Anzeige
Erschienen in:
2018 | OriginalPaper | Buchkapitel
Comparison of Divergence-Free Filters for Cardiac 4D PC-MRI Data
verfasst von : Mickäel Francisco Sereno, Benjamin Köhler, Bernhard Preim
Erschienen in: Bildverarbeitung für die Medizin 2018
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
4D PC-MRI enables the measurement of time-resolved blood flow directions within a 3D volume. These data facilitate a comprehensive qualitative and quantitative analysis. However, noise is introduced, e.g., due to inhomogeneous magnetic field gradients. Blood is commonly assumed as a non-Newtonian fluid, thus, incompressible, and divergence should be zero. Divergence-free filters enforce this model assumption and have been shown to improve data quality. In this paper, we compare binomial smoothing and three of these techniques: The finite difference method (FDM), divergence-free radial basis functions (DFRBF) and divergence-free wavelets (DFW). The results show that average and maximum velocities tend to decrease, while average line lengths tend to increase slightly. We recommend FDM or DFW divergence-free filtering as an optional pre-processing step in 4D PC-MRI processing pipelines, as they have feasible computation times of few seconds.