Journal Article

Gender identification based on human brain structural MRI with a multi-layer 3D convolution extreme learning machine

Luo, Zhiguo, Hu, Dewen, Zhao, Longfei

2019

Overview

Previous group-level neuroimaging studies have shown significant gender differences in the human brain. Research on sex-specific brain differences in healthy individuals is an important base for understanding sex-specific expression in psychiatric disorders. This study proposes a multi-layer 3D convolution extreme learning machine (MCN-ELM) to classify male and female brains based on structural MRI (sMRI) grey matter (GM) data scans from human connectome projects (HCP) of 876 healthy adults (491 females). First, the authors extracted multi-scale features by three-scale multi-layer 3D convolution neural networks (CNNs) without fine-tuning the parameters of convolution kernels. Then, they pulled the network output feature maps into a vector as separate ELMs. By voting on the three-scale networks, the MCN-ELM algorithm classifies male and female brains with an accuracy of 98.06% through a 10-fold cross-validation strategy, outperforming other state-of-the-art algorithms. The proposed method may be used to understand other brain diseases. Additionally, the results show that the human brain can be categorised into two distinct classes, male and female brains, suggesting it is better to treat men and women separately when researching psychiatric disorders.

• Publisher: The Institution of Engineering and Technology,John Wiley & Sons, Inc,Wiley
• Subject: Algorithms / biomedical MRI / brain / brain diseases / Brain mapping / Brain research / Classification / convolutional neural nets / Deep learning / diseases / feature extraction / female brains / Females / Gender / Gender differences / gender issues / HCP / human brain / human connectome projects / image classification / Learning algorithms / Magnetic resonance imaging / male brains / Males / MCN‐ELM algorithm / medical disorders / medical image processing / Medical imaging / Mental disorders / multilayer 3D convolution extreme learning machine / multilayer 3D convolution neural networks / Neural networks / Neuroimaging / neuroimaging studies / neurophysiology / psychiatric disorders / psychology / Research Article / Sex differences / sex-specific brain differences / sMRI / structural MRI grey matter / Substantia grisea / Support vector machines / Women