Pacheco Gustavo, Pautasso Juan J, Michielsen Koen, Sechopoulos Ioannis
Dept. of Medical Imaging, Radboudumc, Nijmegen, The Netherlands.
Dutch Expert Centre for Screening (LRCB), Nijmegen, The Netherlands.
Med Phys. 2025 Sep;52(9):e18079. doi: 10.1002/mp.18079.
Cascaded linear models are widely used for the development and optimization of x-ray imaging systems, yet no publicly available Python implementation currently exists. We introduce CASYMIR, a flexible and open-source Python package capable of modeling direct and indirect-conversion x-ray imaging detectors under various acquisition conditions.
We employed a modular software design with generalized frequency-domain expressions for each process in the detection chain, which can be implemented as serial or parallel blocks. The gain factors and other parameters are derived from the detector's characteristics, system geometry, and incident x-ray spectra, all of which can be specified by the user. The signal reaching the detector is propagated throughout the detection stages by applying these process blocks, enabling the computation of the Modulation Transfer Function (MTF) and Noise Power Spectrum (NPS) at any stage of the model.
Our implementation was experimentally validated using two commercial x-ray detectors: a flat-panel a-Se detector for digital mammography and digital breast tomosynthesis, and a flat-panel scintillator (CsI) detector for dedicated breast CT. The modeled MTF had root-mean-square (RMS) percent errors below 6% for the a-Se detector, while the normalized RMS error for the NNPS was below 3%. For the CsI detector, the RMS percent error in the MTF was 5.4%, and the normalized RMS error for the NNPS was 5.8%.
The CASYMIR Python package can be downloaded from https://github.com/radboud-axti/casymir_public, and it includes a standalone executable script suitable for modeling common commercial systems, along with an extensive README file and example files.
CASYMIR is available as an open-source Python package under the MIT license. Given its modular and flexible structure, it can be easily modified and integrated into other simulation/virtual clinical trial pipelines where information about the detector's spatial resolution and noise performance is needed. The standalone version of CASYMIR may be particularly useful for running batch simulations with varying acquisition and system parameters, making it ideal for optimizing system design and acquisition techniques. Furthermore, given the package's modular structure, new processes can be implemented to simulate other detector and system designs.
级联线性模型广泛应用于X射线成像系统的开发与优化,但目前尚无公开可用的Python实现。我们引入了CASYMIR,这是一个灵活的开源Python包,能够在各种采集条件下对直接转换和间接转换X射线成像探测器进行建模。
我们采用模块化软件设计,对检测链中的每个过程使用广义频域表达式,这些表达式可以实现为串行或并行模块。增益因子和其他参数源自探测器特性、系统几何结构和入射X射线光谱,所有这些均可由用户指定。通过应用这些过程模块,到达探测器的信号在整个检测阶段进行传播,从而能够在模型的任何阶段计算调制传递函数(MTF)和噪声功率谱(NPS)。
我们使用两款商用X射线探测器对我们的实现进行了实验验证:一款用于数字乳腺摄影和数字乳腺断层合成的平板非晶硅探测器,以及一款用于专用乳腺CT的平板闪烁体(碘化铯)探测器。对于非晶硅探测器,建模的MTF的均方根(RMS)百分比误差低于6%,而NNPS的归一化RMS误差低于3%。对于碘化铯探测器,MTF的RMS百分比误差为5.4%,NNPS的归一化RMS误差为5.8%。
CASYMIR Python包可从https://github.com/radboud-axti/casymir_public下载,它包括一个适用于对常见商用系统进行建模的独立可执行脚本,以及一份详尽的自述文件和示例文件。
CASYMIR以开源Python包的形式在MIT许可下提供。鉴于其模块化和灵活的结构,它可以轻松修改并集成到其他需要探测器空间分辨率和噪声性能信息的模拟/虚拟临床试验流程中。CASYMIR的独立版本对于运行具有不同采集和系统参数的批量模拟可能特别有用,使其成为优化系统设计和采集技术的理想选择。此外,鉴于该包的模块化结构,可以实现新的过程来模拟其他探测器和系统设计。