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 …

Artificial intelligence (AI) continues to garner substantial interest in medical imaging. The
potential applications are vast and include the entirety of the medical imaging life cycle from …

This review highlights recent efforts on applying electron microscopy (EM) to soft (including
biological) nanomaterials. We will show how developments of both the hardware and …

Since the introduction of artificial intelligence (AI) in radiology, the promise has been that it
will improve health care and reduce costs. Has AI been able to fulfill that promise? We …

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

Objectives Radiologists' perception is likely to influence the adoption of artificial intelligence
(AI) into clinical practice. We investigated knowledge and attitude towards AI by radiologists …

Research into artificial intelligence (AI) has made tremendous progress over the past
decade. In particular, the AI-powered analysis of images and signals has reached human …

Purpose To characterize the noise and spatial resolution properties of a commercially
available deep learning‐based computed tomography (CT) reconstruction algorithm …

GE Healthcare's deep learning image reconstruction (DLIR) is the first Food and Drug
Administration (FDA) cleared technology to utilize a deep neural network-based recon …