Objectives Deep learning reconstruction (DLR) is a new reconstruction method; it introduces
deep convolutional neural networks into the reconstruction flow. This study was conducted …

The control provided by digital displays over how visual information is presented to readers
has the potential to improve reading for each and every reader, regardless of ability or …

In oncology, the feasibility of Cerenkov luminescence imaging (CLI) has been assessed by
imaging superficial lymph nodes in a few patients undergoing diagnostic 18F-fluoro-2 …

Purpose To evaluate the effect of a deep learning–based reconstruction (DLR) method on
the conspicuity of hypovascular hepatic metastases on abdominal CT images. Materials and …

Objectives The aim of this study was to investigate potential benefits of ultra-high resolution
(UHR) over standard resolution scan mode in ultra-low dose photon-counting detector CT …

Objectives We evaluated lower dose (LD) hepatic dynamic ultra-high-resolution computed
tomography (U-HRCT) images reconstructed with deep learning reconstruction (DLR) …

Background Ex vivo lung perfusion (EVLP) has improved the process of donor lung
management. Cytokine accumulation during EVLP has been shown to correlate with worse …

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

Purpose Deep learning reconstruction (DLR) introduces deep convolutional neural networks
into the reconstruction flow. We examined the clinical applicability of drip-infusion …

An iconic recent moment in the English Premier League was the final day of the 2011/2012
season, where Manchester City needed a win to secure the title but trailed Queens Park …