Accuracy of nuclear classification in cervical smear images: Quantitative impact of computational deconvolution and 3-D feature computation

Analytical and Quantitative Cytology and Histology

Volumn 20, Issue 2, 1998, Pages 77-91

  Mackin Jr , Robert W ^a,b   Newton, Louise M ^c   Turner, James N ^c   Holmes, Timothy J ^a,d   Roysam, Badrinath ^a  

^a RENSSELAER POLYTECHNIC INSTITUTE   (United States)

^b SIEMENS CORPORATE RESEARCH   (United States)

^c WADSWORTH CENTER   (United States)

^d AutoQuant Imaging Inc   (United States)

Author keywords

3 D brightfield microscopy; 3 D features; Cell classification; Cell clusters; Cervical smears; Computational deconvolution

Indexed keywords

ACCURACY; ARTICLE; CANCER SCREENING; DISEASE CLASSIFICATION; FEULGEN STAINING; HUMAN; HUMAN TISSUE; PRIORITY JOURNAL; THREE DIMENSIONAL IMAGING; UTERINE CERVIX CANCER; UTERINE CERVIX CYTOLOGY; VOLUMETRY;

ALGORITHMS; CELL NUCLEUS; CERVIX UTERI; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; VAGINAL SMEARS;

EID: 2642648641     PISSN: 08846812     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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