Automatic analysis based on image content is a hotspot with bright future of medical image diagnosis technology research. Analysis of the want of skull can help doctor to diagnose. In this paper

a new method is proposed to automatic detect the want of skull based on CT image content. Region growing method

which 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. The shape of the boundary is analyzed

and the circularity is taken as description parameter. Then

the rules for computer automatic diagnosis of the want of 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

those are chosen from medical image database randomly and are not included in the training examples. This method integrates gray 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.