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We propose a novel T2 relaxation data analysis method which we have namedspectrum analysis for multiple exponentials via experimental condition orientedsimulation (SAME-ECOS). SAME-ECOS, which was developed based on a combinationof information theory and machine learning neural network algorithms, istailored for different MR experimental conditions, decomposingmulti-exponential decay data into T2 spectra, which had been considered anill-posed problem using conventional fitting algorithms, including the commonlyused non-negative least squares (NNLS) method. Our results demonstrated that,compared with NNLS, the simulation-derived SAME-ECOS model yields much morereliable T2 spectra in a dramatically shorter time, increasing the feasibilityof multi-component T2 decay analysis in clinical settings.

Introduction to a novel T2 relaxation analysis method SAME-ECOS:  Spectrum Analysis for Multiple Exponentials via Experimental Condition  Oriented Simulation