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 Ultra–low-dose (ULD) CT could facilitate the clinical implementation of large-
scale lung cancer screening while minimizing the radiation dose. However, traditional image …

The aim of this study was to characterize image quality and to determine the optimal strength
levels of a novel iterative reconstruction algorithm (quantum iterative reconstruction, QIR) for …

Innovations in CT have been impressive among imaging and medical technologies in both
the hardware and software domain. The range and speed of CT scanning improved from the …

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 …

Conventional reconstruction techniques, such as filtered back projection (FBP) and iterative
reconstruction (IR), which have been utilised widely in the image reconstruction process of …

Background and purpose Artificial intelligence (AI) is present in many areas of our lives.
Much of the digital data generated in health care can be used for building automated …

Objectives To assess the impact of a new artificial intelligence deep-learning reconstruction
(Precise Image; AI-DLR) algorithm on image quality against a hybrid iterative reconstruction …

Objective To determine the difference in CT values and image quality of abdominal CT
images reconstructed by filtered back-projection (FBP), hybrid iterative reconstruction (IR) …