Hyperspectral imaging in medical applications

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires three-dimensional data set called hypercube with two spatial dimensions and one spectral dimension. Spatially resolved spectral obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This chapter presents an overview of literature on medical hyperspectral imaging (MHSI) technology and its applications. The aim of this chapter is threefold: an introduction for those new to the field of MHSI, an overview for those working in the field, and a reference for those searching for literature on a specific application. This chapter starts to review the basic mechanisms of MHSI and then classify MHSI technology based on acquisition mode, spectral range and spatial resolution, measurement mode, dispersive devices, detector arrays, and combination with other techniques. Image analysis methods for MHSI are summarized with preprocessing, feature extraction and selection, image classification methods. The part on applications is a reference of the literature available on disease diagnosis and surgical guidance. MHSI applications on cancer detection, cardiology, pathology, retinal imaging, diabetic foot, shock, tissue pathology, mastectomy, gallbladder surgery, renal surgery, and abdominal surgery are reviewed. This chapter closes with a discussion on future challenges and perspectives.

Original languageEnglish (US)
Title of host publicationData Handling in Science and Technology
PublisherElsevier Ltd.
Pages523-565
Number of pages43
DOIs
StatePublished - 2020

Publication series

NameData Handling in Science and Technology
Volume32
ISSN (Print)0922-3487

Keywords

  • Cancer detection and diagnosis
  • Image analysis and classification
  • Image-guided surgery
  • Medical hyperspectral imaging
  • Quantitative imaging
  • Tissue optics

ASJC Scopus subject areas

  • Signal Processing
  • Chemistry(all)
  • Modeling and Simulation
  • Computer Science Applications

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  • Cite this

    Fei, B. (2020). Hyperspectral imaging in medical applications. In Data Handling in Science and Technology (pp. 523-565). (Data Handling in Science and Technology; Vol. 32). Elsevier Ltd.. https://doi.org/10.1016/B978-0-444-63977-6.00021-3