Regional difference is the kernel guidance in the area of image segmentation. In this paper, we present a novel region- based active contour model that could be applied to detect the contour of both nucleolus and cell membrane from the background. Both local and global intensity information are used as the driving forces of the active contour model on the principle of maximum regional difference. The local and global fitting forces ensure that local dissimilarities could be captured and global different areas could be segmented respectively. By combining the advantages of local and global information, the motion of contour is driven by the mixed fitting force, which is composed of the local and global fitting term in energy functional. A strategic weight parameter using the gradient information is introduced to explain how the local and global fitting terms work together as the mixed fitting force. Experimental results show desirable performances of our model in segmenting nucleolus.