文章基本信息

标题：Classification of Ultrasound Kidney Images using PCA and Neural Networks
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作者：Mariam Wagih Attia ; F.E.Z. Abou-Chadi ; Hossam El-Din Moustafa 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2015
卷号：6
期号：4
DOI：10.14569/IJACSA.2015.060407
出版社：Science and Information Society (SAI)
摘要：In this paper, a computer-aided system is proposed for automatic classification of Ultrasound Kidney diseases. Images of five classes: Normal, Cyst, Stone, Tumor and Failure were considered. A set of statistical features and another set of multi-scale wavelet-based features were extracted from the region of interest (ROI) of each image and the principal component analysis was performed to reduce the number of features. The selected features were utilized in the design and training of a neural network classifier. A correct classification rate of 97% has been obtained using the multi-scale wavelet-based features.
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; Ultrasound kidney images; Feature Extraction; Principal Component Analysis; Neural Network classifier