Data and code underlying the publication: ''Optimising proton stopping power ratio prediction with spectral cone-beam CT''
DOI: 10.4121/bd754669-5af8-4e2d-9a70-37ac56bd6674
Datacite citation style
Dataset
This repository contains the data and code for our paper:
David Leibold, Dennis R. Schaart, and Marlies C. Goorden, "Optimising proton stopping power ratio prediction with spectral cone-beam CT", Phys. Med. Biol., vol. 70, no. 14, p. 145023, 2025, doi: 10.1088/1361-6560/adebd6.
The objective of the publication is a comparison of various spectral cone-beam CT setups in terms of their suitability for proton therapy, more specifically, their ability to predict proton stopping power ratios.
In this repository you can find the data that is presented in our paper, along with the Python code that was used to generate it. For more information please see the README.txt file, which can be opened with any text editor.
History
- 2025-07-17 first online, published, posted
Publisher
4TU.ResearchDataFormat
Raw data: .txt (Plain text) files. Simulation software: .py (Python) files. Auxiliary data: .npy (Numpy) files.Associated peer-reviewed publication
Optimising proton stopping power ratio prediction with spectral cone-beam CTFunding
- This research was partially funded by Varian, a Siemens Healthineers company, grant number 2018016.
Organizations
TU Delft, Faculty of Applied Sciences, Department of Radiation Science and TechnologyDATA
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scatter_data.zip - 24,570 bytesMD5:
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source_spectra_7deg.zip -
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