What step in digital image processing identifies the useful exposure values ("values of interest") in raw image data?

The identification of useful exposure values, often referred to as "values of interest," in raw image data is primarily achieved through histogram analysis. This process involves analyzing the distribution of pixel values in the image.

In digital radiography, each pixel in the image corresponds to a specific intensity value that represents the level of X-ray attenuation. By creating a histogram of these pixel values, we can visually assess the range and distribution, highlighting the areas that hold significant diagnostic information. The "values of interest" typically correspond to the region of the histogram where these important exposure values lie.

The histogram helps in determining optimal image processing parameters, such as windowing and leveling, for enhancing the visibility of anatomical structures while suppressing noise and irrelevant data. Thus, histogram analysis is fundamental in ensuring that the subsequent image processing steps are effective and focused on the clinically relevant portions of the image.