Medical image segmentation method based on combination of cloud module and image segmentation

The invention request to protect a medical image segmentation method based on the combination of a cloud module and image segmentation. The method comprises the steps of: firstly, carrying out smoothing processing on an image, and removing noise points; then utilizing reverse cloud conversion to cloud characteristic constants of an image foreground and background respectively, and utilizing an X condition cloud generator to calculate membership degrees of each pixel relative to the foreground and background; calculating data items and smooth items; then establishing an energy function to construct a corresponding network figure, and utilizing a maximum flow/minimum cut algorithm to realize medical image segmentation; and finally, judging whether a segmentation result meets iteration conditions, if yes, then outputting the result, and otherwise, calculating cloud characteristic constants of a current segmentation result foreground and background again. According to the invention, the cloud module and the image segmentation algorithm are combined, the good multi-characteristic constraint capability and the global optimality of the image segmentation method are reserved, and the fuzziness and randomness of the cloud model and nondeterminacy of the association between the cloud module and the image segmentation algorithm are introduced, so that the precision of medical image segmentation can be effectively improved.