Automatic Classification Of Medical X-Ray Images

Malaysian Journal of Computer Science

Ahmed Mueen¹  Woo Chaw Seng¹  Mohammad Reza Zare¹ 

关键词: Classification;    X-Ray;    Image Processing;   

DOI  :  

学科分类：社会科学、人文和艺术（综合）

来源: University of Malaya * Faculty of Computer Science and Information Technology

【 摘 要 】

Image representation is one of the major aspects of automatic classification algorithms. In this paper, differentfeature extraction techniques have been utilized to represent medical X-ray images. They are categorized into twogroups; (i) low-level image representation such as Gray Level Co-occurrence Matrix(GLCM), Canny EdgeOperator, Local Binary Pattern(LBP) , pixel value, and (ii) local patch-based image representation such as Bag ofWords (BoW). These features have been exploited in different algorithms for automatic classification of medical Xrayimages. We then analyzed the classification performance obtained with regard to the image representationtechniques used. These experiments were evaluated on ImageCLEF 2007 database consists of 11000 medical X-rayimages with 116 classes. Experimental results showed the classification performance obtained by exploiting LBPand BoW outperformed the other algorithms with respect to the image representation techniques used.

【 授权许可】

Unknown