This files are related to implementation of the article entitled "Integrating spatial fuzzy clustering with level set methods for automated medical image segmentation".

模糊聚类分析作为无监督机器学习的主要技术之一，是用模糊理论对重要数据分析和建模的方法，建立了样本类属的不确定性描述，能比较客观地反映现实世界，它已经有效地应用在大规模数据分析、数据挖掘、矢量量化、图像分割、模式识别等领域，具有重要的理论与实际应用价值，随着应用的深入发展，模糊聚类算法的研究不断丰富-Unsupervised fuzzy clustering analysis as the main machine learning techniques is the use of fuzzy t

智能计算主要程序源码，有matlab的模糊聚类图像分割，还有VC++编写的模拟退火和遗传算法。-Intelligent Computing The main program source code, there is matlab fuzzy clustering image segmentation, as well as VC++ Prepared simulated annealing and genetic algorithms.

In this post, we are going to share with you, the MATLAB implementation of Color Quantization and Color Reduction of images, using intelligent clustering approaches: (a) k-Means Algorithm, (b) Fuzzy c-Means Clustering (FCM), and (c) Self-Organizing M