Classification of cervix lesions using filter bank-based texture models

Yeshwanth Srinivasan, Brian Nutter, Sunanda Mitra, Benny Phillips, Eric Sinzinger

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

11 Scopus citations

Abstract

This paper explores the classification of texture patterns observed in digital images of the cervix. In particular, the problem of identifying and segmenting punctations and mosaic patterns is considered. First, the ability of large scale filter banks in characterizing punctations and mosaic structures is studied using texton models. However, texton-based models fail to consistently classify punctation and mosaic sections obtained from cervix images of different subjects. We present a novel method to segment punctations that combines matched filtering using a Gaussian template with Gaussian Mixture Models. Features extracted from the objects detected using this novel method on punctation and mosaic sections are shown to provide excellent classification between punctation and mosaicism. Results demonstrate the effectiveness of our approach in detecting punctations and separating punctation sections from mosaic sections.

Original languageEnglish
Title of host publicationProceedings - 19th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2006
Pages832-837
Number of pages6
DOIs
StatePublished - 2006
Event19th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2006 - Salt Lake City, UT, United States
Duration: Jun 22 2006Jun 23 2006

Publication series

NameProceedings - IEEE Symposium on Computer-Based Medical Systems
Volume2006
ISSN (Print)1063-7125

Conference

Conference19th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2006
CountryUnited States
CitySalt Lake City, UT
Period06/22/0606/23/06

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