Online prediction of respiratory motion: Multidimensional processing with low-dimensional feature learning

Physics in Medicine and Biology

Volumn 55, Issue 11, 2010, Pages 3011-3025

  Ruan, Dan ^a   Keall, Paul ^a  

^a STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COVARIATES; CURSE OF DIMENSIONALITY; DIMENSION REDUCTION; DIMENSIONAL REPRESENTATION; ERROR DISTRIBUTIONS; FEATURE LEARNING; FEATURE SPACE; HIGH DIMENSIONAL DATA; IMAGE INTENSITIES; KERNEL DENSITY ESTIMATION; LEARNING DATA; LIMITED TRAINING DATA; LOWER DIMENSIONAL MANIFOLDS; LUNG TUMOR; MACHINE-LEARNING; MOTION MANAGEMENT; MOVING TARGETS; NATURAL EXTENSION; NONPARAMETRIC METHODS; ONLINE PREDICTION; PREDICTION METHODS; PREDICTION PERFORMANCE; PREDICTION SCHEMES; RANDOM NOISE; REAL-TIME PREDICTION; RESPIRATORY MOTIONS; ROOT MEAN SQUARED; SET-UP CONDITIONS; TARGET MOTIONS; TRACKING SYSTEM;

BIOLOGICAL ORGANS; FEATURE EXTRACTION; PRINCIPAL COMPONENT ANALYSIS; RESPIRATORY MECHANICS; TARGETS; THREE DIMENSIONAL;

FORECASTING;

ALGORITHM; ARTICLE; BREATHING; COMPUTER PROGRAM; HUMAN; INTERNET; LUNG TUMOR; METHODOLOGY; MOVEMENT (PHYSIOLOGY); NORMAL DISTRIBUTION; PATHOLOGY; RADIOTHERAPY; REPRODUCIBILITY; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING; TIME;

ALGORITHMS; HUMANS; IMAGING, THREE-DIMENSIONAL; INTERNET; LUNG NEOPLASMS; MODELS, STATISTICAL; MOVEMENT; NORMAL DISTRIBUTION; RADIOTHERAPY; REPRODUCIBILITY OF RESULTS; RESPIRATION; SOFTWARE; TIME FACTORS;

EID: 77952375635     PISSN: 00319155     EISSN: 13616560     Source Type: Journal    
DOI: 10.1088/0031-9155/55/11/002     Document Type: Article

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