Automated Extraction of Skin Wound Healing Biomarkers From In Vivo Label-Free Multiphoton Microscopy Using Convolutional Neural Networks.

The CNNs trained and presented in this study can accurately segment MPM imaged wound sections and in vivo z-stacks to enable automated and rapid calculation of wound geometry and metabolism. Although MPM is a noninvasive imaging modality well suited to imaging living wound tissue, its use has been limited by time-intensive user segmentation. The use of CNNs for automated image segmentation demonstrate that it is possible for MPM to deliver near real-time quantitative readouts of tissue structure and function. Lasers Surg. Med. © 2021 Wiley Periodicals LLC.