【摘要】 微结构成像是为了改善传统扩散磁共振成像的一些缺点而发展的一种新技术。微结构成像范式旨在建立组织结构特性与体素级磁共振信号相联系的模型,以此来估计并绘制微结构属性。目前该技术正在实现从实验室研究到临床应用研究的转变。首先介绍扩散磁共振成像并分析传统技术存在的主要问题,然后阐述微结构成像原理;随后,对受阻与受限制复合扩散模型、神经突起方向离散度与密度成像等微结构成像中常用的多隔室模型研究现状展开综述,包括模型组成、模型优化和临床应用等方面,重点在于深度学习算法应用于微结构成像参数拟合的研究现状。最后,对微结构成像技术发展趋势进行展望。更多还原

【Abstract】 Microstructure imaging is a new technology developed to improve some of the shortcomings of traditional diffusion magnetic resonance imaging. The microstructure imaging paradigm aims to estimate and map microscopic properties of tissue using a model that links these properties to the voxel scale MR signal. It is currently undergoing a transition from laboratory research to clinical applications. In this article,we first introduced the diffusion magnetic resonance imaging technology,analyzed the main problems existing and explained the principle of microstructure imaging. In the following parts, the research status of multicompartment models was reviewed such as CHARMED and NODDI,including model composition,model optimization and clinical application. The research progress of deep learning algorithm applied to microstructure imaging was reviewed as well. At last,the development trend of microstructure imaging technology was prospected.更多还原