Data and code underlying the publication: ''Optimising proton stopping power ratio prediction with spectral cone-beam CT''

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.

本仓库包含我们发表论文的相关数据与代码：David Leibold、Dennis R. Schaart 与 Marlies C. Goorden，《基于光谱锥束CT优化质子阻止本领比预测》，刊载于《物理医学与生物学期刊》（Phys. Med. Biol.），第70卷第14期，第145023页，2025年，DOI: 10.1088/1361-6560/adebd6。本论文的核心目标为对比多种光谱锥束CT（spectral cone-beam CT）装置在质子治疗领域的适用性，更具体地说，是评估其预测质子阻止本领比（proton stopping power ratio）的能力。本仓库中收录了本文中展示的全部实验数据，以及用于生成这些数据的Python代码。如需了解更多详细信息，请查阅README.txt文件，该文件可通过任意文本编辑器打开。