Denoising techniques are fundamental in digital mammography, not only to improve image quality but also to reduce patient exposure to ionizing radiation. However, the effectiveness of noise filtering depends on the accurate modeling of noise sources and the understanding of the physical characteristics of the imaging system. In a previous work, our group presented a denoising pipeline that considers a Poisson-Gaussian noise model, which includes both electronic noise and spatially and signal-dependent quantum noise. However, this model did not consider the structural noise present in the image detector, also known as Photo Response Non-Uniformity (PRNU). PRNU correction can be especially important for mammography systems featuring cesium iodide (CsI) scintillators with amorphous silicon (a-Si) image detectors. Thus, in this work, we propose a method for correcting the PRNU in mammographic images prior to noise filtering. We analyzed the impact of including the PRNU correction method in a denoising pipeline designed for digital mammography. Our results indicate that correcting for structural noise improves the effectiveness of our denoising pipeline in terms of signal loss (Bias) by approximately 18%, especially in regions of higher intensity.