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 …

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 …

Purpose: Iterative reconstruction (IR) algorithms have the potential to reduce radiation dose
in CT diagnostic imaging. As these algorithms become available on the market, a …

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

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

ABSTRACT The Filtered Back Projection (FBP) algorithm has been the standard algorithm
for image reconstruction in computed tomography (CT) for many years, but it creates …

Iterative reconstruction (IR) algorithms are the most widely used CT noise-reduction method
to improve image quality and have greatly facilitated radiation dose reduction within the …

Over the past two decades, technical innovations in computed tomography (CT) have
constantly extended its spectrum of clinical applications and made new radiodiagnostic …

Image reconstruction processing in computed tomography (CT) has evolved tremendously
since its creation, succeeding at optimizing radiation dose while maintaining adequate …

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 …