Application of local GAC model for medical image segmentation
局部GAC模型在医学图像分割中的应用

The geodesic active contour (GAC) model based on regions is not applicable to images with intensity inhomogeneity. In this paper,we propose a new model of the GAC based on local regions. Information of the local mean is used to overcome the intensity inhomogeneity effect of the segmentation result. A local signed pressure force function is constructed so that the contour shrinks when outside of the object, or expands when inside of the object. In order to improve the algorithm's effectively and steadily, the model is implemented by a binary level set function. Experimental results with medical images show that the new model can get the better results in a more efficient way.