Stratified learning of local anatomical context for lung nodules in CT images

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2010, Pages 2791-2798

  Wu, Dijia ^a,b   Lu, Le ^a   Bi, Jinbo ^a   Shinagawa, Yoshihisa ^a   Boyer, Kim ^b   Krishnan, Arun ^a   Salganicoff, Marcos ^a  

^a CAD and Knowledge Solutions   (United States)

^b RENSSELAER POLYTECHNIC INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANATOMICAL LANDMARKS; ANNOTATED DATABASE; AREA UNDER ROCS; AUTOMATIC DETECTION; CAD SYSTEM; CLASS PROBABILITIES; CO-OCCURRENCE; CONDITIONAL RANDOM FIELD; CT IMAGE; EXPERIMENTAL VALIDATIONS; FEATURE SETS; LUNG ANATOMY; LUNG NODULE; MULTI-CLASS; MULTI-LABEL; PAIRWISE PROBABILITIES; PULMONARY STRUCTURE; STATISTICAL LEARNING; SUBVOLUMES;

CLASSIFIERS; COMPUTER VISION; COMPUTERIZED TOMOGRAPHY; PROBABILITY DENSITY FUNCTION; THREE DIMENSIONAL;

BIOLOGICAL ORGANS;

EID: 77955996058     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2010.5540008     Document Type: Conference Paper

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