Data inversion of multi-dimensional magnetic resonance in porous media  

作　　者：Fangrong Zong Huabing Liu Ruiliang Bai Petrik Galvosas 

机构地区：[1]Schoolof Artificial Intelligence,Beijing University of Post and Telecommunication,Beijing,100876,China [2]Beijing Limecho Technology Co,Ltd.Beijing,102200,China [3]Interdisciplinary Institute of Neuroscience and Technology,Zhejiang University School of Medicine,Hangzhou,310020,China [4]MOE Frontier Science Centerfor Brain Science and Brain-machine Integration,School of Brain Science and Brain Medicine,Zhejiang University,Hangzhou,310030,China [5]School of Chemical and Physical Sciences,Victoria University of Wellington,Wellington,6140,New Zealand [6]MacDiarmid Institute for Advanced Materials,Victoria University of Wellington,Wellington,6140,New Zealand

出　　处：《Magnetic Resonance Letters》2023年第2期127-139,I0004,共14页磁共振快报（英文）

基　　金：supported by the National Natural Science Foundation of China(No.61901465,82222032,82172050).

摘　　要：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.

关 键 词：Multi-dimensional MR Data inversion Porous media Inverse Laplace transform FOURIERTRANSFORM 

分 类 号：O482.532[理学—固体物理]