A hybrid Convolutional and Recurrent Neural Network for Hippocampus Analysis in Alzheimer's Disease.

Journal: Journal of neuroscience methods
Published Date:

Abstract

BACKGROUND: Hippocampus is one of the first structures affected by neurodegenerative diseases such as Alzheimer's disease (AD) and mild cognitive impairment (MCI). Hippocampal atrophy can be evaluated in terms of hippocampal volumes and shapes using structural MR images. However, the shape and volume features from hippocampus mask have limited discriminative information for AD diagnosis. In addition, extraction of these features is independent of classification model, resulting to sub-optimal performance for disease diagnosis.

Authors

  • Fan Li
    Department of Instrument Science and Engineering, School of SEIEE, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Manhua Liu
    Department of Instrument Science and Engineering, School of EIEE, Shanghai Jiao Tong University, Shanghai, 200240, China; Shanghai Engineering Research Center for Intelligent Diagnosis and Treatment Instrument, Shanghai Jiao Tong University, Shanghai, 200240, China. Electronic address: mhliu@sjtu.edu.cn.