Aug 23, 2022 · Abstract. Spectral computed tomography (Spectral CT) has attracted more and more attention because of its ability of material discrimination.
This paper presents a direct multi-material reconstruction method, in which a deep convolutional neural network (CNN)-based prior is incorporated into the ...
The method consists of 4 steps. First, horizontal contour images of the object was extracted from the sliced images. Second, vertical contour curves are ...
A direct multi-material reconstruction method, in which a deep convolutional neural network (CNN)-based prior is incorporated into the optimization model, ...
A full-spectral Bayesian reconstruction approach based on the material decomposition model applied in dual-energy computed tomography. C. Cai, ...
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Apr 12, 2023 · This paper proposes a one-step multi-material reconstruction model as well as an iterative proximal adaptive decent method.
Inspired by deep learning, here we first develop a deep learning based reconstruction method; i.e., U-net with L p p -norm, Total variation, Residual learning, ...
In this study, we proposed a multi-material decomposition method for spectral CT via FC-DenseNets. Spectral data were acquired by the photon-counting detector ...
Missing: Prior | Show results with:Prior
In this paper, we first propose a variational model for the limited-angle computed tomography (CT) image reconstruction and then convert the model into an end- ...
Apr 25, 2014 · We propose a penalized-likelihood (PL) method with edge-preserving regularizers for each material to reconstruct multi-material images using a similar ...
Missing: Deep | Show results with:Deep