Automatic landmark detection in uterine cervix images for indexing in a content-retrieval system

Gali Zimmerman, Shiri Gordon, Hayit Greenspan

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

21 Scopus citations

Abstract

This work is motivated by the need for visual information extraction and management in the growing field of content based image retrieval from medical archives. In particular it focuses on a unique medical repository of cervicographic images ("Cervigrams") collected by the National Cancer Institute, National Institutes of Health, to study the evolution of lesions related to cervical cancer. The paper briefly presents a framework for cervigram segmentation and labelling, focusing on the identification of two anatomical landmarks: the cervix boundary and the os. These landmarks are identified based on their convexity, using adequate mathematical tools. Segmentation results are exemplified and an initial validation is carried out on a subset of 120 manually labelled cervigrams.

Original languageEnglish
Title of host publication2006 3rd IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro - Proceedings
Pages1348-1351
Number of pages4
StatePublished - 17 Nov 2006
Externally publishedYes
Event2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Arlington, VA, United States
Duration: 6 Apr 20069 Apr 2006

Publication series

Name2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
Volume2006

Conference

Conference2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Country/TerritoryUnited States
CityArlington, VA
Period6/04/069/04/06

ASJC Scopus subject areas

  • General Engineering

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