Purpose The purpose of this study was to assess the impact of the new artificial intelligence
deep-learning reconstruction (AI-DLR) algorithm on image quality and radiation dose …

Objectives To determine the best compromise between low radiation dose and suitable
image quality for the detection of lytic and sclerotic bone lesions of the lumbar spine and …

OBJECTIVE. Previous advances over filtered back projection (FBP) have incorporated
model-based iterative reconstruction. The purpose of this study was to characterize the latest …

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 …

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

Purpose To compare the impact on CT image quality and dose reduction of two versions of a
Deep Learning Image Reconstruction algorithm. Material and methods Acquisitions on the …

Background New reconstruction algorithms based on deep learning have been developed
to correct the image texture changes related to the use of iterative reconstruction algorithms …

Background Two deep learning image reconstruction (DLIR) techniques from two different
computed tomography (CT) vendors have recently been introduced into clinical practice …

Purpose: To assess the physical performance of deep learning image reconstruction (DLIR)
compared with those of filtered back projection (FBP) and iterative reconstruction (IR) and to …

Objectives: To evaluate image quality and lesion detection capabilities of low-dose (LD)
portal venous phase whole-body computed tomography (CT) using deep learning image …