TY - JOUR
T1 - Wound Size Imaging
T2 - Ready for Smart Assessment and Monitoring
AU - Lucas, Yves
AU - Niri, Rania
AU - Treuillet, Sylvie
AU - Douzi, Hassan
AU - Castaneda, Benjamin
N1 - Publisher Copyright:
© 2021 by Mary Ann Liebert, Inc., publishers.
PY - 2021/11/1
Y1 - 2021/11/1
N2 - Significance: We introduce and evaluate emerging devices and modalities for wound size imaging and also promising image processing tools for smart wound assessment and monitoring. Recent Advances: Some commercial devices are available for optical wound assessment but with limited possibilities compared to the power of multimodal imaging. With new low-cost devices and machine learning, wound assessment has become more robust and accurate. Wound size imaging not only provides area and volume but also the proportion of each tissue on the wound bed. Near-infrared and thermal spectral bands also enhance the classical visual assessment. Critical Issues: The ability to embed advanced imaging technology in portable devices such as smartphones and tablets with tissue analysis software tools will significantly improve wound care. As wound care and measurement are performed by nurses, the equipment needs to remain user-friendly, enable quick measurements, provide advanced monitoring, and be connected to the patient data management system. Future Directions: Combining several image modalities and machine learning, optical wound assessment will be smart enough to enable real wound monitoring, to provide clinicians with relevant indications to adapt the treatments and to improve healing rates and speed. Sharing the wound care histories of a number of patients on databases and through telemedicine practice could induce a better knowledge of the healing process and thus a better efficiency when the recorded clinical experience has been converted into knowledge through deep learning.
AB - Significance: We introduce and evaluate emerging devices and modalities for wound size imaging and also promising image processing tools for smart wound assessment and monitoring. Recent Advances: Some commercial devices are available for optical wound assessment but with limited possibilities compared to the power of multimodal imaging. With new low-cost devices and machine learning, wound assessment has become more robust and accurate. Wound size imaging not only provides area and volume but also the proportion of each tissue on the wound bed. Near-infrared and thermal spectral bands also enhance the classical visual assessment. Critical Issues: The ability to embed advanced imaging technology in portable devices such as smartphones and tablets with tissue analysis software tools will significantly improve wound care. As wound care and measurement are performed by nurses, the equipment needs to remain user-friendly, enable quick measurements, provide advanced monitoring, and be connected to the patient data management system. Future Directions: Combining several image modalities and machine learning, optical wound assessment will be smart enough to enable real wound monitoring, to provide clinicians with relevant indications to adapt the treatments and to improve healing rates and speed. Sharing the wound care histories of a number of patients on databases and through telemedicine practice could induce a better knowledge of the healing process and thus a better efficiency when the recorded clinical experience has been converted into knowledge through deep learning.
KW - computer vision
KW - deep learning
KW - mobile health
KW - tissue classification
KW - wound size imaging
UR - http://www.scopus.com/inward/record.url?scp=85096840293&partnerID=8YFLogxK
U2 - 10.1089/wound.2018.0937
DO - 10.1089/wound.2018.0937
M3 - Review article
C2 - 32320356
AN - SCOPUS:85096840293
SN - 2162-1918
VL - 10
SP - 641
EP - 661
JO - Advances in Wound Care
JF - Advances in Wound Care
IS - 11
ER -