title: Motion prediction using dual Kalman filter for robust beating heart tracking.
abstract: A novel prediction method for robust beating heart tracking is proposed. The dual time-varying Fourier series is used to model the heart motion. The frequency parameters and Fourier coefficients in the model are estimated respectively by using a dual Kalman filter scheme. The instantaneous frequencies of breathing and heartbeat motion are measured online from the 3D trajectory of the point of interest using an orthogonal decomposition algorithm. The proposed method is evaluated based on both the simulated signals and the real motion signals, which are measured from the videos recorded using the da Vinci surgical system.
authors.forename: Bo
authors.initials: B
authors.lastname: Yang
authors.forename: Chao
authors.initials: C
authors.lastname: Liu
authors.forename: Philippe
authors.initials: P
authors.lastname: Poignet
authors.forename: Wenfeng
authors.initials: W
authors.lastname: Zheng
authors.forename: Shan
authors.initials: S
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D005583:Fourier Analysis; D006801:Humans; D008955:Models, Cardiovascular; D009038:Motion; D009200:Myocardial Contraction / Q000502:physiology*; D019047:Phantoms, Imaging; D012119:Respiration