Performance Comparison Of Extracted Features In Automated Classification Of Cervical Smears

Andrew Seit; Dapeng Tien; Peter Nickolls; Alan Yeung; Jim Tucker

doi:10.1117/12.968671

27 June 1988 Performance Comparison Of Extracted Features In Automated Classification Of Cervical Smears

Andrew Seit, Dapeng Tien, Peter Nickolls, Alan Yeung, Jim Tucker

Proceedings Volume 0914, Medical Imaging II; (1988) https://doi.org/10.1117/12.968671
Event: Medical Imaging II, 1988, Newport Beach, CA, United States

Abstract

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.

Citation Download Citation

Andrew Seit, Dapeng Tien, Peter Nickolls, Alan Yeung, and Jim Tucker "Performance Comparison Of Extracted Features In Automated Classification Of Cervical Smears", Proc. SPIE 0914, Medical Imaging II, (27 June 1988); https://doi.org/10.1117/12.968671

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