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A multi-spectral approach for scene analysis of cervical cytology smears.
Author(s) -
R K Aggarwal,
James W. Bacus
Publication year - 1977
Publication title -
journal of histochemistry and cytochemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.971
H-Index - 124
eISSN - 1551-5044
pISSN - 0022-1554
DOI - 10.1177/25.7.330720
Subject(s) - papanicolaou stain , thresholding , papanicolaou test , cytology , artificial intelligence , computer science , stain , optical density , computer vision , pattern recognition (psychology) , cluster analysis , pathology , image (mathematics) , cervical cancer , medicine , staining , physics , optics , cancer
A multi-spectral approach for the scene analysis of cervical cytology smears, using multiple images of a scene digitized through suitably chosen color filters matched to the Papanicolaou stain, has been proposed here. This technique involves clustering of two-dimensional data for extracting cytoplasm of the epithelial cells. Its performance on an experimental data set of 233 scenes involving more than 10 types of normal and malignant epithelial cells has been compared with density and gradient thresholding techniques. This resulted in an approximate 83% rate of success compared to approximately 40% for the rest of the other techniques.

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