Paper
13 March 2009 Analysis and dynamic 3D visualization of cerebral blood flow combining 3D and 4D MR image sequences
Nils Daniel Forkert, Dennis Säring, Jens Fiehler, Till Illies, Dietmar Möller, Heinz Handels
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Abstract
In this paper we present a method for the dynamic visualization of cerebral blood flow. Spatio-temporal 4D magnetic resonance angiography (MRA) image datasets and 3D MRA datasets with high spatial resolution were acquired for the analysis of arteriovenous malformations (AVMs). One of the main tasks is the combination of the information of the 3D and 4D MRA image sequences. Initially, in the 3D MRA dataset the vessel system is segmented and a 3D surface model is generated. Then, temporal intensity curves are analyzed voxelwise in the 4D MRA image sequences. A curve fitting of the temporal intensity curves to a patient individual reference curve is used to extract the bolus arrival times in the 4D MRA sequences. After non-linear registration of both MRA datasets the extracted hemodynamic information is transferred to the surface model where the time points of inflow can be visualized color coded dynamically over time. The dynamic visualizations computed using the curve fitting method for the estimation of the bolus arrival times were rated superior compared to those computed using conventional approaches for bolus arrival time estimation. In summary the procedure suggested allows a dynamic visualization of the individual hemodynamic situation and better understanding during the visual evaluation of cerebral vascular diseases.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nils Daniel Forkert, Dennis Säring, Jens Fiehler, Till Illies, Dietmar Möller, and Heinz Handels "Analysis and dynamic 3D visualization of cerebral blood flow combining 3D and 4D MR image sequences", Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 726133 (13 March 2009); https://doi.org/10.1117/12.813742
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Cited by 4 scholarly publications.
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KEYWORDS
3D modeling

Visualization

Hemodynamics

3D image processing

Cerebral blood flow

Image visualization

Temporal resolution

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