Filtered back projection (FBP) has been the standard CT image reconstruction method for 4
decades. A simple, fast, and reliable technique, FBP has delivered high-quality images in …

Abstract Purpose of Review Deep Learning reconstruction (DLR) is the current state-of-the-
art method for CT image formation. Comparisons to existing filter back-projection, iterative …

Background An iterative reconstruction (IR) algorithm was introduced for clinical photon-
counting detector (PCD) CT. Purpose To investigate the image quality and the optimal …

Computed tomography (CT) dramatically improved the capabilities of diagnostic and
interventional radiology. Starting in the early 1970s, this imaging modality is still evolving …

Background CT deep learning reconstruction (DLR) algorithms have been developed to
remove image noise. How the DLR affects image quality and radiation dose reduction has …

Background Accurate CT attenuation and diagnostic quality of virtual noncontrast (VNC)
images acquired with photon-counting detector (PCD) CT are needed to replace true …

Objective Iterative reconstruction degrades image quality. Thus, further advances in image
reconstruction are necessary to overcome some limitations of this technique in low-dose …

There have been substantial advances in computed tomography (CT) technology since its
introduction in the 1970s. More recently, these advances have focused on image …

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 …

Objectives To compare image noise and sharpness of vessels, liver, and muscle in lower
extremity CT angiography between “adaptive statistical iterative reconstruction-V”(ASIR-V) …