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Point-and-Capture Wound Imaging: Auto-Measurement Without a Ruler

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How computer vision measures length, width, depth, and tissue composition from a single phone capture — and why disposable rulers are finally optional.

Rulers were the compromise. They work, but they contaminate the field, they slow the visit, and they produce measurements that vary by clinician. Point-and-capture imaging replaces the ruler with computer vision that measures the wound from a single phone photo.

How it works

The camera detects the wound boundary, calibrates scale from depth sensors or a reference marker, and computes length, width, surface area, and depth in seconds. Tissue composition — granulation, slough, eschar — is segmented and quantified as a percentage of the wound bed.

Why it matters clinically

Inter-rater variability is the silent problem in wound care. When Clinician A measures 4.2 × 3.1 cm and Clinician B measures 5.0 × 3.5 cm on the same wound two days apart, the healing trajectory is meaningless. Consistent auto-measurement makes percent area reduction a real signal.

Where it fits the workflow

Capture happens during the encounter, not after. The measurement flows directly into the AI-powered EMR, attaches to the SOAP note the AI scribe is writing, and feeds the healing dashboard for trajectory analysis.

What clinicians give up

Manual override is still there — you can correct a boundary the model got wrong. But the default is measurement in under five seconds, no ruler, no manual entry.

See how point-and-capture wound imaging works.