Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification.
<h4>Objectives</h4>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.<h4>Materials and methods</h4>EWDRS recordings (450-1550 nm...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2019-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0223682 |
| Summary: | <h4>Objectives</h4>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.<h4>Materials and methods</h4>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.<h4>Results</h4>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.<h4>Conclusion</h4>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. |
|---|---|
| ISSN: | 1932-6203 |