Probabilistic Modeling of Blood Vessels for Segmenting MRA Images

A new physically justified adaptive probabilistic model of blood vessels on magnetic resonance angiography (MRA) images is proposed. The model accounts for both laminar (for normal subjects) and turbulent blood flow (in abnormal cases like anemia or stenosis) and results in a fast algorithm for extracting a 3D cerebrovascular system from the MRA data. Experiments with real data sets confirm the high accuracy of the proposed approach

[1]  Max A. Viergever,et al.  Fast delineation and visualization of vessels in 3-D angiographic images , 2000, IEEE Transactions on Medical Imaging.

[2]  Olivier D. Faugeras,et al.  CURVES: Curve evolution for vessel segmentation , 2001, Medical Image Anal..

[3]  Anthony J. Yezzi,et al.  Vessel Segmentation Using a Shape Driven Flow , 2004, MICCAI.

[4]  Aly A. Farag,et al.  Precise segmentation of multimodal images , 2006, IEEE Transactions on Image Processing.

[5]  Demetri Terzopoulos,et al.  Medical image segmentation using topologically adaptable surfaces , 1997, CVRMed.

[6]  J. Alison Noble,et al.  An adaptive segmentation algorithm for time-of-flight MRA data , 1999, IEEE Transactions on Medical Imaging.

[7]  Wiro J. Niessen,et al.  Local Speed Functions in Level Set Based Vessel Segmentation , 2004, MICCAI.

[8]  Guillermo Sapiro,et al.  Geodesic Active Contours , 1995, International Journal of Computer Vision.

[9]  Maxime Descoteaux,et al.  Geometric Flows for Segmenting Vasculature in MRI: Theory and Validation , 2004, MICCAI.

[10]  Y. Fung,et al.  Mechanics of the Circulation , 2011, Developments in Cardiovascular Medicine.

[11]  Wu Zhong International Trends of Pattern Recognition Research A Brief Introduction to the 18th International Conference on Pattern Recognition , 2006 .

[12]  A C Dornhorst,et al.  Review of Medical Physiology. , 1966 .

[13]  J. Alison Noble,et al.  Fusing speed and phase information for vascular segmentation of phase contrast MR angiograms , 2002, Medical Image Anal..

[14]  Laurent D. Cohen,et al.  Fast extraction of tubular and tree 3D surfaces with front propagation methods , 2002, Object recognition supported by user interaction for service robots.