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 …

Spectral computed tomography (CT) produces an energy-discriminative attenuation map of
an object, extending a conventional image volume with a spectral dimension. In spectral CT …

This paper proposes a deep learning-based denoising method for noisy low-dose
computerized tomography (CT) images in the absence of paired training data. The proposed …

Objective. In this work, a dedicated end-to-end deep convolutional neural network, named
as Triple-CBCT, is proposed to demonstrate the feasibility of reconstructing three different …

Objectives The aims of this study were to compare virtual monoenergetic images and
polyenergetic images reconstructed from unenhanced dual-layer detector computed …

Objective The aim of the study was to investigate the performance and diagnostic value of
metal artifact reduction in virtual monoenergetic images generated from dual-layer …

Goal: Spectral computed tomography (SCT) images reconstructed by an analytical approach
often suffer from a poor signal-to-noise ratio and strong streak artifacts when sufficient …

Gout is a common inflammatory arthropathy in adults, with the prevalence increasing in
males of older age. It occurs when monosodium urate (MSU) crystals are deposited in joints …

Purpose The purpose of this paper is to present an end‐to‐end deep convolutional neural
network to improve the dual‐energy CT (DECT) material decomposition performance …

X-ray spectrum plays a very important role in dual energy computed tomography (DECT)
reconstruction. Because it is difficult to measure x-ray spectrum directly in practice, efforts …