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

Autoři: Ulf Dahlstrand aff001;  Rafi Sheikh aff001;  Cu Dybelius Ansson aff001;  Khashayar Memarzadeh aff001;  Nina Reistad aff002;  Malin Malmsjö aff001
Působiště autorů: Lund University, Skåne University Hospital, Department of Clinical Sciences Lund, Ophthalmology, Lund, Sweden aff001;  Department of Atomic Physics, Lund University, Lund, Sweden aff002
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0223682



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.


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.


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.

Klíčová slova:

Cancer detection and diagnosis – Histology – Light – Melanin – Pig models – Tongue – Skin tissue – Skin tumors


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2019 Číslo 10
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