摘要
This paper investigates a reconstruction method for helical computed tomography which compensates for the motion artifacts in the thorax caused by patient breathing. The method takes into account a motion vector field determined from a four-dimensional （4-D） uncompensated image data set. Surface models of the lung and the ribs are tracked through the 4-D data set to create motion information within the entire thorax. Finally, an image is reconstructed using motion compensated back-projection. The results show that due to the use of shape models for the motion estimation, the method is fast and robust. Furthermore, since the surfaces are tracked individually, reconciling the opposite motion direction of the lung and rib cage in one motion vector field is avoided.
This paper investigates a reconstruction method for helical computed tomography which compensates for the motion artifacts in the thorax caused by patient breathing. The method takes into account a motion vector field determined from a four-dimensional （4-D） uncompensated image data set. Surface models of the lung and the ribs are tracked through the 4-D data set to create motion information within the entire thorax. Finally, an image is reconstructed using motion compensated back-projection. The results show that due to the use of shape models for the motion estimation, the method is fast and robust. Furthermore, since the surfaces are tracked individually, reconciling the opposite motion direction of the lung and rib cage in one motion vector field is avoided.
