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

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

Abstract

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.

Detaljer

Författare
Enheter & grupper
Externa organisationer
  • Skåne University Hospital
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Biomedicinsk laboratorievetenskap/teknologi
Originalspråkengelska
Artikelnummere0223682
TidskriftPLoS ONE
Volym14
Utgåva nummer10
StatusPublished - 2019
PublikationskategoriForskning
Peer review utfördJa