The development and widespread adoption of iterative reconstruction (IR) algorithms for CT
have greatly facilitated the contemporary practice of radiation dose reduction during …

Objectives To assess image noise, diagnostic performance, and potential for radiation dose
reduction of photon-counting detector (PCD) computed tomography (CT) with quantum …

Objectives To compare deep learning (True Fidelity, TF) and partial model based Iterative
Reconstruction (ASiR-V) algorithm for image texture, low contrast lesion detectability and …

Objectives The aim of this study was to evaluate the optimal energy level of virtual
monoenergetic images (VMIs) from photon-counting detector computed tomography (CT) for …

Background Current CT quality control (QC) for low‐contrast detectability relies on visual
inspection and measurement of contrast‐to‐noise ratio (CNR). However, CNR numbers …

Model observers have a long history of success in predicting human observer performance
in clinically-relevant detection tasks. New 3D image modalities provide more signal …

Objectives To assess task-based image quality for two abdominal protocols on various CT
scanners. To establish a relationship between diagnostic reference levels (DRLs) and task …

Background Recent advances in computed tomography (CT) technology have considerably
improved the quality of CT images and reduced radiation exposure in patients. At present …

Currently, quality assurance measurements in mammography are performed on
unprocessed images. For diagnosis, however, radiologists are provided with processed …

Purpose: A recently proposed model observer mimics the foveated nature of the human
visual system by processing the entire image with varying spatial detail, executing eye …