Rician noise represents the major
source of bias in parametric fitting techniques, such as the estimation of the
T2* relaxation time. This bias is particularly strong when the signal-to-noise ratio is low or T2* values are
short, such as in clinical cases of severe brain or liver iron overload.
work, we trained a deep convolutional neural network to recognize Rician noise
and compute unbiased relaxation parameters from multi-echo gradient echo data.