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Deep Neural Network Classification of In Vivo Burn injuries with Different Etiologies Using THz Time-Domain Spectral Imaging

  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Patients arrive in burn centers with many etiologies of burn incidence (such as scald, contact, flame, steam, etc.). Treatment of these injuries depends on the burn depth and surface area of these burns. Moreover, earlier diagnosis and treatment of these burns lead to better patient outcomes. In this study, we show that THz-TDS imaging with a neural network classification algorithm can reproducibly classify burns, independent of their etiology, with an ROC-AUC of 88% in a porcine model.

Original languageEnglish
Title of host publication2021 46th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2021
PublisherIEEE Computer Society
ISBN (Electronic)9781728194240
DOIs
StatePublished - 2021
Event46th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2021 - Chengdu, China
Duration: Aug 30 2021Sep 3 2021

Publication series

NameInternational Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz
Volume2021-August
ISSN (Print)2162-2027
ISSN (Electronic)2162-2035

Conference

Conference46th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2021
Country/TerritoryChina
CityChengdu
Period08/30/2109/3/21

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