CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Muliscale Vessel Enhancement Filtering
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
A review of vessel extraction techniques and algorithms
ACM Computing Surveys (CSUR)
A Non-Local Algorithm for Image Denoising
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A Novel 3D Joint Markov-Gibbs Model for Extracting Blood Vessels from PC---MRA Images
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Segmentation and Quantification of Human Vessels Using a 3-D Cylindrical Intensity Model
IEEE Transactions on Image Processing
Minimization of Region-Scalable Fitting Energy for Image Segmentation
IEEE Transactions on Image Processing
A flexible 3D cerebrovascular extraction from TOF-MRA images
Neurocomputing
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In order to solve the complex problems of segmenting cerebral vessels with many branches, small shape, special position and various patterns, a novel approach based on markov random field (MRF) and particle swarm optimization algorithm (PSO) is proposed in this paper to accurately segment cerebral vessels. Firstly, an improved nonlocal means filtering is used to reduce the interference of correlated noise. Then a new finite mixture model (FMM) - two Gaussian distribution and one Rayleigh distribution is used to fit the intensity histogram of brain tissues. Moreover, the MRF is constructed and fused with the PSO to obtain the optimal parameters of FMM. The experimental results verified the high accuracy on cerebrovascular segmentation especially for those small vessels, and relative high robustness and generalization comparing with the classical methods. The method can be widely applied in the clinical prevention and diagnosis of cerebrovascular diseases.