A model for studying the detectability of X-ray images using the representation of images in the primary visual cortex

Abstract

It is well known that the visual information represented in the simple cells of the primary visual cortex V1 is spatially localized, orientation-sensitive and bandpass-filtered. In addition, the visual information represented is subsampled. On the other hand, the methods used to assess image quality of x-ray systems performing detectability tasks are usually carried out in the spatial or image domain. This study examines the behavior of two observers, IBO and NPW, employed in the evaluation of imaging systems, in a domain that simulates the representation of visual information in V1 to gain a better understanding of the degree of optimization in human observer detectability tasks. The comparison of the two observers is conducted on images of a contrast-detail phantom and is performed in both the spatial and the wavelet domains. Furthermore, the study examines the covariance matrices of the noise. The strong covariance exhibited in the noise among neighboring pixels in the spatial domain results in covariance matrices with relatively high values outside the main diagonal, leading to significant differences between the NPW and IBO observers. In the transformed domain, the band-pass decimated filters have substantially reduced the covariance between neighboring pixels, resulting in the convergence of the detectability indices of both observers. The vast amount of information captured by the retina necessitates an optimization of informational nature. This strategy eliminates low-frequency correlations in the image, after bandpass filtering carried out by simple cells in V1. This loss of information could contribute to the suboptimal performance of the human observer. Interestingly, in V1 the differences between IBO and NPW observers are very small. Therefore, either NPW does not accurately represent the human observer in V1, or the human observer is close to optimal in this domain.