Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification

Research output: Contribution to journalArticle


OBJECTIVES: An extended-wavelength diffuse reflectance spectroscopy (EWDRS) technique was evaluated for its ability to differentiate between and classify different skin and tissue types in an in vivo pig model.

MATERIALS AND METHODS: EWDRS recordings (450-1550 nm) were made on skin with different degrees of pigmentation as well as on the pig snout and tongue. The recordings were used to train a support vector machine to identify and classify the different skin and tissue types.

RESULTS: The resulting EWDRS curves for each skin and tissue type had a unique profile. The support vector machine was able to classify each skin and tissue type with an overall accuracy of 98.2%. The sensitivity and specificity were between 96.4 and 100.0% for all skin and tissue types.

CONCLUSION: EWDRS can be used in vivo to differentiate between different skin and tissue types with good accuracy. Further development of the technique may potentially lead to a novel diagnostic tool for e.g. non-invasive tumor margin delineation.


External organisations
  • Skåne University Hospital
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Biomedical Laboratory Science/Technology
Original languageEnglish
Article numbere0223682
JournalPLoS ONE
Issue number10
Publication statusPublished - 2019
Publication categoryResearch

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Ulf Dahlstrand, 2020, Lund: Lund University, Faculty of Medicine. 67 p.

Research output: ThesisDoctoral Thesis (compilation)

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