1. A method for tracking a tumor, comprising for each pair of current images in sequences of bi-plane images: generating a set, of segmentation hypotheses using a 3D model of the tumor, a bi-plane geometry, and a previous location of the tumor as determined from each pairs of biplane images; constructing volume prior probabilities based on the set of hypotheses; selecting seed pixels in the pair of current images using the volume prior probabilities; constructing a bi-plane dual image graph using intensity values and the seed pixels; and obtaining segmentation masks corresponding to tumor boundaries using image intensities to determine a current location of the tumor, wherein the steps performed in a processor.