Medical Image Segmentation Based on Fuzzy Region Growth
According to the characteristics of lung image,a region growing image segmentation method based on fuzzy mem-bership degree is proposed in this paper.First of all,the original image is preprocessed and binarized.Secondly,the contours of dif-ferent regions are determined according to the binary image,and the centroids of different regions are calculated.Thirdly,according to the labeled image,the centroid of the target region is automatically obtained as the seed point of the region growth.Finally,the membership function is used to calculate the membership degree of the seed point adjacent to the pixel point,and the region growth is carried out according to its membership degree.The experimental results show that,compared with the traditional region growing method,the proposed method can alleviate the phenomenon of over-segmentation or under-segmentation,the segmentation accura-cy is 21.88%higher than the traditional method,and the target area can be segmented more clearly.It provides help for future clini-cal diagnosis.
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