title: Comparison of three different methods for automated classification of cervical cells.
abstract: Over 4600 exfoliated squamous cervical cells taken from appropriate Papanicolaou samples were classified as normal, mildly dysplastic, moderately dysplastic and severely dysplastic by an experienced cytopathologist. The slides were de-stained and subsequently re-stained with Feulgen Thionin-SO2 stain. Images of the nuclei were then captured, recorded and processed employing an image cytometry device. Automated classification of the cells was carried out using three different methods--discriminant function analysis, a decision tree classifier and a neutral network classifier. The discriminant function analysis method, which combined all dysplastic cells into an abnormal group, achieved a combined error rate of less than 0.4% for moderate and severe dysplastic cells, and less than 40% for mildly dysplastic cells. All three methods yielded comparable results, which approached those of human performance.
mesh_terms: D002467:Cell Nucleus / Q000473:pathology; D004396:Coloring Agents; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D065006:Papanicolaou Test; D012394:Rosaniline Dyes; D013194:Staining and Labeling; D013223:Statistics as Topic; D002583:Uterine Cervical Neoplasms / Q000145:classification*; D014626:Vaginal Smears
chemical_list: D004396:Coloring Agents; C007722:Feulgen stain; D012394:Rosaniline Dyes