We propose a novel T2 relaxation data analysis method called spectrum analysis for multiple exponentials via experimental condition oriented simulation (SAME-ECOS), which was developed based on a combination of information theory and deep learning neural network algorithms. SAME-ECOS is tailored for different MR experimental conditions to decompose the multi-exponential decay data into a T2 spectrum, which has been considered an ill-posed problem using conventional fitting algorithms including the commonly used non-negative least squares (NNLS). Our results demonstrated that, compared with NNLS, SAME-ECOS can yield much more reliable T2 spectra in a dramatically shorter time.
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