Performance Comparison Of Extracted Features In Automated Classification Of Cervical Smears
Andrew Seit, Dapeng Tien, Peter M. Nickolls, Alan Yeung, J. H. Tucker · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1988
Automated cervical smear screening is potentially a cheap, rapid method for detecting early cervical cancer and so preventing deaths from this disease. CERVIFIP is a fast scanning machine which classifies microscope images of cervical smears. Although its current false negative error rate is below that of cytotechnicians, its false positive error rate is unacceptably high. New boundary and grey-level texture algorithms are being applied to reduce these rates. In addition a hierarchical rules-based classifier is to be superimposed on the existing statistical classifiers.