Combining statistical and geometric features for colonic polyp detection in CTC based on multiple kernel learning

International Journal of Computational Intelligence and Applications

Volumn 9, Issue 1, 2010, Pages 1-15

  Wang, Shijun ^a   Yao, Jianhua ^a   Petrick, Nicholas ^b   Summers, Ronald M ^a  

^a NATIONAL INSTITUTES OF HEALTH   (United States)

^b CENTER FOR DEVICES AND RADIOLOGICAL HEALTH   (United States)

Author keywords

Colonic polyp detection; Computed tomographic colonography; Histograms of curvature features; Multiple kernel learning; Semi definite programming

Indexed keywords

COLON CANCER; COLONIC POLYP DETECTION; COLONIC POLYPS; COMBINED FEATURES; COMPUTED TOMOGRAPHIC COLONOGRAPHY; COMPUTER AIDED DETECTION SYSTEMS; CURVATURE INFORMATION; DATA SETS; FALSE POSITIVE; FEATURE SETS; GEOMETRIC FEATURE; MULTIPLE KERNEL LEARNING; SCALE INVARIANT; SEMI-DEFINITE PROGRAMMING; SHAPE DESCRIPTORS; SHAPE INFORMATION; STATISTICAL FEATURES;

GRAPHIC METHODS; OPTIMIZATION; STATISTICAL TESTS; TEMPERATURE CONTROL;

SUPPORT VECTOR MACHINES;

EID: 77951683262     PISSN: 14690268     EISSN: None     Source Type: Journal    
DOI: 10.1142/S1469026810002744     Document Type: Article

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