Multiclass detection of cells in multicontrast composite images

Computers in Biology and Medicine

Volumn 40, Issue 2, 2010, Pages 168-178

  Long, Xi ^a   Louis Cleveland, W ^b   Lawrence Yao, Y ^a  

^a Department of Earth and Environmental Sciences   (United States)

^b Och Spine at New York Presbyterian Hospitals   (United States)

Author keywords

Cell detection; Kernel methods; Multicontrast composite images; Support vector machines

Indexed keywords

CELL DETECTION; COMPOSITE IMAGES; DETECTION ACCURACY; HIGH-ORDER; KERNEL METHODS; KERNEL PCA; MULTI-CLASS; MULTICONTRAST COMPOSITE IMAGES; NON-LINEAR CORRELATIONS; PRACTICAL SYSTEMS; SYSTEMATIC STUDY; TRANSMITTED LIGHT;

SUPPORT VECTOR MACHINES;

BIOINFORMATICS;

ACCURACY; ANIMAL CELL; ARTICLE; CONTROLLED STUDY; HUMAN; HUMAN CELL; ILLUMINATION; IMAGE PROCESSING; INTERMETHOD COMPARISON; KERNEL METHOD; MOLECULAR IMAGING; MOUSE; NONHUMAN; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL;

ALGORITHMS; ANIMALS; ARTIFICIAL INTELLIGENCE; CELL LINE, TUMOR; EUKARYOTIC CELLS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MICE; MICROSCOPY; PATTERN RECOGNITION, AUTOMATED; PRINCIPAL COMPONENT ANALYSIS; ROC CURVE; SOFTWARE; STAINING AND LABELING;

EID: 77649185866     PISSN: 00104825     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2009.11.013     Document Type: Article

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