Automated detection of tuberculosis in Ziehl-Neelsen-stained sputum smears using two one-class classifiers

Journal of Microscopy

Volumn 237, Issue 1, 2010, Pages 96-102

  Khutlang, R ^a   Krishnan, S ^a   Whitelaw, A ^b   Douglas, T S ^a  

^a UNIVERSITY OF CAPE TOWN   (South Africa)

^b UNIVERSITY OF CAPE TOWN   (South Africa)

Author keywords

Automated microscopy; Classifiers; Segmentation; Tuberculosis; Ziehl Neelsen

Indexed keywords

BACTERIOLOGY; MATHEMATICAL TRANSFORMATIONS; TUBES (COMPONENTS);

AUTOMATED DETECTION; AUTOMATED IDENTIFICATION; AUTOMATED MICROSCOPY; BRIGHT-FIELDS; MYCOBACTERIUM TUBERCULOSIS; OBJECTS SEGMENTATION; ONE-CLASS CLASSIFIER; SEGMENTATION; TUBERCULOSIS; ZIEHL-NEELSEN;

AUTOMATION;

ARTICLE; BACTERIUM DETECTION; BACTERIUM IDENTIFICATION; BRIGHT FIELD MICROSCOPY; CLASSIFICATION; GEOMETRY; IMAGE ANALYSIS; LABORATORY AUTOMATION; MICROSCOPE; MYCOBACTERIUM TUBERCULOSIS; NONHUMAN; NORMAL DISTRIBUTION; PERFORMANCE; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SCREENING TEST; SPUTUM SMEAR; TUBERCULOSIS;

MYCOBACTERIUM TUBERCULOSIS;

EID: 72349092102     PISSN: 00222720     EISSN: 13652818     Source Type: Journal    
DOI: 10.1111/j.1365-2818.2009.03308.x     Document Type: Article

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