Automatic analysis based on image content is a hotspot with bright future of medical image diagnosis technology research. Analysis of the fracture of skull can help doctors diagnose. In this paper, a new approach is proposed to automatically detect the fracture of skull based on CT image content. First region growing method, whose seeds and growing rules are chosen by k-means clustering dynamically, is applied for image automatic segmentation. The segmented region boundary is found by boundary tracing. Then the shape of the boundary is analyzed, and the circularity measure is taken as description parameter. At last the rules for computer automatic diagnosis of the fracture of the skull are reasoned by entropy function. This method is used to analyze the images from the third ventricles below layer to cerebral cortex top layer. Experimental result shows that the recognition rate is 100% for the 100 images, which are chosen from medical image database randomly and are not included in the training examples. This method integrates color and shape feature, and isn't affected by image size and position. This research achieves high recognition rate and sets a basis for automatic analysis of brain image.