Blood Vessel Segmentation Using Optimal Flow Based on Bayesian Selecting Scheme

Abstract:

In this paper, we present a novel method for segmentation of cerebral blood vessels form magnetic resonance angiography(MRA) images using optimal flow based on Bayesian selecting scheme algorithm. First the multi-distribution regression algorithm is applied to MIP to decrease the quantity of mixing elements. Then the probability-control selecting scheme is put forward to divide the local neighbor into brain vessels and other tissues with consistent motion vector. Finally, the optimal flow algorithm is adopted to refine the vector and get the final result. The feasibility and validity of the algorithm is verified by the experiment. With the algorithm, small branches of the brain vessels can be segmented, and the accuracy of segmentation is improved. Experimental results on head MRA dataset confirm the efficiency of the proposed approach.

• Periodical: Advanced Materials Research (Volumes 433-440)
• Pages: 5425-5430
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.433-440.5425
• Online since: January 2012
• Authors: Shi Feng Zhao, Ming Quan Zhou
• Keywords: Cerebral Blood Vessel, Optimal Flow, Segmentation

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