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...
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doaj-bbca7c833af04d22ae3d5e31fc7db9102021-03-04T10:23:45ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-011410e022368210.1371/journal.pone.0223682Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification.Ulf DahlstrandRafi SheikhCu Dybelius AnssonKhashayar MemarzadehNina ReistadMalin Malmsjö<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.https://doi.org/10.1371/journal.pone.0223682 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ulf Dahlstrand Rafi Sheikh Cu Dybelius Ansson Khashayar Memarzadeh Nina Reistad Malin Malmsjö |
spellingShingle |
Ulf Dahlstrand Rafi Sheikh Cu Dybelius Ansson Khashayar Memarzadeh Nina Reistad Malin Malmsjö Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification. PLoS ONE |
author_facet |
Ulf Dahlstrand Rafi Sheikh Cu Dybelius Ansson Khashayar Memarzadeh Nina Reistad Malin Malmsjö |
author_sort |
Ulf Dahlstrand |
title |
Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification. |
title_short |
Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification. |
title_full |
Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification. |
title_fullStr |
Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification. |
title_full_unstemmed |
Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification. |
title_sort |
extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2019-01-01 |
description |
<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. |
url |
https://doi.org/10.1371/journal.pone.0223682 |
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