Analysis of digitized cervical images to detect cervical neoplasia

Research output: Contribution to journalConference article

3 Scopus citations

Abstract

Cervical cancer is the second most common malignancy in women worldwide. If diagnosed in the premalignant stage, cure is invariably assured. Although the Papanicolaou (Pap) smear has significantly reduced the incidence of cervical cancer where implemented, the test is only moderately sensitive, highly subjective and skilled-labor intensive. Newer optical screening tests (cervicography, direct visual inspection and speculoscopy), including fluorescent and reflective spectroscopy, are fraught with certain weaknesses. Yet, the integration of optical probes for the detection and discrimination of cervical neoplasia with automated image analysis methods may provide an effective screening tool for early detection of cervical cancer, particularly in resource poor nations. Investigative studies are needed to validate the potential for automated classification and recognition algorithms. By applying image analysis techniques for registration, segmentation, pattern recognition, and classification, cervical neoplasia may be reliably discriminated from normal epithelium. The National Cancer Institute (NCI), in cooperation with the National Library of Medicine (NLM), has embarked on a program to begin this and other similar investigative studies.

Original languageEnglish (US)
Pages (from-to)181-194
Number of pages14
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5370 I
DOIs
StatePublished - Oct 27 2004
EventProgress in Biomedical Optics and Imaging - Medical Imaging 2004: Imaging Processing - San Diego, CA, United States
Duration: Feb 16 2004Feb 19 2004

Keywords

  • Automated image analysis
  • Cervical neoplasia
  • Classification
  • Digitized cervical images
  • Image processing
  • Pattern recognition
  • Registration
  • Segmentation
  • Wavelet

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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