Design of auto-classifying system and its application in Raman spectroscopy diagnosis of gastric carcinoma

Author

Tan, Yi-yong ; Shen, Ai-guo ; Zhang, Jing-wei ; Wu, Nan ; Feng, Liang ; Wu, Qiao-feng ; Ye, Yong ; Hu, Ji-ming

Author_Institution

Dept. of Anal. & Meas. Sci., Wuhan Univ., China

Volume

3

fYear

2003

fDate

2-5 Nov. 2003

Firstpage

1360

Abstract

A tentative user-friendly auto-classifying system is developed to classify Raman spectra of gastric carcinoma tissues. By combining two efficient fuzzy clustering methods: artificial neural network (ANN) and fuzzy C-means (FCM), the software system integrates high robustness of ANN and strong quantity estimation ability of FCM, and provides more credible classifying results for the Raman spectroscopy auto-diagnosis of gastric carcinoma. Also the system can be applied to classifying of other spectroscopy by some necessary alteration of feature vector.

Keywords

Raman spectroscopy; cancer; fuzzy set theory; medical diagnostic computing; neural nets; patient diagnosis; pattern clustering; vectors; Raman spectroscopy; artificial neural network; autoclassifying system; cancer diagnosis; feature vector; fuzzy C-means; fuzzy clustering method; gastric carcinoma diagnosis; Artificial neural networks; Cancer; Diseases; Endoscopes; In vivo; Raman scattering; Robustness; Software packages; Software systems; Spectroscopy;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2003 International Conference on

Print_ISBN

0-7803-8131-9

Type

conf

DOI

10.1109/ICMLC.2003.1259703

Filename

1259703