In DR, what is the relationship between SNR and CNR?

• A. SNR and CNR describe signal quality and contrast relative to noise, affecting detectability.
• B. SNR measures spatial resolution, while CNR measures color depth.
• C. SNR and CNR only impact exposure time.
• D. SNR equals CNR.

Answer: (A)

In DR, SNR and CNR describe signal quality and contrast relative to noise, which directly affects how detectable structures are on an image. SNR is the average signal level divided by the level of random noise in a region, so a higher SNR means the true signal stands out more clearly. CNR takes this a step further by looking at the difference in signal between a feature and its background, scaled by the noise, which tells you how well you can distinguish that feature from surrounding tissue. Because noise obscures subtle differences, both higher SNR and higher CNR improve detectability of structures. They’re related but not the same: SNR coats the overall signal quality, while CNR specifically measures contrast between two areas in the presence of noise. Increasing dose or improving detector performance can raise both values up to practical and safety limits. The other statements misstate what these metrics measure—SNR and CNR aren’t about spatial resolution or color depth, aren’t solely about exposure time, and they aren’t equal to each other.