"Normal" is not a verdict

"Normal" is not a finding. It is a verdict, and a radiograph cannot deliver it.

I write reports on medical images every day, and I wrote the label contract for the model I train on my own reads. One rule sits at the top of both. A read is about this image, never about the patient's health. "Not detectable on this image" is a sentence I can defend. "Healthy" is not.

A panoramic radiograph is a shadow of a curved slice through the jaws, drawn by a beam that moves. What lies outside the slice blurs or vanishes. The edge of a cortex depends on where the beam met it. Some structures are not on the image at all, whatever a report says about them. So the honest read has two parts: what the image shows, and what this image cannot rule out. The second part is where a specialist earns the signature.

Two habits I hold the model to, because I hold myself to them.

Commit. A competent read names definite findings and reserves "this image cannot show" for the few structures where it is true, never as a general hedge. Hedging everything is not caution. It is a report that says nothing and cannot be wrong.

Never end a finding with "otherwise normal". The phrase launders a real finding into a clean report, and a model learns the laundering faster than the finding.

"Normal" is the cheapest word a model can learn, because normal needs no seeing. An AI read that can only say normal or abnormal is not a read. It has no room for the line that says what this image cannot show, and that line is the part a clinician is for.

The check

Three lines that make a negative read honest:

1. "Not detectable on this image." Never "absent". The image is the limit of the claim.
2. Name the structures this projection cannot show, once, in a fixed place in the report, not scattered as hedges.
3. State the finding, then the negatives, separately. Never close a finding with "otherwise normal".