Learning optical flow propagation strategies using random forests for fast segmentation in dynamic 2D & 3D echocardiography

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

Volumn 7009 LNCS, Issue , 2011, Pages 75-82

  Verhoek, Michael ^a   Yaqub, Mohammad ^a   McManigle, John ^a   Noble, J Alison ^a  

^a UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

3D ECHOCARDIOGRAPHY; AUTOMATIC SEGMENTATIONS; BEST STRATEGY; CLINICAL DIAGNOSIS; ECHOCARDIOGRAPHIC SEQUENCES; HEART FUNCTION; LEFT VENTRICULAR MYOCARDIUMS; PROPAGATION STRATEGIES; QUANTITATIVE DATA; RANDOM FOREST CLASSIFIER; RANDOM FORESTS; SEGMENTATION RESULTS;

ALGORITHMS; DECISION TREES; DIAGNOSIS; ECHOCARDIOGRAPHY; IMAGE SEGMENTATION; LEARNING SYSTEMS; MEDICAL IMAGING; MOTION ESTIMATION; OPTICAL FLOWS; THREE DIMENSIONAL;

COMPUTER AIDED INSTRUCTION;

EID: 80054006970     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-24319-6_10     Document Type: Conference Paper

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