TY - JOUR
T1 - Preliminary research on abnormal brain detection by wavelet-energy and quantum-behaved PSO
AU - Zhang, Yudong
AU - Ji, Genlin
AU - Yang, Jiquan
AU - Wang, Shuihua
AU - Dong, Zhengchao
AU - Phillips, Preetha
AU - Sun, Ping
N1 - Publisher Copyright:
© 2016 - IOS Press and the authors. All rights reserved.
PY - 2016/6/13
Y1 - 2016/6/13
N2 - It is important to detect abnormal brains accurately and early. The wavelet-energy (WE) was a successful feature descriptor that achieved excellent performance in various applications; hence, we proposed a WE based new approach for automated abnormal detection, and reported its preliminary results in this study. The kernel support vector machine (KSVM) was used as the classifier, and quantum-behaved particle swarm optimization (QPSO) was introduced to optimize the weights of the S VM. The results based on a 5 × 5-fold cross validation showed the performance of the proposed WE + QPSO-KSVM was superior to "DWT + PCA + BP-NN", "DWT + PCA + RBF-NN", "DWT + PCA + PSO-KSVM", "WE + BPNN", "WE + KSVM", and "DWT + PCA + GA-KSVM" w.r.t. sensitivity, specificity, and accuracy. The work provides a novel means to detect abnormal brains with excellent performance.
AB - It is important to detect abnormal brains accurately and early. The wavelet-energy (WE) was a successful feature descriptor that achieved excellent performance in various applications; hence, we proposed a WE based new approach for automated abnormal detection, and reported its preliminary results in this study. The kernel support vector machine (KSVM) was used as the classifier, and quantum-behaved particle swarm optimization (QPSO) was introduced to optimize the weights of the S VM. The results based on a 5 × 5-fold cross validation showed the performance of the proposed WE + QPSO-KSVM was superior to "DWT + PCA + BP-NN", "DWT + PCA + RBF-NN", "DWT + PCA + PSO-KSVM", "WE + BPNN", "WE + KSVM", and "DWT + PCA + GA-KSVM" w.r.t. sensitivity, specificity, and accuracy. The work provides a novel means to detect abnormal brains with excellent performance.
KW - Magnetic resonance imaging
KW - Particle swarm optimization
KW - Quantum-behaved PSO
KW - Wavelet energy
UR - http://www.scopus.com/inward/record.url?scp=84978523895&partnerID=8YFLogxK
U2 - 10.3233/THC-161191
DO - 10.3233/THC-161191
M3 - Conference article
C2 - 27163327
AN - SCOPUS:84978523895
SN - 0928-7329
VL - 24
SP - S641-S649
JO - Technology and Health Care
JF - Technology and Health Care
T2 - 4th International Conference on Biomedical Engineering and Biotechnology, iCBEB 2015
Y2 - 18 August 2015 through 21 August 2015
ER -