A large-to-fine-scale shape prior for probabilistic segmentations using a deformable M-rep

2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops

Volumn , Issue , 2008, Pages

  Liu, Xiaoxiao ^a   Jeong, Ja Yeon ^a   Levy, Joshua H ^a   Saboo, Rohit R ^a   Chaney, Edward L ^a   Pizer, Stephen M ^a  

^a UNIVERSITY OF NORTH CAROLINA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER VISION; COMPUTERIZED TOMOGRAPHY; DEFORMATION; FEATURE EXTRACTION; FINANCIAL DATA PROCESSING; IMAGE ENHANCEMENT; IMAGE PROCESSING; LAW ENFORCEMENT; PATTERN RECOGNITION; PRINCIPAL COMPONENT ANALYSIS; PROBABILITY;

ADAPTIVE RADIATION THERAPY; APPLICATIONS.; CT IMAGING; EIGEN-MODES; GLOBAL DEFORMATIONS; HIGH-DIMENSIONAL SPACES; LOCAL PERTURBATIONS; LOCAL REFINEMENT; LOW DIMENSIONAL; MEDIAL REPRESENTATION; PRINCIPAL COMPONENTS; SAMPLE SIZES; SCALE VARIATION; SEGMENTATION ACCURACY; SHAPE PRIORS; SHAPE REPRESENTATIONS; SIMULATED DATA SETS; TRAINING SAMPLES; WEAK INTENSITY;

THREE DIMENSIONAL;

EID: 51849099843     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2008.4563019     Document Type: Conference Paper

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