The stabilisation of motion on the beating heart is investigated in the context of minimally invasive robotic surgery. Although reduced by mechanical stabilisers, residual tissue motion makes safe surgery still difficult and time consuming. Compensation for this movement is therefore highly desirable. Motion can be captured by tracking natural landmarks on the heart surface recorded by a video endoscope. Stabilisation is achieved by transforming the images using a motion field calculated from captured local motion. Since the surface of the beating heart is distorted nonlinearly, compensating the occurring motion with a constant image correction factor is not sufficient. Therefore, heart motion is captured by several landmarks, the motion between which is interpolated such that locally appropriate motion correction values are obtained. To estimate the motion between the landmark positions, a triangulation is built and motion information in each triangle is approximated by linear interpolation. Motion compensation is evaluated by calculating the optical flow remaining in the stabilised images. The proposed linear interpolation model is able to reduce motion significantly and can also be implemented efficiently to stabilise images of the beating heart in realtime.
Local motion on the beating heart is investigated in the context of minimally invasive robotic surgery. The focus lies on the motion remaining in the mechanically stabilised field of surgery of the heart. Motion is detected by tracking natural landmarks on the heart surface in 2D video images. An appropriate motion model is presented with a discussion of its degrees of freedom and a trajectory analysis of its parameters.