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Feature Extraction and Analysis on Xinjiang High Morbidity of Kazak Esophageal Cancer by Using Comprehensive Feature
Murat HAMIT, Fang YANG, Abdugheni KUTLUK, Chuanbo YAN, Elzat ALIP , Weikang YUAN
Pages - 148 - 155     |    Revised - 01-06-2014     |    Published - 01-07-2014
Volume - 8   Issue - 4    |    Publication Date - July 2014  Table of Contents
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KEYWORDS
Xinjiang High Morbidity of Kazak, Esophageal Cancer, Comprehensive Feature, Feature Extraction, Image Classification.
ABSTRACT
Image feature extraction technology has been widely applied in image data mining, pattern recognition and classification. Esophageal cancer is a common digestive malignant tumor, China is one of the world's highest incidence and mortality rates of esophageal cancer among the countries, Xinjiang Uygur Autonomous Region is a high incidence area of esophageal cancer, and the kazak is the esophageal cancer high-risk groups. In this paper, we selected 60 advanced esophageal X-ray barium images, half of them are constricted esophagus and the rest are ulcerous esophagus. Firstly, image preprocessing approaches were used to preprocess images. Secondly, extracting the gray-scale histogram features and the GLCM features of the images, then composing the two features into comprehensive feature. Finally, using Bayes discriminant analysis to verify the classification ability of the comprehensive feature. The classification accuracy for constricted esophagus was 86.7%, for ulcerous esophagus was 93.3%.
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Professor Murat HAMIT
college of medical engineering techology - China
murat.hamit@xjmu.edu.cn
Miss Fang YANG
college of medical engineering techology - China
Professor Abdugheni KUTLUK
college of medical engineering techology - China
Professor Chuanbo YAN
college of medical engineering techology - China
Mr. Elzat ALIP
college of medical engineering techology - China
Mr. Weikang YUAN
college of medical engineering techology - China