4D flow magnetic resonance imaging (MRI) can provide a way to analyze both the anatomical and hemodynamic properties related to complex vessel networks. Using basic principles related to flow conservation the entire vessel networks data can be used to help improve local flow calculations. A Bayesian approach is utilized with a Markov Chain Monte Carlo where flow conservation is enforced to obtain, for a complete vascular network, estimates of mean flow and flow uncertainty. The estimated data results in a lower flow uncertainty overall and can allow for localization of potential erroneous branches in the initial data.
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