In-vivo and ex-vivo tissue analysis through hyperspectral imaging techniques: Revealing the invisible features of cancer

Martin Halicek, Himar Fabelo, Samuel Ortega, Gustavo M. Callico, Baowei Fei

Research output: Contribution to journalReview article

21 Scopus citations

Abstract

In contrast to conventional optical imaging modalities, hyperspectral imaging (HSI) is able to capture much more information from a certain scene, both within and beyond the visual spectral range (from 400 to 700 nm). This imaging modality is based on the principle that each material provides different responses to light reflection, absorption, and scattering across the electromagnetic spectrum. Due to these properties, it is possible to differentiate and identify the different materials/substances presented in a certain scene by their spectral signature. Over the last two decades, HSI has demonstrated potential to become a powerful tool to study and identify several diseases in the medical field, being a non-contact, non-ionizing, and a label-free imaging modality. In this review, the use of HSI as an imaging tool for the analysis and detection of cancer is presented. The basic concepts related to this technology are detailed. The most relevant, state-of-the-art studies that can be found in the literature using HSI for cancer analysis are presented and summarized, both in-vivo and ex-vivo. Lastly, we discuss the current limitations of this technology in the field of cancer detection, together with some insights into possible future steps in the improvement of this technology.

Original languageEnglish (US)
Article number756
JournalCancers
Volume11
Issue number6
DOIs
StatePublished - Jun 2019

Keywords

  • Artificial intelligence
  • Biomedical optical imaging
  • Cancer
  • Clinical diagnosis
  • Hyperspectral imaging
  • Machine learning
  • Medical diagnostic imaging

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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