Rebecca Rowlandhttps://orcid.org/0000-0002-8913-9599,1 Adrien Ponticorvo,1 Melissa Baldado,1 Gordon T. Kennedy,1 David M. Burmeister,2 Robert J. Christy,2 Nicole P. Bernal,3 Anthony J. Durkin1,4
1Beckman Laser Institute and Medical Clinic (United States) 2U.S. Army Institute of Surgical Research (United States) 3Univ. of California, Irvine Regional Burn Ctr. (United States) 4Univ. of California, Irvine (United States)
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
Assessment of burn severity is critical for wound treatment. Spatial frequency domain imaging (SFDI) has been previously used to characterize burns based on the relationships between histology and tissue optical properties. Recently, multispectral and hyperspectral imaging optical features have been combined with machine learning to classify burn severity. Here, we investigated the use of SFDI reflectance data at multiple wavelengths and spatial frequencies, with a support vector machine (SVM), to predict severity in a porcine model of graded burns. Burn severity predictions using SVM were compared to burn grade determined using histology techniques. Results suggest that the combination of spatial frequency data with machine learning models has the potential for accurately predicting burn severity at the 24 hr postburn time point.
Rebecca Rowland,Adrien Ponticorvo,Melissa Baldado,Gordon T. Kennedy,David M. Burmeister,Robert J. Christy,Nicole P. Bernal, andAnthony J. Durkin
"A simple burn wound severity assessment classifier based on spatial frequency domain imaging (SFDI) and machine learning", Proc. SPIE 10851, Photonics in Dermatology and Plastic Surgery 2019, 1085109 (26 February 2019); https://doi.org/10.1117/12.2510670
ACCESS THE FULL ARTICLE
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
The alert did not successfully save. Please try again later.
Rebecca Rowland, Adrien Ponticorvo, Melissa Baldado, Gordon T. Kennedy, David M. Burmeister, Robert J. Christy, Nicole P. Bernal, Anthony J. Durkin, "A simple burn wound severity assessment classifier based on spatial frequency domain imaging (SFDI) and machine learning," Proc. SPIE 10851, Photonics in Dermatology and Plastic Surgery 2019, 1085109 (26 February 2019); https://doi.org/10.1117/12.2510670