Learning multispectral texture features for cervical cancer detection

Yanxi Liu, Tong Zhao, Jiayong Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

We present a bottom-up approach for automatic cancer cell detection in multispectral microscopic thin Pap smear images. Around 4, 000 multispectral texture features are explored for cancer cell detection. Using two feature screening measures, the initial feature set is effectively reduced to a computationally manageable size. Based on pixel-level screening results, cancerous regions can thus be detected through a relatively simple procedure. Our experiments have demonstrated the potential of both multispectral and texture information to serve as valuable complementary cues to traditional detection methods.

Original languageEnglish (US)
Title of host publication2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings
PublisherIEEE Computer Society
Pages169-172
Number of pages4
ISBN (Electronic)078037584X
DOIs
StatePublished - Jan 1 2002
EventIEEE International Symposium on Biomedical Imaging, ISBI 2002 - Washington, United States
Duration: Jul 7 2002Jul 10 2002

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2002-January
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

OtherIEEE International Symposium on Biomedical Imaging, ISBI 2002
CountryUnited States
CityWashington
Period7/7/027/10/02

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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