Smart pathological brain detection by synthetic minority oversampling technique, extreme learning machine, and Jaya algorithm

• Published in: Multimedia tools and applications Vol. 77; no. 17; pp. 22629 - 22648
• Main Authors: Zhang, Yu-Dong, Zhao, Guihu, Sun, Junding, Wu, Xiaosheng, Wang, Zhi-Heng, Liu, Hong-Min, Govindaraj, Vishnu Varthanan, Zhan, Tianmin, Li, Jianwu
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2018; Springer Nature B.V
• Subjects: Algorithms; Brain; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Genetic algorithms; Image detection; Machine learning; Medical imaging; Multimedia Information Systems; Neural networks; Oversampling; Particle swarm optimization; Special Purpose and Application-Based Systems; Wavelet analysis; Jaya algorithm; Pathological brain detection; Extreme learning machine; Synthetic minority oversampling

Pathological brain detection is an automated computer-aided diagnosis for brain images. This study provides a novel method to achieve this goal.We first used synthetic minority oversampling to balance the dataset. Then, our system was based on three components: wavelet packet Tsallis entropy, extrem...