A respiration correction method for real-time ultrasound image fusion with pre-acquired 3D dataset

Ultrasound image fusion has been widely used in interventional surgeries, providing surgeons both detailed structural information via CT/MRI and real-time ultrasound information. However, patient respiration induced quasi-periodic organ motion usually leads to unacceptable registration and fusion errors. In this paper, we propose a method to build a patient specific respiratory motion model and make respiration displacement correction accordingly. An additional EM body sensor is introduced to provide respiration information. Block matching and least mean square approaches are applied on a training ultrasound sequence to build patient specific respiratory model. Displacement correction can then be carried out in real time with this model and the EM body sensor´s position. Preliminary test shows that this method can effectively reduce the respiration-induced registration error.