本项目研究面向大数据的快速磁共振成像。针对目前磁共振成像存在的成像时间和成像质量之间的矛盾，本项目拟以磁共振图像的快速成像为中心，围绕K-空间数据获取、高分辨率磁共振图像重建、模型快速算法设计、相关模型和算法理论四方面开展研究。项目从磁共振装置软硬件、磁共振成像算法、磁共振影像在医学中的应用三个角度出发，改进华东师范大学上海市磁共振重点实验室已有的自研磁共振成像系统，设计新型K-空间数据的获取方式；并充分利用磁共振重点实验室和上海交通大学附属第六人民医院积累的海量磁共振数据，结合稀疏优化和深度学习，构造快速求解模型，实现高分辨率磁共振图像的重建；项目还将研究相关方法的理论基础，并积极拓展快速成像的应用范围。预期项目研究的新理论、新模型、新算法和新应用将为磁共振快速成像的发展做出重大贡献。

This project will study the big data oriented fast magnetic resonance (MR) imaging. Facing on the trade-off between imaging time and quality, our project will focus on fast imaging for MR images by studying the following four aspects, i.e., the data acquisition from K-space, the high resolution MR image reconstruction, fast algorithm for reconstruction, and relevant models and theories. This project will start from three points, i.e., the hardware and software of the MR equipment, MR imaging algorithms and the applications in medical diagnosis. Its goal is 1) improving the MR system developed by Shanghai Key Laboratory of Magnetic Resonance (SKLMR) in East China Normal University; 2) designing novel acquisition scheme in K-space; and 3) reconstructing fast super resolution model by sparse optimization and deep learning, using the big data from SKLMR and Shanghai Sixth People's Hospital affiliated by Shanghai Jiaotong University. Related theories and the new fields of application for fast imaging will also be explored. It is expected that the new theory, model, algorithm and applications from this project will make an important contribution in the field of MR imaging.