Maximum-likelihood estimation of Rician distribution parameters
Jan Sijbers, Arnold Jan den Dekker, Paul Scheunders, Dirk Van Dyck · IEEE Transactions on Medical Imaging · 1998
The problem of parameter estimation from Rician distributed data (e.g., magnitude magnetic resonance images) is addressed. The properties of conventional estimation methods are discussed and compared to maximum-likelihood (ML) estimation which is known to yield optimal results asymptotically. In contrast to previously proposed methods, ML estimation is demonstrated to be unbiased for high signal-to-noise ratio (SNR) and to yield physical relevant results for low SNR.