Oscar Gustafsson1,2, Mikael Montelius1, Göran Starck1,2, and Maria Ljungberg1,2
1Department of Radiation Physics, Institute of Clinical Sciences, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, 2Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
Bayesian
model fitting has been proposed as an alternative to the commonly used least
squares fitting of the IVIM model. In this work we used Monte Carlo simulations
to study the convergence of a Markov Chain Monte Carlo implementation of
Bayesian model fitting and compared the resulting model parameters to two least
squares model fitting methods. We saw
that the convergence of the Bayesian model fitting procedure was affected by
noise and compartment sizes. Bayesian model fitting was beneficial for the diffusion coefficient and the perfusion fraction, especially at low SNR
