Fluoroscopic tumor tracking for image-guided lung cancer radiotherapy

Physics in Medicine and Biology

Volumn 54, Issue 4, 2009, Pages 981-992

  Lin, Tong ^a,b   Cervĩo, Laura I ^a   Tang, Xiaoli ^a   Vasconcelos, Nuno ^c   Jiang, Steve B ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b Peking University   (China)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORKS; CONFIDENCE LEVELS; FIDUCIAL MARKERS; FLUOROSCOPIC IMAGES; IMAGE-GUIDED; IMAGE-GUIDED RADIOTHERAPIES; LUNG CANCER RADIOTHERAPIES; LUNG CANCERS; LUNG TUMORS; MARKERLESS; MARKERLESS TRACKING; MAXIMUM ERRORS; MOTION PATTERNS; PARAMETRIC REPRESENTATIONS; PIXEL SIZES; POLYNOMIAL REGRESSIONS; PRINCIPAL COMPONENTS; REAL TIME; REGIONS OF INTERESTS; REGRESSION METHODS; TEMPLATE MATCHING METHODS; TRACKING ALGORITHMS; TRACKING ERRORS; TUMOR BOUNDARIES; TUMOR TRACKING;

BACKPROPAGATION; BIOLOGICAL ORGANS; NEURAL NETWORKS; PIXELS; PRINCIPAL COMPONENT ANALYSIS; RADIOTHERAPY; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES; TEMPLATE MATCHING; TUMORS;

TRACKING (POSITION);

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; CANCER PATIENT; CANCER RADIOTHERAPY; CLINICAL ARTICLE; EYE TRACKING; FLUOROSCOPY; HUMAN; IMAGE ANALYSIS; IMAGING SYSTEM; LUNG CANCER; LUNG TUMOR; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE; TUMOR LOCALIZATION;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; FLUOROSCOPY; HUMANS; LUNG NEOPLASMS; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; RADIOTHERAPY, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 63649127172     PISSN: 00319155     EISSN: 13616560     Source Type: Journal    
DOI: 10.1088/0031-9155/54/4/011     Document Type: Article

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