Support vector classification for pathological prostate images based on texture features of multi-categories

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics

Volumn , Issue , 2009, Pages 912-916

  Huang, P W ^a   Lee, Cheng Hsiung ^a   Lin, Phen Lan ^b  

^a NATIONAL CHUNG HSING UNIVERSITY   (Taiwan)

^b PROVIDENCE UNIVERSITY   (Taiwan)

Author keywords

Fractal dimension; Gleason grading; Prostate image; Prostatic carcinoma; SVM

Indexed keywords

AUTOMATED SYSTEMS; COMBINED FEATURES; CROSS VALIDATION; FEATURE SELECTION; FEATURE SETS; GLEASON GRADING; MULTI-WAVELETS; PATHOLOGICAL IMAGES; PROSTATE IMAGES; PROSTATIC CARCINOMA; SUPPORT VECTOR CLASSIFICATION; TEXTURE FEATURES; TRAINING AND TESTING;

CYBERNETICS; FINITE DIFFERENCE METHOD; IMAGE PROCESSING; INITIATORS (CHEMICAL); PARTIAL DISCHARGES; SUPPORT VECTOR MACHINES; TEXTURES;

FRACTAL DIMENSION;

EID: 74849113957     PISSN: 1062922X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSMC.2009.5346754     Document Type: Conference Paper

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