文章基本信息

标题：Lung Nodule Detection Based on Semi Supervised Classification
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作者：S.Ramya Preethi ; Prof. R.Vijayalakshmi ; P.Deepa 等
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2015
期号：MULTICON
页码：250
出版社：S&S Publications
摘要：Lung cancer is a major cause of cancer related deaths. Thus the identification of lung nodule is essentialpart for screening and diagnosis of lung cancer. The classification of four type of lung nodule in low dose computedtomography scans. i.e., Well-circumscribed, vascularized, juxta-pleural, and pleural-tail. Thus classification of lungnodule is on three stages by combining the lung nodule with surrounding anatomical structures. First stage an adaptivegraph patch based division is used to construct concentric multi level partition use of super pixel formulation. Thesecond stage of the method is feature set designed to incorporate intensity, texture, and gradient information for imagepatch feature description use of scale-invariant feature transform, local binary pattern provides texture description ofobjects and Histogram of oriented gradients represents the local portions of object. And third stage is to classify thelung nodule based on semi supervised classifier with respect to feature descriptors and performance is compared withsupervised classification.
关键词：scale-invariant feature transform; local binary pattern; Histogram of oriented gradients; semisupervised;classifier.