A method for estimating tissue parameters using cardiovascular MRI and biophysical model by combining neural network (NN) and numerical optimization (NO) is illustrated on estimating $$$T_1$$$ relaxation time from MOLLI. Compared to the estimation obtained from MOLLI by the scanner, the proposed method provided $$$T_1$$$ closer to turbo spin-echo pseudo-ground in 7 out of 8 phantoms and higher or comparable myocardial and blood $$$T_1$$$ in 6 out of 7 patiens’ datasets. Including the NN-based initial guess accelerated the subsequent NO. NO initialized by NN, trained using simulated data, showed the potential to increase the efficiency and robustness of parameter estimation.
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