HOG Based Radial Basis Function Network for Brain MR Image Classification

被引：0
|
作者：
Behera, N. K. S. [1 ]
Sahoo, M. K. [1 ]
Behera, H. S. [1 ]
机构：
[1] Veer Surendra Sai Univ Technol, Dept Comp Sci Engn & Informat Technol, Burla 768018, Odisha, India
来源：
COMPUTATIONAL INTELLIGENCE IN DATA MINING, VOL 1 | 2015年 / 31卷
关键词：
Principal component analysis; Histograms oriented gradients; Magnetic resonance imaging; Radial basis function network; Skull stripping; SKULL STRIPPING PROBLEM;
D O I：
10.1007/978-81-322-2205-7_5
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Fully automated computer-aided diagnosis system is very much helpful for early detection and diagnosing of brain abnormalities like cancers and tumors. This paper presents two hybrid intelligent techniques such as HOG+PCA+RBFN and HOG+PCA+k-NN, which consists of four stages namely skull stripping, feature extraction, dimension reduction and classification. For efficient feature extraction Histograms of Oriented Gradients (HOG) method is used to extract the required feature vector and then the proposed techniques are used to classify images as normal or abnormal. The results show that the proposed technique gives an accuracy of 100 %, sensitivity of 99 % and specificity 100 %.
引用
收藏
页码：45 / 56
页数：12
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