Automatic recognition of five types of white blood cells in peripheral blood

Computerized Medical Imaging and Graphics

Volumn 35, Issue 4, 2011, Pages 333-343

  Rezatofighi, Seyed Hamid ^a   Soltanian Zadeh, Hamid ^a,b  

^a UNIVERSITY OF TEHRAN   (Iran)

^b HENRY FORD HEALTH SYSTEM   (United States)

Author keywords

Classification; Feature selection; Gram Schmidt orthogonalization; Peripheral blood; Segmentation; Texture feature; White blood cell

Indexed keywords

CLASSIFICATION; FEATURE SELECTION; GRAM-SCHMIDT ORTHOGONALIZATION; PERIPHERAL BLOOD; SEGMENTATION; TEXTURE FEATURE; WHITE BLOOD CELL;

ALGORITHMS; CELLS; CYTOLOGY; FEATURE EXTRACTION; IMAGE PROCESSING; NEURAL NETWORKS; TEXTURES;

BLOOD;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BLOOD; CELL NUCLEUS; CELL TYPE; CLASSIFICATION ALGORITHM; CONTROLLED STUDY; CYTODIAGNOSIS; CYTOPLASM; GRAM SCHMIDT ORTHOGONALIZATION METHOD; IMAGE PROCESSING; LEUKOCYTE; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE;

ALGORITHMS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LEUKOCYTES; MICROSCOPY; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED;

EID: 79953749339     PISSN: 08956111     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compmedimag.2011.01.003     Document Type: Article

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