010
Firstpage :
4
Lastpage :
4
Abstract :
The Traditional Chinese Medicine (TCM) diagnosis methods, such as looking/smelling/touching, have been successfully used for thousands of years. However, these methods are mainly relied on Doctor´s experience and not quantified. In this presentation, we will try to develop a novel approach by using Medical Biometrics technology, i.e., Computerized TCM Diagnosis, to solve these problems. By some TCM-orient diagnosis acquisition devices, we could collect many kinds of date like tongue/pulse/odor with a priori knowledge from different diseases in hospitals. Then we use a statistical pattern recognition approach to extract all possible features from these images/waveforms, including color, texture, shape, and so on. After matching between our training data and testing data, some decision rules will be made. Finally, we apply our results to the practical diseases diagnosis to illustrate the effectiveness of our approach.
Keywords :
data acquisition; diseases; feature extraction; image colour analysis; image recognition; image texture; knowledge acquisition; medical image processing; patient diagnosis; statistical analysis; waveform analysis; data testing; diagnosis data acquisition device; diseases; feature extraction; image color; image shape; image texture; medical biometrics-computerized diagnosis; odor analysis; priori knowledge; pulse analysis; statistical pattern recognition; tongue data; traditional chinese medicine diagnosis method; waveform analysis; diagnosis; medical biometrics; traditional Chinese medicine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine Workshops (BIBMW), 2010 IEEE International Conference on
Conference_Location :
Hong, Kong
Print_ISBN :
978-1-4244-8303-7
Electronic_ISBN :
978-1-4244-8304-4
Type :
conf
DOI :
10.1109/BIBMW.2010.5703764
Filename :
5703764
Link To Document :
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