High resolution analysis of cervical cells: a progress report

R. S. Poulsen, L. H. Oliver, R. L. Cahn, C. Louis, G. Toussaint

Research output: Contribution to journalArticle

Abstract

This paper presents preliminary results of research toward the development of a high resolution analysis stage for a dual resolution image processing based prescreening device for cervical cytology. Experiments using both manual and automatic methods for cell segmentation are described. In both cases, 1500 cervical cells were analyzed and classified as normal or abnormal (dysplastic or malignant) using a minimum Mahalanobis distance classifier with 8 subclasses of normal cells, and 5 subclasses of abnormal cells. With manual segmentation, false positive and false negative error rates of 2.98 and 7.73% were obtained. Similar experiments using automatic cell segmentation methods yielded false positive and false negative error rates of 3.90 and 11.56%, respectively. In both cases, independant training and testing data were used.

Original languageEnglish (US)
Pages (from-to)689-695
Number of pages7
JournalUnknown Journal
Volume25
Issue number7
DOIs
StatePublished - Jan 1 1977

    Fingerprint

ASJC Scopus subject areas

  • Anatomy
  • Histology

Cite this