Rapid multi-organ segmentation using context integration and discriminative models

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

Volumn 7917 LNCS, Issue , 2013, Pages 450-462

  Lay, Nathan ^a   Birkbeck, Neil ^a   Zhang, Jingdan ^a   Zhou, S Kevin ^a  

^a SIEMENS AG   (Germany)

Author keywords

context integration; discriminative learning; Local global context; multi landmark detection; multi organ segmentation

Indexed keywords

DISCRIMINATIVE CLASSIFIERS; DISCRIMINATIVE LEARNING; DISCRIMINATIVE MODELS; EFFICIENT DETECTION; GLOBAL CONTEXT; LOW RESOLUTION; MULTI-ORGAN SEGMENTATIONS; NON-PARAMETRIC MODELING;

DATA PROCESSING; MEDICAL IMAGING;

DETECTORS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; COMPUTER SIMULATION; DISCRIMINANT ANALYSIS; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; SYSTEM ANALYSIS; THREE DIMENSIONAL IMAGING; VISCERA;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DISCRIMINANT ANALYSIS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SYSTEMS INTEGRATION; TOMOGRAPHY, X-RAY COMPUTED; VISCERA;

EID: 84901277078     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-38868-2_38     Document Type: Conference Paper

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