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Traditional fuzzy C-means clustering (FCM) algorithm has the problem of large amount of calculation and too long operation time in medical image segmentation. In the case that sample set is not ideal, it can lead to bad clustering results. Against disadvantages of this algorithm, a kind of medical segmentation algorithm is put forward based on hybrid leapfrog optimized fuzzy c-means clustering. The...
The study is based on the principles of mathematical morphology and the features of tumor cell image about unclearness and uncertainty. It adopts fast median filtering in spatial domain and classification method of statistical pattern recognition to process the image segmentation of cell images. To describe the objects to be recognized, it extracts the features and adopts neural network theory for...
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