Background and purpose The use of AI in the process of CT image reconstruction may
improve image quality of resultant images and therefore facilitate low-dose CT …

CT, one of the most groundbreaking innovations of the 20th century, is an important
diagnostic tool that dictates treatment strategies and enables vital decision making in day-to …

Concerns over need for CT radiation dose optimization and reduction led to improved
scanner efficiency and introduction of several reconstruction techniques and image …

Background Recently, computed tomography (CT) manufacturers have developed deep‐
learning‐based reconstruction algorithms to compensate for the limitations of iterative …

The field of artificial intelligence (AI) is transforming almost every aspect of modern society,
including medical imaging. In computed tomography (CT), AI holds the promise of enabling …

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

CT reconstruction has undergone a substantial change over the last decade with the
introduction of iterative reconstruction (IR) and now with deep learning reconstruction (DLR) …

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

Objectives To assess the impact on image quality and dose reduction of a new deep
learning image reconstruction (DLIR) algorithm compared with a hybrid iterative …

Purpose To investigate the image quality and feasibility of a novel artificial intelligence
iterative reconstruction (AIIR) algorithm for aortic computer tomography angiography (CTA) …