Spatial Image Segmentation for Breast Cancer Detection in Terahertz Imaging

Tanny Chavez, Nagma Vohra, Jingxian Wu, Magda El-Shenawee, Keith Bailey

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

Abstract

This paper proposes a new spatial image segmentation algorithm for breast cancer detection in terahertz (THz) images of freshly excised human tumors. Region classifications of fresh tissue with 3 or more regions, such as cancer, fat, and collagen, remain a challenge for cancer detection. We propose to tackle this problem by exploiting the spatial correlation among neighboring pixels in THz images, that is, pixels that are close to each other are more likely to belong to the same region. The spatial correlation among pixels is modeled by using Markov random fields (MRF). A Gaussian mixture model (GMM) with expectation maximization (EM) is then used to represent the statistical distributions of the THz images in both the frequency and spatial domain. Experiment results demonstrated that the proposed spatial image segmentation algorithm outperforms existing algorithms that do not consider spatial information.

Original languageEnglish (US)
Title of host publication2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, IEEECONF 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1157-1158
Number of pages2
ISBN (Electronic)9781728166704
DOIs
StatePublished - Jul 5 2020
Event2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, IEEECONF 2020 - Virtually, Toronto, Canada
Duration: Jul 5 2020Jul 10 2020

Publication series

Name2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, IEEECONF 2020 - Proceedings

Conference

Conference2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, IEEECONF 2020
CountryCanada
CityVirtually, Toronto
Period7/5/207/10/20

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Instrumentation

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