Regional heart motion abnormality detection via information measures and unscented Kalman filtering

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

Volumn 6361 LNCS, Issue PART 1, 2010, Pages 409-417

  Punithakumar, Kumaradevan ^a   Ben Ayed, Ismail ^a   Islam, Ali ^b   Ross, Ian G ^c   Li, Shuo ^a,d  

^a GE HEALTHCARE   (Canada)

^b ST JOSEPH S HEALTH CENTRE   (Canada)

^c LONDON HEALTH SCIENCES CENTRE   (Canada)

^d UNIVERSITY OF WESTERN ONTARIO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ABNORMALITY DETECTION; BAYESIAN FILTERS; DIFFERENTIAL ENTROPY; EXPERIMENTAL ANALYSIS; FUNCTIONAL IMAGES; GLOBAL DISTRIBUTION; HEART MOTION; HEART WALL MOTION; INFORMATION MEASURES; MAGNETIC RESONANCE IMAGES; MYOCARDIAL MOTION; NAIVE BAYES CLASSIFIERS; NOISY DATA; NONLINEAR DYNAMIC MODELS; PRIOR KNOWLEDGE; SET OF MOMENTS; SUPPORT TOOL; UNSCENTED KALMAN FILTER; UNSCENTED KALMAN FILTERING;

CLASSIFIERS; IMAGE SEGMENTATION; KALMAN FILTERS; MAGNETIC RESONANCE; MAGNETIC RESONANCE IMAGING; MEDICAL COMPUTING;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; HEART LEFT VENTRICLE FUNCTION; IMAGE ENHANCEMENT; METHODOLOGY; MOTION; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MOTION; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; VENTRICULAR DYSFUNCTION, LEFT;

EID: 84875249821     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15705-9_50     Document Type: Conference Paper

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