Core clinical engineering and protocols for Wound Care Computer Vision.
Traditionally, nurses evaluate diabetic foot ulcers and pressure injuries using disposable paper rulers and subjective visual estimation. Inter-observer variability often exceeds 30%, making it difficult to ascertain whether a wound is truly responding to treatment.
HealthRecognition applies UNet++ segmentation networks to color-calibrated photos. The AI segments individual tissue types down to the pixel level, calculating exact percentages of necrotic vs. healthy granulation tissue and computing automated surface area and volume, providing clinicians with objective healing curves.