The introduction of photon-counting detectors is expected to be the next major breakthrough
in clinical x-ray computed tomography (CT). During the last decade, there has been …

X‐ray imaging is the most widely used diagnostic imaging method in modern medicine and
several advanced forms of this technology have recently emerged. Iodinated molecules and …

Purpose Exploiting the x‐ray measurements obtained in different energy bins, spectral
computed tomography (CT) has the ability to recover the 3‐D description of a patient in a …

Purpose To develop a convolutional neural network (CNN) that can directly estimate
material density distribution from multi‐energy computed tomography (CT) images without …

Spectral CT using a photon counting x-ray detector (PCXD) shows great potential for
measuring material composition based on energy dependent x-ray attenuation. Spectral CT …

The proposed spectral CT method solves the constrained one-step spectral CT
reconstruction (cOSSCIR) optimization problem to estimate basis material maps while …

The state-of-the art for solving the nonlinear material decomposition problem in spectral
computed tomography is based on variational methods, but these are computationally slow …

In this paper, we consider the use of prior knowledge within neural networks. In particular,
we investigate the effect of a known transform within the mapping from input data space to …

Spectral computed tomography (CT) has recently emerged as an advanced version of
medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two …

Purpose We aim at developing a model‐based algorithm that compensates for the effect of
both pulse pileup (PP) and charge sharing (CS) and evaluates the performance using …