A fast convex optimization approach to segmenting 3D scar tissue from delayed-enhancement cardiac MR images

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

Volumn 7510 LNCS, Issue , 2012, Pages 659-666

  Rajchl, Martin ^a,b   Yuan, Jing ^a   White, James A ^a,c   Nambakhsh, Cyrus M S ^a,b   Ukwatta, Eranga ^a,b   Li, Feng ^a,b   Stirrat, John ^a   Peters, Terry M ^a,b  

^a ROBARTS RESEARCH INSTITUTE   (Canada)

^b UNIVERSITY OF WESTERN ONTARIO   (Canada)

^c WESTERN UNIVERSITY   (Canada)

Author keywords

Convex relaxation; DE MRI; Image segmentation

Indexed keywords

CONVEX OPTIMIZATION; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; MEDICAL COMPUTING; MEDICAL IMAGING; RELAXATION PROCESSES; TISSUE;

CARDIAC MR IMAGES; CONVEX OPTIMIZATION PROBLEMS; CONVEX RELAXATION; GEOMETRIC REPRESENTATION; MULTI-REGION SEGMENTATIONS; OPTIMIZATION APPROACH; OPTIMIZATION PROBLEMS; SPATIAL CONSISTENCY;

IMAGE ENHANCEMENT;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER PROGRAM; COMPUTER SIMULATION; HEART MUSCLE; HUMAN; IMAGE PROCESSING; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; OBSERVER VARIATION; PATHOLOGY; REPRODUCIBILITY; SCAR; STATISTICAL MODEL; THEORETICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CICATRIX; COMPUTER SIMULATION; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MODELS, STATISTICAL; MODELS, THEORETICAL; MYOCARDIUM; OBSERVER VARIATION; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SOFTWARE;

MLCS; MLOWN;

EID: 84872579831     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33415-3_81     Document Type: Conference Paper

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