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Cervical Cancer Cells Classification Using Cytological Optical Images Features | ||
| Al-Mustansiriyah Journal of Science | ||
| Article 1, Volume 26, Issue 1, 2015, Pages 4-7 | ||
| Author | ||
| Salim J. Attia | ||
| Abstract | ||
| The discussed approach in this paper is extracting the statistical features of digital optical images. The features include mean, coefficient of variance, contrast, maximum probability density and standard deviation. The decision making step in this research used minimum distance MD approach, which presented as a chosen technique to classify images. In this paper we focus on human cervical cancer screening system that can be used by cytologists to differentiate benign from malignant in suspicious cases that cytologists face. | ||
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