Predicting respiratory tumor motion with multi-dimensional adaptive filters and support vector regression

Physics in Medicine and Biology

Volumn 54, Issue 19, 2009, Pages 5735-5748

  Riaz, Nadeem ^a   Shanker, Piyush ^b   Wiersma, Rodney ^a   Gudmundsson, Olafur ^b   Mao, Weihua ^a   Widrow, Bernard ^b   Xing, Lei ^a  

^a STANFORD UNIVERSITY   (United States)

^b Stanford University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BEAM TRACKING; CONVENTIONAL METHODS; CORRELATED SIGNALS; FUTURE POSITION; LUNG TUMOR; MULTIPLE INPUT SINGLE OUTPUTS; NOVEL METHODS; RADIATION DELIVERY; ROOT-MEAN SQUARE ERRORS; SINGLE INPUT , SINGLE OUTPUTS; SUPPORT VECTOR REGRESSIONS; TIME LATENCY; TREATMENT BEAMS; TUMOR MOTION; TUMOR TRACKING;

ADAPTIVE FILTERING; ADAPTIVE FILTERS; ADAPTIVE SYSTEMS; ELECTRIC FILTERS; IMAGE ACQUISITION; REGRESSION ANALYSIS; TRACKING (POSITION); TUMORS; VECTORS;

SIGNAL PROCESSING;

ARTICLE; CANCER RADIOTHERAPY; DIAGNOSTIC IMAGING; FILTER; IMAGE DISPLAY; INTENSITY MODULATED RADIATION THERAPY; LINEAR REGRESSION ANALYSIS; LUNG TUMOR; MOTION; MULTIDIMENSIONAL LINEAR ADAPTIVE FILTERS; PRIORITY JOURNAL; RADIATION DOSE DISTRIBUTION; SUPPORT VECTOR MACHINE;

ARTIFICIAL INTELLIGENCE; HUMANS; LUNG NEOPLASMS; MODELS, BIOLOGICAL; MOVEMENT; NONLINEAR DYNAMICS; REGRESSION ANALYSIS; RESPIRATION;

EID: 70350649031     PISSN: 00319155     EISSN: 13616560     Source Type: Journal    
DOI: 10.1088/0031-9155/54/19/005     Document Type: Article

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