Brain MRI (magnetic resonance image) segmentation method based on improved fuzzy C-means clustering algorithm
An image segmentation and mean value clustering technology, which is applied in image analysis, image enhancement, image data processing, etc., can solve problems such as inability to segment brain MRI images well, achieve enhanced anti-noise, broad market prospects, overcome The effect of limitations
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[0051] In order to better understand the technical solutions of the present invention, the implementation manners of the present invention will be further described below in conjunction with the accompanying drawings.
[0052] The objective function form of the improved fuzzy C-means algorithm proposed by the present invention is as follows:
[0053]
[0054] Indicates the degree of intuitionistic fuzzy membership, ρ ki Indicates the similarity of pixels to classes. The meanings of other parameters in the formula are given in Table 1.
[0055] The specific implementation steps of the improved fuzzy C-means algorithm are as follows:
[0056] Step 1: Use the fuzzy C-means algorithm for initial classification, and obtain the membership degree matrix U 0 As the initialization result of the membership degree matrix U in the improved algorithm, and set the number of iterations t=1;
[0057] Step 2: Given the number of clusters c, the fuzzy factor m, the threshold ε for stop...
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