Shape priors for segmentation of the cervix region within uterine cervix images

Shelly Lotenberg, Shiri Gordon, Hayit Greenspan

Research output: Contribution to journalArticlepeer-review

Abstract

The work focuses on a unique medical repository of digital uterine cervix images ("cervigrams") collected by the National Cancer Institute (NCI), National Institute of Health, in longitudinal multiyear studies. NCI together with the National Library of Medicine is developing a unique web-based database of the digitized cervix images to study the evolution of lesions related to cervical cancer. Tools are needed for the automated analysis of the cervigram content to support the cancer research. In recent works, a multistage automated system for segmenting and labeling regions of medical and anatomical interest within the cervigrams was developed. The current paper concentrates on incorporating prior-shape information in the cervix region segmentation task. In accordance with the fact that human experts mark the cervix region as circular or elliptical, two shape models (and corresponding methods) are suggested. The shape models are embedded within an active contour framework that relies on image features. Experiments indicate that incorporation of the prior shape information augments previous results.

Original languageEnglish
Pages (from-to)286-296
Number of pages11
JournalJournal of Digital Imaging
Volume22
Issue number3
DOIs
StatePublished - Jun 2009

Keywords

  • Boundary extraction
  • Image analysis
  • Image segmentation
  • Levelset function
  • Shape prior
  • Uterine cervix

Fingerprint

Dive into the research topics of 'Shape priors for segmentation of the cervix region within uterine cervix images'. Together they form a unique fingerprint.

Cite this