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 …

The spectral computed tomography (CT) system based on a photon-counting detector (PCD)
can quantitatively analyze the material composition of the inspected object by material …

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 …

Background Dual‐energy CT with virtual noncalcium (VNCa) images allows the evaluation
of focal intramedullary bone marrow involvement in patients with multiple myeloma …

Objective: Dual energy CT (DECT) has been shown to estimate stopping power ratio (SPR)
map with a higher accuracy than conventional single energy CT (SECT) by obtaining the …

Background Compared with single-energy computed tomography (CT), dual-energy CT
(DECT) can distinguish materials better. However, most DECT reconstruction theories …

Cone-beam CT (CBCT) is installed in the treatment room to facilitate online clinical
applications, including image guidance in radiation and surgery. Half-fan and short-can are …

Objective. Cone beam CT (CBCT) in preclinical small animal irradiation platforms provides
essential information for image guidance and radiation dose calculation for experiment …

BACKGROUND: Dual-energy computed tomography (DECT) is a widely used and actively
researched imaging modality that can estimate the physical properties of an object more …

In this work, we applied the singular value decomposition (SVD) method to a set of
monochromatic images to extract the dominant physical contributions to image formation …