Data and code underlying the publication: "Framework for evaluating photon-counting detectors under pile-up conditions"

This repository contains the data and code for our paper<br>David Leibold, Stefan J. van der Sar, Marlies C. Goorden, Dennis R. Schaart, Framework for evaluating photon-counting detectors under pile-up conditions, <em style="background-color:rgb(255, 250, 234);">J. Med. Imag.</em> <strong style="background-color:rgb(255, 250, 234);">11</strong>(S1), S12802 (2024), doi: 10.1117/1.JMI.11.S1.S12802. <br>The objective of the publication is a framework that aims to evaluate PCDs under pile-up conditions by employing a small-signal analysis. In this repository you will find the raw data of energy depositions in a pixel array obtained via Monte-Carlo simulations (stored as .root files), the Python scripts for performing the pulse train analysis and the calculation of the perturbation point spread function, as well as the Python scripts for creating the plots shown in the abovementioned publication, along with the actual plots (.png, .pdf) and the plotted data (.npy files). For an in-depth description of this repository we refer to the REAMDE.md file, which can be opened with any text editor. It also contains instructions for setting up a Python environment with all required dependencies, and instructions for using the scripts performing the pulse train analysis.

本仓库包含对应学术论文的数据与代码。论文作者为David Leibold、Stefan J. van der Sar、Marlies C. Goorden、Dennis R. Schaart，题为《脉冲堆积条件下光子计数探测器的评估框架（Framework for evaluating photon-counting detectors under pile-up conditions）》，发表于《医学成像杂志》（*J. Med. Imag.*）**11(S1)**，页码S12802（2024年），DOI：10.1117/1.JMI.11.S1.S12802。
本研究的核心目标是构建一套评估框架，通过小信号分析实现脉冲堆积条件下光子计数探测器（Photon-Counting Detectors, PCDs）的性能评估。本仓库涵盖如下内容：通过蒙特卡洛模拟得到的像素阵列能量沉积原始数据（存储为.root格式文件）；用于执行脉冲序列分析与扰动点扩散函数计算的Python脚本；用于复现上述论文中所有图表的Python脚本，同时附带生成的图表文件（.png、.pdf格式）与绘图原始数据（.npy格式文件）。
如需深入了解本仓库的详细说明，请查阅README.md文件，该文件可通过任意文本编辑器打开，其中还包含了配置包含所有依赖项的Python运行环境的步骤，以及脉冲序列分析脚本的使用指南。