A Survey of Wound Image Analysis Using Deep Learning: Classification, Detection, and Segmentation

Wounds not only harm the physical and mental health of patients, but also introduce huge medical costs. Meanwhile, there is a shortage physicians in some areas, clinical examinations are sometimes unreliable wound diagnosis. Reliable analysis great importance its diagnosis, treatment, care. Currently, deep learning has developed rapidly field computer vision imaging become most commonly used technique image analysis. This paper studies current research on analysis, including classification, detection, segmentation. We first review publicly available datasets from various research, study preprocessing methods Second, models different tasks (classification, segmentation) their applications types wounds (e.g., burns, diabetic foot ulcers, pressure ulcers) investigated. Finally, we discuss challenges using learning, provide an outlook development prospects.