Title :
A Flow Quantification Method Using Fluid Dynamics Regularization and MR Tagging
Author :
Jiraraksopakun, Yuttapong ; McDougall, Mary P. ; Wright, Steven M. ; Ji, Jim X.
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX, USA
fDate :
6/1/2010 12:00:00 AM
Abstract :
This paper presents a new method for improved flow analysis and quantification using MRI. The method incorporates fluid dynamics to regularize the flow quantification from tagged MR images. Specifically, the flow quantification is formulated as a minimization problem based on the following: 1) the Navier-Stokes equation governing the fluid dynamics; 2) the flow continuity equation and boundary conditions; and 3) the data consistency constraint. The minimization is carried out using a genetic algorithm. This method is tested using both computer simulations and MR flow experiments. The results are evaluated using flow vector fields from the computational fluid dynamics software package as a reference, which show that the new method can achieve more realistic and accurate flow quantifications than the conventional method.
Keywords :
Navier-Stokes equations; biological fluid dynamics; biomedical MRI; computational fluid dynamics; genetic algorithms; minimisation; motion estimation; MR tagging; MRI; Navier-Stokes equation; computational fluid dynamics; flow continuity; flow quantification; flow vector fields; fluid dynamics regularization; genetic algorithm; minimization; MR flow quantification; MR tagging; MRI; Motion estimation; Algorithms; Blood Flow Velocity; Blood Vessels; Computer Simulation; Humans; Image Interpretation, Computer-Assisted; Magnetic Resonance Angiography; Models, Cardiovascular; Phantoms, Imaging; Reproducibility of Results; Rheology; Sensitivity and Specificity; Spin Labels;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2009.2038229