3 July 2001 Knowledge-based extraction of cerebral vasculature from anatomical MRI
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Abstract
A vessel extraction approach is presented that permits visualization of the cerebral vasculature in 3D from anatomical proton density (PD) weighted magnetic resonance imaging (MRI) volumes. The approach presented utilizes general knowledge about the shape and size of the cerebral vasculature and is divided into multi-scale vessel enhancement filtering, centre-line extraction, and surface modeling. To improve the discrimination between blood vessels and other tissue a multi-scale filtering method that enhances tubular structures is used as a pre-processing step. Centre-line extraction is applied to roughly estimate the centre-line of the vasculature involving both segmentation and skeletonization. The centre-line is used to initialize an active contour modeling process where cylinders are used to model the 3D surface of the blood vessels. The accuracy and robustness of the vessel extraction approach have been demonstrated on both simulated and real data (1mm3 voxels). On simulated data, the mean error of the estimated radii was found to be less than 0.4mm. On real data, the vasculature was successfully extracted from 20 MRI data sets using the same input parameters. An expert found the extracted vessel surfaces to coincide with the vessel walls in the data. Results from CTA data indicate that the approach will work successfully with other imaging modalities as well.
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Lasse Riis Oestergaard, Lasse Riis Oestergaard, Ole Vilhelm Larsen, Ole Vilhelm Larsen, Jens Haase, Jens Haase, Frederick Van Meer, Frederick Van Meer, Alan C. Evans, Alan C. Evans, D. Louis Collins, D. Louis Collins, } "Knowledge-based extraction of cerebral vasculature from anatomical MRI", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); doi: 10.1117/12.431061; https://doi.org/10.1117/12.431061
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