Real-time prediction and gating of respiratory motion using an extended Kalman filter and Gaussian process regression

Physics in Medicine and Biology

Volumn 60, Issue 1, 2015, Pages 233-252

  Bukhari, W ^a   Hong, S M ^a  

^a Kyungpook National University   (South Korea)

Author keywords

Gating; Gaussian process regression; Kalman filter; Motion prediction; Respiratory motion

Indexed keywords

APPROXIMATION ALGORITHMS; EXPERIMENTS; FORECASTING; GAUSSIAN BEAMS; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); KALMAN FILTERS; REGRESSION ANALYSIS; RESPIRATORY MECHANICS; TUMORS;

ADAPTIVE RADIOTHERAPY; GATING; GAUSSIAN PROCESS REGRESSION; MOTION PREDICTION; NON-PARAMETRIC BAYESIAN; NUMERICAL EXPERIMENTS; RESPIRATORY MOTIONS; SPARSE APPROXIMATIONS;

EXTENDED KALMAN FILTERS;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; BAYES THEOREM; BREATHING; BREATHING MECHANICS; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED RADIOTHERAPY; HUMAN; MOVEMENT (PHYSIOLOGY); NEOPLASMS; NORMAL DISTRIBUTION; PATHOPHYSIOLOGY; PROCEDURES; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINE; THEORETICAL MODEL;

ALGORITHMS; BAYES THEOREM; HUMANS; MODELS, THEORETICAL; MOVEMENT; NEOPLASMS; NEURAL NETWORKS (COMPUTER); NORMAL DISTRIBUTION; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; RADIOTHERAPY, COMPUTER-ASSISTED; REGRESSION ANALYSIS; RESPIRATION; RESPIRATORY MECHANICS; SUPPORT VECTOR MACHINE;

EID: 84918536918     PISSN: 00319155     EISSN: 13616560     Source Type: Journal    
DOI: 10.1088/0031-9155/60/1/233     Document Type: Article

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