A tumor is tracked in sequences of bi-plane images by 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 the pairs of biplane images. Volume prior probabilities are constructed based on the set of hypotheses. Seed pixels are selected using the volume prior probabilities, and a bi-plane dual image graph is constructed using intensity gradients and the seed pixels to obtaining segmentation masks corresponding to tumor boundaries using the image intensities to determine a current location of the tumor.本發明係有關於一種追蹤雙平面影像序列中的腫瘤,產生一組使用腫瘤的3D模型、雙平面幾何及先前的位置,從該雙平面影像中決定腫瘤的分割假說。基於該組假設,建構體積先前機率。使用該體積先前機率選擇種子像素,且使用強度梯度及該種子像素建構雙平面雙影像圖形,以獲得相應於腫瘤邊界的分割遮罩,使用該影像強度,以確定該腫瘤的目前位置。100‧‧‧方法110‧‧‧輸入111‧‧‧雙平面超音波影像112‧‧‧雙平面幾何113‧‧‧腫瘤的3D模型114‧‧‧3D腫瘤位置120‧‧‧假說130‧‧‧體積先前機率131‧‧‧分割種子140‧‧‧雙平面雙影像3D圖形141‧‧‧分割遮罩142‧‧‧細化分割遮罩150‧‧‧參考影像及遮罩160‧‧‧處理器170‧‧‧粒子束171‧‧‧腫瘤
