Transductive cost-sensitive lung cancer image classification

Applied Intelligence

Volumn 38, Issue 1, 2013, Pages 16-28

  Shi, Yinghuan ^a   Gao, Yang ^a   Wang, Ruili ^b   Zhang, Ying ^c   Wang, Dong ^c  

^a NANJING UNIVERSITY   (China)

^b MASSEY UNIVERSITY   (New Zealand)

^c Bayi Hospital   (China)

Author keywords

Cost sensitive; Lung cancer image classification; Transductive

Indexed keywords

CAPTURE IMAGES; CLASSIFICATION METHODS; CLASSIFICATION PROCEDURE; CODE-WORDS; CODEBOOKS; COST-SENSITIVE; EXTRACTION PROCEDURE; IMAGE CAPTURING; INDIVIDUAL CELLS; K-MEANS CLUSTERING; LAPLACIANS; LEARNING PROCEDURES; LUNG CANCER; MULTI-CLASS; NEEDLE BIOPSY; REGULARIZED LEAST SQUARES; SEMI-SUPERVISED LEARNING; SQUAMOUS CARCINOMA; STATISTICAL INFORMATION; TRAINING IMAGE; TRAINING SAMPLE; TRANSDUCTIVE;

ADAPTIVE BOOSTING; BIOLOGICAL ORGANS; BIOPSY; COSTS; DISEASES; FEATURE EXTRACTION; IMAGE SEGMENTATION; SUPERVISED LEARNING;

IMAGE CLASSIFICATION;

EID: 84871788962     PISSN: 0924669X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10489-012-0354-z     Document Type: Article

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