Noise reduction of flow MRI measurements using a lattice Boltzmann based topology optimisation approach

Abstract

In a previous work, the feasibility of coupling magnetic resonance imaging (MRI) measurements and computational fluid dynamics (CFD) was presented, called CFD-MRI. Using a lattice Boltzmann based topology optimisation approach, the method can be described as a Navier–Stokes filter for flow MRI measurements. The main objective of this article is the analysis and quantification of CFD-MRI for its ability to reduce statistical measurement noise. For this, MRI data was analysed and used as basis for synthetic data, where noise was added to a simulation result. Thus, the noise-free data is known and a thorough analysis can be performed. The results show a very high agreement with the original data, even with high statistical noise in the input data and limited information available.