Illumination correction for content analysis in uterine cervix images

Hila Dvir, Shiri Gordon, Hayit Greenspan

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

7 Scopus citations

Abstract

Illumination field inhomogeneity strongly affects the visual appearance of an image. It has a major influence on automatic information extraction within an image and its correction is critical for comparison or model learning across images. In this work a unique medical repository of cervicographic images ("cervigrams") collected by the National Center Institute (NCI), National Institute of Health (NIH) is being addressed. The large diversity of cervix shapes within this database, as well as the acquisition set-up, lead to varying illumination conditions among and within the cervigrams, which hamper their automatic analysis. Illumination correction is therefore one of the first preprocessing steps required prior to the image analysis task. This paper presents a method for illumination correction in cervigrams based on a generalized expectation maximization (GEM) algorithm that interleaves pixels classification with estimation of class distribution and illumination field parameters. For cross-image analysis a normalization of the image dynamic range is conducted, using prior knowledge on cervix tissue intensity distribution. Experimental results are provided and evaluated on a set of 110 cervigrams that were manually labeled, by an NCI expert. Unsupervised segmentation as well, as initial, supervised tissue classification results are presented.

Original languageEnglish
Title of host publication2006 Conference on Computer Vision and Pattern Recognition Workshop
DOIs
StatePublished - 21 Dec 2006
Externally publishedYes
Event2006 Conference on Computer Vision and Pattern Recognition Workshops - New York, NY, United States
Duration: 17 Jun 200622 Jun 2006

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume2006
ISSN (Print)1063-6919

Conference

Conference2006 Conference on Computer Vision and Pattern Recognition Workshops
Country/TerritoryUnited States
CityNew York, NY
Period17/06/0622/06/06

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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