Multi-Modal and Multi-Time Neuro-Imaging Learning for Brain Disease Analysis

Guided by the practical problems in clinical diagnosis, we propose a deep learning algorithm for neuroimaging data, and put the final research results into clinical practice. We focus on machine learning, deep learning and data mining algorithms in the field of computer vision, and carry out systematic research on the early diagnosis of brain diseases: 1) a series of feature learning algorithms are proposed to solve the problems of high specificity, large individual differences and high dimension of neuroimaging in patients with Alzheimer's disease, Parkinson's disease, Autism and other brain diseases; 2) To explore the construction of brain network and explore the internal relationship between brain function degradation and brain activation;3) based on deep learning and machine learning, the early diagnosis model of brain diseases is established to improve the accuracy of diagnosis and prediction.