Use of marginal distributions constrained optimization (MADCO) for accelerated 2D MRI relaxometry and diffusometry.

ABSTRACT: Measuring multidimensional (e.g., 2D) relaxation spectra in NMR and MRI clinical applications is a holy grail of the porous media and biomedical MR communities. The main bottleneck is the inversion of Fredholm integrals of the first kind, an ill-conditioned problem requiring large amounts of data to stabilize a solution. We suggest a novel experimental design and processing framework to accelerate and improve the reconstruction of such 2D spectra that uses a priori information from the 1D projections of spectra, or marginal distributions. These 1D marginal distributions provide powerful constraints when 2D spectra are reconstructed, and their estimation requires an order of magnitude less data than a conventional 2D approach. This marginal distributions constrained optimization (MADCO) met

SUBMITTER: Benjamini D 

PROVIDER: S-EPMC5026962 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature