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Data support for: "Regularization by Denoising Sub-sampled Newton Method for Spectral CT Multi-Material Decomposition" - MaRDI portal

Data support for: "Regularization by Denoising Sub-sampled Newton Method for Spectral CT Multi-Material Decomposition" (Q6704530)

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Dataset published at Zenodo repository.
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Data support for: "Regularization by Denoising Sub-sampled Newton Method for Spectral CT Multi-Material Decomposition"
Dataset published at Zenodo repository.

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    Theprovided spectral CT data accompanies the following publication: A. Perelli, M. S. Andersen, Regularization by Denoising Sub-sampled Newton Methodfor Spectral CT Multi-Material Decomposition, Philosophical Transactions A, 2021 The dataset provides raw energy-resolved CT projections for thephantom considered in the paper which consists of iodine cylinder materials of different concentration. The spectral CT data isacquired through a photon-counting CT scannerat DTU Physics. The repository contains the following files: HER_acq19-02-13-16-01-00.h5: real spectral CT projections and meta data obtained through the prototype scanner at DTU Physics. Main_Spectral_CT_Dataset.m: Matlab files to load and processthe CT projections andforreconstruction. fan_vec_vustom.m: fucntion to create the appropriate CT geometry for the ASTRA Toolbox The MATLAB reconstruction code accompanying the paper is available in the following GitHub repository: https://github.com/alperelli/Denoising-IHS The following Matlab toolbox is required for performing FBP or SIRT reconstruction. ****************** Software Requirement *********************** This script upload the spectral CT data, post-process the data toinsertgaps and generate the ASTRA operator. As option, the SIRT reconstruction can be performed. This code requires the ASTRA Toolbox installed: https://github.com/astra-toolbox/astra-toolbox W. van Aarle, W. J. Palenstijn, J. Cant, E. Janssens, F. Bleichrodt,A. Dabravolski, J. De Beenhouwer, K. J. Batenburg, and J. Sijbers,Fast and Flexible X-ray Tomography Using the ASTRA Toolbox,Optics Express, 24(22), 25129-25147, (2016) http://dx.doi.org/10.1364/OE.24.025129 ********************************************************************
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    8 February 2021
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