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Raman spectroscopy accurately classifies burn severity in an ex vivo model.
Ye, Hanglin; Kruger, Uwe; Wang, Tianmeng; Shi, Sufei; Norfleet, Jack; De, Suvranu.
Affiliation
  • Ye H; Center for Modeling, Simulation and Imaging in Medicine (CeMSIM), Rensselaer Polytechnic Institute, Troy, NY, USA. Electronic address: hanglinye@gmail.com.
  • Rahul; Center for Modeling, Simulation and Imaging in Medicine (CeMSIM), Rensselaer Polytechnic Institute, Troy, NY, USA.
  • Kruger U; Center for Modeling, Simulation and Imaging in Medicine (CeMSIM), Rensselaer Polytechnic Institute, Troy, NY, USA.
  • Wang T; The Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA.
  • Shi S; The Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA.
  • Norfleet J; U.S. Army Futures Command, Combat Capabilities Development Command Soldier Center STTC, Orlando, FL, USA.
  • De S; Center for Modeling, Simulation and Imaging in Medicine (CeMSIM), Rensselaer Polytechnic Institute, Troy, NY, USA. Electronic address: des@rpi.edu.
Burns ; 47(4): 812-820, 2021 06.
Article in En | MEDLINE | ID: mdl-32928613
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Spectrum Analysis, Raman / Burns Type of study: Prognostic_studies Limits: Humans Language: En Journal: Burns Journal subject: TRAUMATOLOGIA Year: 2021 Document type: Article Country of publication: Países Bajos
Fulltext
Add to My VHL
Print
XML
PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Spectrum Analysis, Raman / Burns Type of study: Prognostic_studies Limits: Humans Language: En Journal: Burns Journal subject: TRAUMATOLOGIA Year: 2021 Document type: Article Country of publication: Países Bajos