Efficient gaussian process-based modelling and prediction of image time series

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 9123, Issue , 2015, Pages 626-637

  Lorenzi, Marco ^a   Ziegler, Gabriel ^a   Alexander, Daniel C ^a   Ourselin, Sebastien ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; COVARIANCE MATRIX; FORECASTING; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); TIME SERIES;

COVARIANCE MATRICES; COVARIANCE STRUCTURES; MARGINAL LIKELIHOOD; MODELLING AND PREDICTIONS; NONPARAMETRIC METHODS; POSTERIOR PREDICTIONS; SPATIAL CORRELATIONS; SPATIO-TEMPORAL MODELS;

MEDICAL IMAGING;

AGED; ALZHEIMER DISEASE; AUTOMATED PATTERN RECOGNITION; BRAIN VENTRICLE; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; FEMALE; HUMAN; MALE; MIDDLE AGED; NORMAL DISTRIBUTION; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SPATIOTEMPORAL ANALYSIS; STATISTICAL MODEL; TIME; VERY ELDERLY;

AGED; AGED, 80 AND OVER; ALZHEIMER DISEASE; CEREBRAL VENTRICLES; COMPUTER SIMULATION; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; MODELS, STATISTICAL; NORMAL DISTRIBUTION; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SPATIO-TEMPORAL ANALYSIS; TIME FACTORS;

EID: 84983683532     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-19992-4_49     Document Type: Conference Paper

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