Auto-context and its application to high-level vision tasks and 3D brain image segmentation

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 32, Issue 10, 2010, Pages 1744-1757

  Tu, Zhuowen ^a   Bai, Xiang ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

3D brain segmentation; conditional random fields; Context; discriminative models; image segmentation; object recognition

Indexed keywords

ALGORITHM DESIGN; ANATOMICAL STRUCTURES; BRAIN MRI; BRAIN SEGMENTATION; CLASSIFICATION CONFIDENCE; CONDITIONAL RANDOM FIELD; CONFIGURATION ESTIMATION; CONTEXT; CONTEXT ALGORITHM; CONTEXT INFORMATION; CONTEXT MODELS; DISCRIMINATIVE MODELS; FOREGROUND/BACKGROUND; HUMAN BODIES; IMAGE APPEARANCE; IMAGE PATCHES; MARKOV RANDOM FIELD; MEDICAL IMAGE SEGMENTATION; ORIGINAL IMAGES; PARAMETER SETTING; REGION LABELING; SHAPE INFORMATION; STATE-OF-THE-ART ALGORITHMS; STRUCTURED PREDICTION; TRAINING IMAGE; VISION APPLICATIONS;

BRAIN MODELS; CLASSIFIERS; CONTENT BASED RETRIEVAL; CONVERGENCE OF NUMERICAL METHODS; IMAGE ANALYSIS; LEARNING ALGORITHMS; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING; MEDICAL PROBLEMS; OBJECT RECOGNITION; THREE DIMENSIONAL;

IMAGE SEGMENTATION;

ALGORITHM; ANIMAL; ARTICLE; AUTOMATED PATTERN RECOGNITION; BRAIN; HISTOLOGY; HORSE; HUMAN; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PROBABILITY; THREE DIMENSIONAL IMAGING; WHOLE BODY IMAGING;

ALGORITHMS; ANIMALS; BRAIN; HORSES; HUMANS; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MARKOV CHAINS; PATTERN RECOGNITION, AUTOMATED; WHOLE BODY IMAGING;

EID: 77956051102     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2009.186     Document Type: Article

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