Multimodal learning using convolution neural network and Sparse Autoencoder

• Published in: International Conference on Big Data and Smart Computing pp. 309 - 312
• Main Authors: Vu, Tien Duong, Yang, Hyung-Jeong, Nguyen, Van Quan, Oh, A-Ran, Kim, Mi-Sun
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.02.2017
• Subjects: Alzheimer's disease; autoencoder; Biological neural networks; Convolution; convolutional neural network; deep learning; Feature extraction; Magnetic resonance imaging; MRI; PET; Positron emission tomography; Support vector machines; Three-dimensional displays

In the last decade, pattern recognition methods using neuroimaging data for the diagnosis of Alzheimer's disease (AD) have been the subject of extensive research. Deep learning has recently been a great interest in AD classification. Previous works had done almost on single modality dataset, su...