  We propose a novel T2 relaxation data analysis method which we have named
spectrum analysis for multiple exponentials via experimental condition oriented
simulation (SAME-ECOS). SAME-ECOS, which was developed based on a combination
of information theory and machine learning neural network algorithms, is
tailored for different MR experimental conditions, decomposing
multi-exponential decay data into T2 spectra, which had been considered an
ill-posed problem using conventional fitting algorithms, including the commonly
used non-negative least squares (NNLS) method. Our results demonstrated that,
compared with NNLS, the simulation-derived SAME-ECOS model yields much more
reliable T2 spectra in a dramatically shorter time, increasing the feasibility
of multi-component T2 decay analysis in clinical settings.
