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Missouri University of Science and Technology
<p>Cancer -- Histopathology<br />Cervix uteri -- Histopathology<br />Pattern recognition systems -- Classification<br />Image analysis<br />Cervix uteri -- Cancer -- Diagnosis</p>
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Uterine Cervical Cancer Histology Image Feature Extraction And Classification, Cheng Lu
Uterine Cervical Cancer Histology Image Feature Extraction And Classification, Cheng Lu
Masters Theses
"Cervical cancer, the second most common cancer affecting women worldwide and the most common in developing countries can be cured in almost all patients, if detected early and treated. However, cervical cancer incidence and mortality remain high in resource-poor regions, where early detection systems often cannot be maintained because of inherent complexity. The National Cancer Institute (NCI) has collected a vast amount of visual information, 100,000 cervigrams (35 mm color slides), screening thousands of women by this technique. In addition to the cervigrams, large digitized histology images are being archived.
In this research, a framework for automatic recognition and classification …