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Brain tumor segmentation algorithm based on multi-kernelcollaborative representation classificationGe Ting1,2,Zhan(PDF)


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Brain tumor segmentation algorithm based on multi-kernelcollaborative representation classificationGe Ting1,2,Zhan
Tianming3Mu Shanxiang1
1.School of Electronic and Optical Engineering,Nanjing University of Science and Technology,Nanjing 210094,China; 2.School of Science,Jinling Institute of Technology,Nanjing 211169,China; 3.School of Information Engineering,Nanjing Audit University,Nanjing 211815,China
magnetic resonance images brain tumors image segmentation superpixel multi-scales multi-kernel collaborative representation classification
In order to segment brain tumor regions from brain magnetic resonance(MR)image and provide reference for subsequent disease diagnosis and surgical navigation,a brain tumor segmentation algorithm is proposed based on the multi-kernel collaborative representation classification under the framework of kernel method. Firstly,multi-scale superpixel segmentations of brain tumor images are carried out and the spatial features based on superpixel regions are constructed. Then the original spectral information and the extracted multi-scale spatial features are fused by using the multi-kernel collaborative representation classification method under the multiple kernel frame work. Finally,the segmentation of brain tumor regions is realized in combination with clinical features. Test results on the data sets of MICCAI BraTS 2012 and 2013 show that,compared with the existing brain tumor segmentation algorithms,the proposed method can extract brain tumor regions better and has better segmentation accuracy.


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Last Update: 2019-11-30