Efficient computational fluid dynamics mesh generation by image registration.
Most implementations of computational fluid dynamics (CFD) solutions require a discretisation or meshing of the solution domain. The production from a medical image of a computationally efficient mesh representing the structures of interest can be time consuming and labour-intensive, and remains a major bottleneck in the clinical application of CFD. This paper presents a method for deriving a patient-specific mesh from a medical image. The method uses volumetric registration of a pseudo-image, produced from an idealised template mesh, with the medical image. The registration algorithm used is robust and computationally efficient. The accuracy of the new algorithm is measured in terms of the distance between a registered surface and a known surface, for image data derived from casts of the lumen of two different vessels. The true surface is identified by laser profiling. The average distance between the surface points measured by the laser profiler and the surface of the mapped mesh is better than 0.2 mm. For the images analysed, the new algorithm is shown to be 2-3 times more accurate than a standard published algorithm based on maximising normalised mutual information. Computation times are approximately 18 times faster for the new algorithm than the standard algorithm. Examples of the use of the algorithm on two clinical examples are also given. The registration methodology lends itself immediately to the construction of dynamic mesh models in which vessel wall motion is obtained directly using registration.
Barber
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DC
Department of Medical Physics, University of Sheffield, Royal Hallamshire Hospital, Sheffield, UK. D.Barber@sheffield.ac.uk
Oubel
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Frangi
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AF
Hose
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DR
D000465:Algorithms; D000818:Animals; D001011:Aorta / Q000502:physiology*; D001783:Blood Flow Velocity / Q000502:physiology; D002339:Carotid Arteries / Q000502:physiology*; D002417:Cattle; D019295:Computational Biology / Q000379:methods*; D018056:Hemorheology / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging