文章基本信息

标题：Medical Image Classification: A Comparison of Various Handcrafted Features
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作者：Alebiosu David Olayemi ; Mohammad Reza Zare ; Muhammad Fermi P. 等
期刊名称：International Journal of Advances in Soft Computing and Its Applications
印刷版ISSN：2074-8523
出版年度：2019
卷号：11
期号：3
页码：24-39
出版社：International Center for Scientific Research and Studies
摘要：This paper compares different feature extraction techniques exploited by various researchers for medical image classification and retrieval. They are categorized into three groups; (i) feature extraction techniques used for shape, (ii) feature extraction techniques used for texture and (iii) local patch based representation such as bag of visual words. The main aim of this work is to determine the capabilities and the challenges of medical images handcrafted feature extraction techniques as well as to see how best to improve the efficiency and accuracy of medical image classification and retrieval. It focused centrally on the analysis of the most commonly used shape and texture feature extraction techniques applied on medical images. Bag of visual words which is a type of local patch based method was also analysed. The limitations of these techniques are discussed as presented in the paper reviewed. We summarized with some conclusions and a recommendation for future exploits.
关键词：Bag of visual words;Classification;Feature extraction;Medical image;X-ray.