How WoundScribe Documents Granulation, Slough, and Surrounding Skin from a Single Photo

The wound bed description — how much granulation, how much slough, what the surrounding skin looks like — drives everything downstream: treatment choice, healing trajectory, and payer justification. WoundScribe automates that description from a single point-and-capture photo.

Tissue composition, not just a photo

AI-powered wound imaging segments the wound bed and estimates the percentage of granulation, slough, and eschar. For a DFU showing bright red-pink granulation with a small amount of yellow tissue, the model produces numeric percentages instead of subjective adjectives — the same numbers, visit to visit, regardless of which clinician is holding the phone.

Surrounding skin and periwound findings

The imaging agent also flags surrounding skin changes: erythema, maceration, callus, and skin tone-aware assessment of periwound inflammation. That matters for diabetic feet where a rim of redness or a thickening callus is often the earliest warning sign.

Length, width, depth, and undermining

Dimensions are extracted automatically. For clinicians who want the fundamentals, see Wound Measurement 101: Length, Width, Depth, and Undermining and the primer on Granulation Tissue Explained.

Feeding the healing trajectory

Each structured measurement flows into the Healing dashboard and Wound healing software, so a stalled DFU is flagged early rather than at week 12. That objectivity also strengthens documentation for Medicare audits, which increasingly expect measurable, time-stamped wound characteristics on every visit.