A convex max-flow segmentation of LV using subject-specific distributions on cardiac MRI

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

Volumn 6801 LNCS, Issue , 2011, Pages 171-183

  Nambakhsh, Mohammad Saleh ^a,c   Yuan, Jing ^a   Ben Ayed, Ismail ^b   Punithakumar, Kumaradevan ^b   Goela, Aashish ^a,d   Islam, Ali ^a,d   Peters, Terry ^a,c   Li, Shuo ^a,b  

^a UNIVERSITY OF WESTERN ONTARIO   (Canada)

^b GE HEALTHCARE   (Canada)

^c ROBARTS RESEARCH INSTITUTE   (Canada)

^d ST JOSEPH S HEALTH CENTRE   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

CARDIAC MRI; COMPUTATIONALLY INTENSIVE ALGORITHMS; CONVEX RELAXATION; CURVE EVOLUTION; DISTRIBUTION MODELS; EXPERIMENTAL EVALUATION; FLOW CONFIGURATIONS; GEOMETRICAL CONSTRAINTS; GLOBAL OPTIMUM; GRAPH CUT; GRAY SCALE; LEFT VENTRICLES; OPTIMAL REGIONS; OPTIMALITY; RADIAL DISTANCE; SUB-PROBLEMS; SUBJECT-SPECIFIC; WORK STUDY;

DATA PROCESSING; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; OPTIMIZATION; RELAXATION PROCESSES;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; HEART VENTRICLE; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HEART VENTRICLES; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING, CINE; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 80052314902     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-22092-0_15     Document Type: Conference Paper

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