Visual search, a vital task for humans and animals, has also become a common and
important tool for studying many topics central to active vision and cognition ranging from …

Breast imaging is largely indicated for detection, diagnosis, and clinical management of
breast cancer and for evaluation of the integrity of breast implants. In this work, a prospective …

Purpose We aimed to thoroughly characterize image quality of a novel deep learning image
reconstruction (DLIR), and investigate its potential for dose reduction in abdominal CT in …

Purpose To assess the dose performance in terms of image quality of filtered back projection
(FBP) and two generations of iterative reconstruction (IR) algorithms developed by the most …

We determined contrast thresholds for lesion detection as a function of lesion size in both
mammograms and filtered noise backgrounds with the same average power spectrum …

We consider detection of a nodule signal profile in noisy images meant to roughly simulate
the statistical properties of tomographic image reconstructions in nuclear medicine. The …

Measuring the dependence of visual sensitivity on parameters of the visual stimulus is a
mainstay of vision science. However, it is not widely appreciated that visual sensitivity is a …

How we see is today explained by physical optics and retinal transduction, followed by
feature detection, in the cortex, by a bank of parallel independent spatial-frequency-selective …

Purpose To assess the effect of radiation dose reduction on low-contrast detectability by
using an advanced modeled iterative reconstruction (ADMIRE; Siemens Healthcare …

Purpose The purpose of this study was to compare the effect of two deep learning image
reconstruction (DLR) algorithms in chest computed tomography (CT) with different clinical …