A machine vision system for automated non-invasive assessment of cell viability via dark field microscopy, wavelet feature selection and classification

BMC Bioinformatics

Volumn 9, Issue , 2008, Pages

  Wei, Ning ^a   Flaschel, Erwin ^a   Friehs, Karl ^a   Nattkemper, Tim Wilhelm ^a  

^a BIELEFELD UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

BIOTECHNOLOGICAL APPLICATIONS; DARK FIELD MICROSCOPY; EXTRACTING INFORMATION; FEATURE SELECTION ALGORITHM; MACHINE VISION SYSTEMS; MISLEADING INFORMATIONS; NON-INVASIVE ASSESSMENTS; SUPERVISED MACHINE LEARNING;

CELL CULTURE; CELL PROLIFERATION; COMPUTER VISION; NONINVASIVE MEDICAL PROCEDURES; SUPERVISED LEARNING; WAVELET DECOMPOSITION;

CELLS;

ARTICLE; CELL ENERGY; CELL POPULATION; CELL VIABILITY; CONTROLLED STUDY; DARK FIELD MICROSCOPY; ENTROPY; MACHINE LEARNING; MACHINE VISION SYSTEM; MICROSCOPY; NON INVASIVE PROCEDURE; NONHUMAN; ALGORITHM; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CELL SURVIVAL; COMPUTER ASSISTED DIAGNOSIS; METHODOLOGY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CELL SURVIVAL; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MICROSCOPY; PATTERN RECOGNITION, AUTOMATED;

EID: 56049112338     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-9-449     Document Type: Article

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