Challenges in automated detection of cervical intraepithelial neoplasia

Yeshwanth Srinivasan, Shuyu Yang, Brian Nutter, Sunanda Mitra, Benny Phillips, Rodney Long

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Cervical Intraepithelial Neoplasia (CIN) is a precursor to invasive cervical cancer, which annually accounts for about 3700 deaths in the United States and about 274,000 worldwide. Early detection of CIN is important to reduce the fatalities due to cervical cancer. While the Pap smear is the most common screening procedure for CIN, it has been proven to have a low sensitivity, requiring multiple tests to confirm an abnormality and making its implementation impractical in resource-poor regions. Colposcopy and cervicography are two diagnostic procedures available to trained physicians for non-invasive detection of CIN. However, many regions suffer from lack of skilled personnel who can precisely diagnose the bio-markers due to CIN. Automatic detection of CIN deals with the precise, objective and noninvasive identification and isolation of these bio-markers, such as the Acetowhite (AW) region, mosaicism and punctations, due to CIN. In this paper, we study and compare three different approaches, based on Mathematical Morphology (MM), Deterministic Annealing (DA) and Gaussian Mixture Models (MM), respectively, to segment the AW region of the cervix. The techniques are compared with respect to their complexity and execution times. The paper also presents an adaptive approach to detect and remove Specular Reflections (SR). Finally, algorithms based on MM and matched filtering are presented for the precise segmentation of mosaicism and punctations from AW regions containing the respective abnormalities.

Original languageEnglish
Title of host publicationMedical Imaging 2007
Subtitle of host publicationComputer-Aided Diagnosis
EditionPART 1
DOIs
StatePublished - 2007
EventMedical Imaging 2007: Computer-Aided Diagnosis - San Diego, CA, United States
Duration: Feb 20 2007Feb 22 2007

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
NumberPART 1
Volume6514
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2007: Computer-Aided Diagnosis
CountryUnited States
CitySan Diego, CA
Period02/20/0702/22/07

Keywords

  • Cervical cancer
  • Computer-aided diagnosis
  • Gaussian mixture models
  • Matched filtering
  • Segmentation

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