Hyperspectral imaging and spectral-spatial classification for cancer detection

Baowei Fei, Hamed Akbari, Luma V. Halig

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

20 Scopus citations

Abstract

Hyperspectral imaging is an emerging technology for biomedical applications. In this study, an advanced image processing and classification method is proposed to analyze hyperspectral image data for prostate cancer detection. Least squares support vector machines (LS-SVMs) were developed and evaluated for classifying hyperspectral data in order to enhance the detection of cancer tissue. The method was used to detect prostate cancer in tumor-bearing mice. Spatially resolved images were created to highlight the differences of the reflectance properties of cancer versus those of normal tissue. Preliminary results in mice show that the hyperspectral imaging and classification method was able to reliably detect prostate tumors in the animal model. The hyperspectral imaging technique may provide a new tool for optical diagnosis of cancer.

Original languageEnglish (US)
Title of host publication2012 5th International Conference on Biomedical Engineering and Informatics, BMEI 2012
Pages62-64
Number of pages3
DOIs
StatePublished - Dec 1 2012
Externally publishedYes
Event2012 5th International Conference on Biomedical Engineering and Informatics, BMEI 2012 - Chongqing, China
Duration: Oct 16 2012Oct 18 2012

Publication series

Name2012 5th International Conference on Biomedical Engineering and Informatics, BMEI 2012

Conference

Conference2012 5th International Conference on Biomedical Engineering and Informatics, BMEI 2012
CountryChina
CityChongqing
Period10/16/1210/18/12

Keywords

  • Hyperspectral imaging
  • prostate cancer detection
  • spectral-spatial classification
  • support vector machine

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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  • Cite this

    Fei, B., Akbari, H., & Halig, L. V. (2012). Hyperspectral imaging and spectral-spatial classification for cancer detection. In 2012 5th International Conference on Biomedical Engineering and Informatics, BMEI 2012 (pp. 62-64). [6513047] (2012 5th International Conference on Biomedical Engineering and Informatics, BMEI 2012). https://doi.org/10.1109/BMEI.2012.6513047