Brain imaging technology is one of the important tools for brain science studies. Brain imaging data itself has characteristics of high dimensionality, heterogeneity and time-varying. How to analyze the brain imaging data quickly and effectively is one of the key issues in current research. At the same time, the brain has a high degree of complexity in structure and function, and traditional brain image analysis methods are difficult to reveal complex and subtle patterns of brain changes caused by brain diseases or cognitive activities. New intelligent image analysis theories and methods based on machine learning and pattern recognition technology and the applications in early diagnosis of brain diseases and brain decoding can solve the above problems.