Conventional Magnetic Resonance Imaging (MRI) is hampered by long scan times and only qualitative image contrasts that prohibit a direct comparison between different systems. To address these limitations, model-based reconstructions explicitly model the physical laws that govern the MRI signal generation. By formulating image reconstruction as an inverse problem, quantitative maps of the underlying physical parameters can then be extracted directly from efficiently acquired k-space signals without intermediate image reconstruction -- addressing both shortcomings of conventional MRI at the same time. This review will discuss basic concepts of model-based reconstructions and report about our experience in developing several model-based methods over the last decade using selected examples that are provided complete with data and code.
翻译:常规磁共振成像(MRI)受到长扫描时间的阻碍,只有定性图像对比才能禁止对不同系统进行直接比较。为解决这些局限性,基于模型的重建明确模拟管理MRI信号生成的物理法律。通过将图像重建作为反向问题进行设计,然后可以直接从有效获得的K-空间信号中提取基本物理参数的定量地图,而不进行中间图像重建,同时解决常规的MRI的缺陷。本审查将讨论基于模型的重建的基本概念,并报告我们在过去十年中利用一些附有数据和代码的选定实例制定若干基于模型的方法的经验。