TY - JOUR
T1 - Automated classification of brain images using wavelet-energy and biogeography-based optimization
AU - Yang, Gelan
AU - Zhang, Yudong
AU - Yang, Jiquan
AU - Ji, Genlin
AU - Dong, Zhengchao
AU - Wang, Shuihua
AU - Feng, Chunmei
AU - Wang, Qiong
N1 - Publisher Copyright:
© 2015, Springer Science+Business Media New York.
PY - 2016/12/1
Y1 - 2016/12/1
N2 - 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 × 5-fold cross validation showed the performance of the proposed BBO-KSVM was superior to BP-NN, KSVM, and PSO-KSVM in terms of sensitivity and accuracy. The study offered a new means to detect abnormal brains with excellent performance.
AB - 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 × 5-fold cross validation showed the performance of the proposed BBO-KSVM was superior to BP-NN, KSVM, and PSO-KSVM in terms of sensitivity and accuracy. The study offered a new means to detect abnormal brains with excellent performance.
KW - Biogeography-based optimization
KW - Classification
KW - Magnetic resonance imaging
KW - Pattern recognition
KW - Support vector machine
UR - http://www.scopus.com/inward/record.url?scp=84928688048&partnerID=8YFLogxK
U2 - 10.1007/s11042-015-2649-7
DO - 10.1007/s11042-015-2649-7
M3 - Article
AN - SCOPUS:84928688048
SN - 1380-7501
VL - 75
SP - 15601
EP - 15617
JO - Multimedia Tools and Applications
JF - Multimedia Tools and Applications
IS - 23
ER -