Since its inception in the 1970s,multi-dimensional magnetic resonance(MR)has emerged as a powerful tool for non-invasive investigations of structures and molecular interactions.MR spectroscopy beyond one dimension all...Since its inception in the 1970s,multi-dimensional magnetic resonance(MR)has emerged as a powerful tool for non-invasive investigations of structures and molecular interactions.MR spectroscopy beyond one dimension allows the study of the correlation,exchange processes,and separation of overlapping spectral information.The multi-dimensional concept has been re-implemented over the last two decades to explore molecular motion and spin dynamics in porous media.Apart from Fourier transform,methods have been developed for processing the multi-dimensional time-domain data,identifying the fluid components,and estimating pore surface permeability via joint relaxation and diffusion spectra.Through the resolution of spectroscopic signals with spatial encoding gradients,multi-dimensional MR imaging has been widely used to investigate the microscopic environment of living tissues and distinguish diseases.Signals in each voxel are usually expressed as multi-exponential decay,representing microstructures or environments along multiple pore scales.The separation of contributions from different environments is a common ill-posed problem,which can be resolved numerically.Moreover,the inversion methods and experimental parameters determine the resolution of multi-dimensional spectra.This paper reviews the algorithms that have been proposed to process multidimensional MR datasets in different scenarios.Detailed information at the microscopic level,such as tissue components,fluid types and food structures in multi-disciplinary sciences,could be revealed through multi-dimensional MR.展开更多
为了解决全球定位系统(Global position system,GPS)微弱信号的快速捕获问题,在基于快速傅里叶变换(Fourier transform,FFT)捕获方法的基础上,改进过去的相干积分或非相干积分,提出了一种新的改进微弱信号捕获算法,采用批处理方式提高...为了解决全球定位系统(Global position system,GPS)微弱信号的快速捕获问题,在基于快速傅里叶变换(Fourier transform,FFT)捕获方法的基础上,改进过去的相干积分或非相干积分,提出了一种新的改进微弱信号捕获算法,采用批处理方式提高捕获增益,并运用多普勒补偿,提高信号累加时间容限,进一步提高信号捕获灵敏度。仿真测试表明,该方法较传统的FFT算法,提高了捕获概率,最后在FPGA上具体实现了该方案。展开更多
基金supported by the National Natural Science Foundation of China(No.61901465,82222032,82172050).
文摘Since its inception in the 1970s,multi-dimensional magnetic resonance(MR)has emerged as a powerful tool for non-invasive investigations of structures and molecular interactions.MR spectroscopy beyond one dimension allows the study of the correlation,exchange processes,and separation of overlapping spectral information.The multi-dimensional concept has been re-implemented over the last two decades to explore molecular motion and spin dynamics in porous media.Apart from Fourier transform,methods have been developed for processing the multi-dimensional time-domain data,identifying the fluid components,and estimating pore surface permeability via joint relaxation and diffusion spectra.Through the resolution of spectroscopic signals with spatial encoding gradients,multi-dimensional MR imaging has been widely used to investigate the microscopic environment of living tissues and distinguish diseases.Signals in each voxel are usually expressed as multi-exponential decay,representing microstructures or environments along multiple pore scales.The separation of contributions from different environments is a common ill-posed problem,which can be resolved numerically.Moreover,the inversion methods and experimental parameters determine the resolution of multi-dimensional spectra.This paper reviews the algorithms that have been proposed to process multidimensional MR datasets in different scenarios.Detailed information at the microscopic level,such as tissue components,fluid types and food structures in multi-disciplinary sciences,could be revealed through multi-dimensional MR.
文摘为了解决全球定位系统(Global position system,GPS)微弱信号的快速捕获问题,在基于快速傅里叶变换(Fourier transform,FFT)捕获方法的基础上,改进过去的相干积分或非相干积分,提出了一种新的改进微弱信号捕获算法,采用批处理方式提高捕获增益,并运用多普勒补偿,提高信号累加时间容限,进一步提高信号捕获灵敏度。仿真测试表明,该方法较传统的FFT算法,提高了捕获概率,最后在FPGA上具体实现了该方案。
