Computer Science ›› 2014, Vol. 41 ›› Issue (7): 322-325.doi: 10.11896/j.issn.1002-137X.2014.07.067

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Brain Image Segmentation Method Based on FCM and Random Walk

GUO Peng-fei,LIU Wan-jun,LIN Lin,ZHAO Yong-gang and MIN Liang   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Random walk algorithm only considers the gray similarity of adjacent pixels,ignores neighboring pixels gra-dient information.This suppresses random walker walking to the seed point along some edges of similar gray to seed point,resulting in misclassification and missing points.This paper presented a segmentation method of brain image.It extracts image gradient information by using wavelet transform,and puts the gradient information into the edge weight.Finally using improved FCM algorithm,combining with the pixel neighborhood information,we obtained a final split brain image.Experimental results show that this method improves segmentation correct rate and the edge of the segmented image is smoother.

Key words: Random walk,Fuzzy C means,Image segmentation,Gradient information

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