Background: In cardiac T mapping, a series of T -weighted (T w) images are collected and numerically fitted to a two or three-parameter model of the signal recovery to estimate voxel-wise T values. To reduce the scan time, one can collect fewer T w images, albeit at the cost of precision or/and accuracy. Recently, the feasibility of using a neural network instead of conventional two- or three-parameter fit modeling has been demonstrated.
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