Superpixel-based spectral classification for the detection of head and neck cancer with hyperspectral imaging

Hyunkoo Chung, Guolan Lu, Zhiqiang Tian, Dongsheng Wang, Zhuo Georgia Chen, Baowei Fei

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

16 Scopus citations

Abstract

Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications. HSI acquires two di- mensional images at various wavelengths. The combination of both spectral and spatial information provides quantitative information for cancer detection and diagnosis. This paper proposes using superpixels, principal component analysis (PCA), and support vector machine (SVM) to distinguish regions of tumor from healthy tissue. The classification method uses 2 principal components decomposed from hyperspectral images and ob-tains an average sensitivity of 93% and an average specificity of 85% for 11 mice. The hyperspectral imaging technology and classification method can have various applications in cancer research and management.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2016
Subtitle of host publicationBiomedical Applications in Molecular, Structural, and Functional Imaging
EditorsBarjor Gimi, Andrzej Krol
PublisherSPIE
ISBN (Electronic)9781510600232
DOIs
StatePublished - 2016
Externally publishedYes
EventMedical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging - San Diego, United States
Duration: Mar 1 2016Mar 3 2016

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume9788
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging
CountryUnited States
CitySan Diego
Period3/1/163/3/16

Keywords

  • Feature extraction
  • Head and neck cancer
  • Hyperspectral imaging
  • Image classification
  • Principal component analysis (PCA)
  • Superpixels
  • Support vector machine (SVM)

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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