Spectral computed tomography (CT) imaging encompasses a unique generation of CT
systems based on a simple principle that makes use of the energy-dependent information …

Over the past decade, spectral or dual‐energy CT has gained relevancy, especially in
oncological radiology. Nonetheless, its use in the radiotherapy (RT) clinic remains limited …

Background Accurate CT attenuation and diagnostic quality of virtual noncontrast (VNC)
images acquired with photon-counting detector (PCD) CT are needed to replace true …

The purpose of this study was to evaluate virtual-non contrast reconstructions of Photon-
Counting Detector (PCD) CT-angiography datasets using a novel calcium-preserving …

Handcrafted and deep learning (DL) radiomics are popular techniques used to develop
computed tomography (CT) imaging-based artificial intelligence models for COVID-19 …

Detection and characterization of adrenal lesions have evolved during the past two
decades. Although the role of imaging in adrenal lesions associated with hormonal …

Our objective was to develop and evaluate the clinical feasibility of deep-learning-based
synthetic contrast-enhanced computed tomography (DL-SynCCT) in patients designated for …

The present study evaluates the diagnostic reliability of virtual non-contrast (VNC) images
acquired with the first photon counting CT scanner that is approved for clinical use by …

Objectives To assess epicardial adipose tissue (EAT) volume and attenuation of different
virtual non-contrast (VNC) reconstructions derived from coronary CTA (CCTA) datasets of a …

Objective: To evaluate the performance of virtual non-contrast images (VNC) compared to
true non-contrast (TNC) images in photon-counting detector computed tomography (PCD …