In digital mammography, the physics of the acquisition system and post-processing algorithms can cause image noise to be spatially correlated. Noise correlation is characterized by non-constant noise power spectral density and can negatively affect image quality. Although the literature explores ways to quantify the frequency dependence of noise in digital mammography, there is still a lack of studies that explore the effect of this phenomenon on clinical tasks. Thus, the aim of this work is to evaluate the impact of noise correlation on the quality of digital mammography and the detectability of lesions using a virtual clinical trial (VCT) tool. Considering the radiographic factors of a standard full-dose acquisition, VCT was used to generate two sets of images: one containing mammograms corrupted with correlated noise and the other with uncorrelated (white) noise. Clusters of five to seven microcalcifications of different sizes and shapes were computationally inserted into the images at regions of dense tissue. We then designed a human observer study to investigate performance on a clinical task of locating microcalcifications on digital mammography from both image sets. In addition, nine objective image quality metrics were calculated on mammograms. The results obtained with four medical physicists showed that the average performance in localization was 72% for images with correlated noise and 95% with uncorrelated noise. Thus, our results suggest that correlated noise promotes a greater reduction in the conspicuity of subtle microcalcifications than uncorrelated noise. Furthermore, only four of the nine objective quality metrics calculated in this work were consistent with the results of the human observer study, highlighting the importance of using appropriate metrics to assess the quality of corrupted images with correlated noise. The source code for our framework is publicly available at

The validation of many dose optimization methods in x-ray imaging requires clinical images from a range of signal-to-ratio regimes. This data is commonly generated through computer simulation. For this purpose, our group developed a method to simulate dose reduction for digital breast tomosynthesis. In the previous work, tests were performed in a system that features an amorphous selenium detector with minimal pixel correlation. In the current work, we evaluate the simulation performance in an amorphous silicon system, which yields a relevant pixel correlation. Signal and noise characteristics in real and simulated images were measured using the signal-to-noise ratio (SNR) and the normalized noise power spectrum (NNPS). The simulation method assessment was performed through the average relative error between simulated and real images. The SNR results point to an error of less than 2.5% between the images. The noise correlation influence was verified through the NNPS. The tests pointed to errors up to 55% between the real and simulated images when the correlation kernel is not considered, whereas the error considering the correlation kernel was kept around 5.5%. Therefore, the results show that the correlation kernel is a relevant factor to be considered when simulating amorphous silicon systems.

Neste pequeno trecho do meu trabalho, e não menos importante, gostaria de agradecer a todos que, de alguma maneira, me ajudaram durante esse trajetória, não só para a elaboração da pesquisa, mas também o apoio pessoal no geral.Aos meus pais, Evaldo e Myrla, por sempre confiarem em mim e me incentivando a ser sempre a minha melhor versão.Ao meu irmão, Thiago, por ser sempre um companheiro nas horas que mais precisei.A todos os meus familiares, sem exceção, que essa singela citação possa demonstrar minha enorme gratidão a cada um.A Bruna, por me ajudar a superar diversas etapas dessa caminhada, deixando minha vida mais leve e colorida.A todos da república, onde vivi o período da pesquisa, pelo companheirismo na convivência do dia a dia.Ao meu orientador, Marcelo, por sempre estar presente e disposto a ajudar e agregar ao meu conhecimento.A todos os membros do laboratório, que ao compartilhar os conhecimentos, enriquecem o trabalho de todos. O meu agradecimento a cada um pela enorme contribuição tanto pessoal quanto profissional.Por fim, a todos meus amigos que agregaram de alguma forma nessa caminhada e durante toda minha vida. ResumoBrandão, Renann Método para estimativa do ganho quântico do ruído Poisson não-estacionário a partir da imagem digital degradada. 119 p. Dissertação