title: Preliminary research on abnormal brain detection by wavelet-energy and quantum- behaved PSO.
abstract: 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 SVM. 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.
authors.affiliation: School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu, China.|Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing, Jiangsu, China.
authors.forename: Yudong
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu, China.|Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing, Jiangsu, China.
authors.forename: Genlin
authors.initials: G
authors.lastname: Ji
authors.affiliation: Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing, Jiangsu, China.
authors.forename: Jiquan
authors.initials: J
authors.lastname: Yang
authors.affiliation: School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu, China.|Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing, Jiangsu, China.
authors.forename: Shuihua
authors.initials: S
authors.lastname: Wang
authors.affiliation: Translational Imaging Division and MRI Unit, Columbia University and New York State Psychiatric Institute, New York, NY, USA.
authors.forename: Zhengchao
authors.initials: Z
authors.lastname: Dong
authors.affiliation: School of Natural Sciences and Mathematics, Shepherd University, Shepherdstown, WV, USA.
authors.forename: Preetha
authors.initials: P
authors.lastname: Phillips
authors.affiliation: Department of Electrical Engineering, The City College of New York, CUNY, New York, NY, USA.
authors.forename: Ping
authors.initials: P
authors.lastname: Sun
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D025341:Principal Component Analysis; D011873:Radiology Information Systems; D060388:Support Vector Machine; D058067:Wavelet Analysis
keywords: Magnetic resonance imaging; particle swarm optimization; quantum-behaved PSO; wavelet energy