Abstract
The brain MRI images are processed with statistical analysis technology, and then the accuracy of segmentation is improved by the random assortment iteration .First the MIP algorithm is applied to decrease the quantity of mixing elements. Then the Gaussian Mixture Model is put forward to fit the stochastic distribution of the brain vessels and brain tissue. Finally, the SEM algorithm is adopted to estimate the parameters of Gaussian Mixture Model. The feasibility and validity of the model is verified by the experiment. With the model, small branches of the brain vessel can be segmented, the speed of the convergent is improved and local minima are avoided.
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Wang, X., Xu, F., Zhou, M., Wu, Z., Liu, X. (2010). The SEM Statistical Mixture Model of Segmentation Algorithm of Brain Vessel Image. In: Li, K., Jia, L., Sun, X., Fei, M., Irwin, G.W. (eds) Life System Modeling and Intelligent Computing. ICSEE LSMS 2010 2010. Lecture Notes in Computer Science(), vol 6330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15615-1_24
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DOI: https://doi.org/10.1007/978-3-642-15615-1_24
Publisher Name: Springer, Berlin, Heidelberg
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