Application of multiphoton imaging and machine learning to lymphedema tissue analysis.

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ID: 27447
2019
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Ranked #12 of 18 articles by views in Biomedical optics express

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Abstract
The results of in-vivo two-photon imaging of lymphedema tissue are presented. The study involved 36 image samples from II stage lymphedema patients and 42 image samples from healthy volunteers. The papillary layer of the skin with a penetration depth of about 100 μm was examined. Both the collagen network disorganization and increase of the collagen/elastin ratio in lymphedema tissue, characterizing the severity of fibrosis, was observed. Various methods of image characterization, including edge detectors, a histogram of oriented gradients method, and a predictive model for diagnosis using machine learning, were used. The classification by "ensemble learning" provided 96% accuracy in validating the data from the testing set.
Reference Key
kistenev2019applicationbiomedical Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Kistenev, Yury V;Nikolaev, Viktor V;Kurochkina, Oksana S;Borisov, Alexey V;Vrazhnov, Denis A;Sandykova, Ekaterina A;
Journal Biomedical optics express
Year 2019
DOI
10.1364/BOE.10.003353
URL
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