期刊论文

Zhang, Yudong

英文

Multimedia Tools and Applications

1380-7501

2016

75

23

15601-15617

10.1007/s11042-015-2649-7

NSFCNational Natural Science Foundation of China (NSFC) [610011024, 61273243, 51407095]; Program of Natural Science Research of Jiangsu Higher Education Institutions [13KJB460011, 14KJB520021]; Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing [BM2013006]; Key Supporting Science and Technology Program (Industry) of Jiangsu Province [BE2012201, BE2014009-3, BE2013012-2]; Special Funds for Scientific and Technological Achievement Transformation Project in Jiangsu Province [BA2013058]; Nanjing Normal University Research Foundation for Talented Scholars [2013119XGQ0061, 2014119XGQ0080]; Science Research Foundation of Hunan Provincial Education Department [12B023]

本校为第一机构

It is very important to early detect abnormal brains, in order to save social and hospital resources. The wavelet-energy was a successful feature descriptor that achieved excellent performances in various applications; hence, we proposed a novel wavelet-energy based approach for automated classification of MR brain images as normal or abnormal. SVM was used as the classifier, and biogeography-based optimization (BBO) was introduced to optimize the weights of the SVM. The results based on a 5 x 5-fold cross validation showed the performance of the proposed BBO-KSVM was superior to BP-NN, KSVM, ...