4D Motion Modeling: Estimation of Respiratory Motion for Radiation Therapy

With 4D imaging techniques spatiotemporal image sequences can be acquired to investigate dynamic processes in the patient's body. However, 4-D images are not sufficient in themselves for motion measurement. Therefore, motion estimation algorithms have gained in importance in the last years. In this paper, the increasing role of image registration and motion estimation algorithms for the interpretation of complex 4D medical image sequences is illustrated. Two conceptually different motion estimation algorithms are presented and the clinical relevance is demonstrated by means of two example applications which are related to the radiation therapy of thoracic and abdominal tumors. Perspectives are shown by an insight into a current field of research: the statistical motion modeling.