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Proceedings Paper

Determination of 3D flow velocity distributions from single-plane angiographic sequences
Author(s): Kenneth R. Hoffmann; Todd Dorazio; Joseph Lee; Jae-Hun Jung; E. Bruce Pitman; Alan Walczak; Xinjuan Chen
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Paper Abstract

Understanding 3D flow-velocity fields may be valuable during interventional procedures. Thus, we are developing methods to calculate 3D flow fields from single-plane angiographic sequences. The vessel geometry is selected. Flow fields are generated based on laminar flow conditions. X-ray-attenuating contrast is propagated through the vessel using the flow fields. Angiograms are generated at 30 frames/second using ray-casting. Vessel profile data are extracted from the angiograms along lines perpendicular to the vessel axis. The conversion from image intensity to contrast pathlength is determined. The contrast pathlength is calculated for each vessel-profile point, and the contrast is centered about the vessel's central plane generating a 3D contrast distribution. This procedure is repeated for each acquired angiogram. Corresponding points on the surface of the calculated contrast distributions are established for temporally adjacent distributions using estimated streamlines. Distances between corresponding points are calculated from which average velocities are calculated. These average velocities are placed at points along the streamlines, thereby generating a 3D velocity flow field in the vessel lumen. Simulations for steady flow conditions for straight vessels, curved (in-plane) vessels, and vessels with stenoses, for noiseless and noisy (10% peak contrast) angiograms were performed. The calculated and simulated 3D contrast distributions agree well for both noiseless and noisy conditions (errors < 2 voxels ~ 0.2 mm). Average absolute error of the calculated 3D flow velocities is approximately 10%. These promising initial results indicate that this technique may form the basis for calculating 3D-contrast and 3D-flow-velocity distributions from standard single-plane angiographic sequences.

Paper Details

Date Published: 16 March 2011
PDF: 10 pages
Proc. SPIE 7961, Medical Imaging 2011: Physics of Medical Imaging, 79613S (16 March 2011); doi: 10.1117/12.877792
Show Author Affiliations
Kenneth R. Hoffmann, Univ. at Buffalo (United States)
Imagination Software Corp. (United States)
Todd Dorazio, Univ. at Buffalo (United States)
Joseph Lee, Univ. at Buffalo (United States)
Jae-Hun Jung, Univ. at Buffalo (United States)
E. Bruce Pitman, Univ. at Buffalo (United States)
Alan Walczak, Univ. at Buffalo (United States)
Imagination Software Corp. (United States)
Xinjuan Chen, Univ. at Buffalo (United States)


Published in SPIE Proceedings Vol. 7961:
Medical Imaging 2011: Physics of Medical Imaging
Norbert J. Pelc; Ehsan Samei; Robert M. Nishikawa, Editor(s)

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