CAREER: Compressed Sensing Magnetic Resonance Imaging

0846514L。Ying这份职业建议书的研究目标是将压缩传感这一新的理论框架应用到磁共振成像(MRI)中，以提高其成像速度并实现实时成像。这项拟议的研究调查了将新的数学理论转化为MRI实践的各种问题，并探索了解决这些问题的各种想法。具体地说，为了满足压缩感知理论的要求，将开发新的非自适应、非傅立叶编码和采样技术，将发现新的稀疏变换来最有效地表示MR图像，并将开发高效且稳健的非线性重建算法来从稀疏采样数据中恢复图像。还将研究与现有快速MRI技术的集成，以实现最大加速。此外，拟议的研究将通过推导速度提升的理论界限并进行模拟和实验来评估性能。开发的技术将被应用于各种实际的磁共振成像问题。这项提议的教育目标是建立一个有效的教育框架，向不同的学生群体系统地传授生物医学成像方面的基本知识和新发现，并创建一个资源共享的基础设施。拟议的教育计划包括一个新的生物医学成像课程，将研究和教育与特别努力相结合的活动，以提高妇女和少数族裔在工程学中的地位，以及一个在图像重建方面传播成果和共享资源的开放平台。

0846514L. YingThe research objective of this CAREER proposal is to apply compressed sensing, a new theoretical framework, to magnetic resonance imaging (MRI) to revolutionize its imaging speed and enable real-time imaging. The proposed research investigates various issues in transforming the new mathematical theory into MRI practice and explores various ideas to address these issues. Specifically, to meet the conditions required by the compressed sensing theory, novel non-adaptive, non-Fourier encoding and sampling techniques will be developed, novel sparse transformations will be discovered to represent MR images most efficiently, and efficient and robust nonlinear reconstruction algorithms will also be developed to recover the images from sparsely sampled data. Integration with the existing fast MRI techniques for maximal acceleration will also be studied. Furthermore, the proposed research will evaluate performance by deriving theoretical bounds on speed enhancements and carrying out simulation and experiments. Applications of the developed techniques will be explored for various practical MR imaging problems. The educational objective of this proposal is to develop an effective educational framework for systematic delivery of both basic knowledge and new discoveries in biomedical imaging to a diverse body of students, and create an infrastructure for resource sharing. The proposed educational plan features a new biomedical imaging curriculum, activities to integrate research and education with special efforts to increase women and minority in engineering, and an open platform to disseminate results and share resources in image reconstruction.