This work compares T2 maps calculated from multi-echo spin-echo MR images using a conventional non-linear least squares (NLLS) fitting method to those constructed with a U-Net, a type of convolutional neural network. The performance of the U-Net and NLLS methods was compared in two retrospectively simulated experiments with a) reduced echo train lengths and b) decreased SNR to emulate accelerated acquisitions. The U-Net generally gave higher accuracy than NLLS fitting, with the trade-off of a modest increase of blurring of the resultant T2 maps.
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