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Software Article: A generalized cascaded linear system model implementation for x-ray detectors.

Gustavo Pacheco1, Juan J Pautasso1, Koen Michielsen1

  • 1Dept. of Medical Imaging, Radboudumc, Nijmegen, The Netherlands.

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|September 4, 2025
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Summary
This summary is machine-generated.

We developed CASYMIR, an open-source Python package for modeling x-ray imaging detectors. This tool enables accurate simulation of Modulation Transfer Function (MTF) and Noise Power Spectrum (NPS), aiding system optimization.

Keywords:
X‐ray detectorsflat‐panel detectorimage qualityparallel cascaded models

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Area of Science:

  • Medical Imaging Physics
  • Computational Imaging
  • Detector Modeling

Background:

  • Cascaded linear models are crucial for x-ray imaging system development.
  • Existing Python implementations for these models are lacking.
  • Accurate modeling of detector performance is essential for image quality.

Purpose of the Study:

  • Introduce CASYMIR, a novel, open-source Python package for simulating x-ray imaging detectors.
  • Provide a flexible tool for modeling both direct and indirect conversion detectors.
  • Enable computation of Modulation Transfer Function (MTF) and Noise Power Spectrum (NPS) across various acquisition conditions.

Main Methods:

  • Modular software design utilizing generalized frequency-domain expressions.
  • Modeling of individual detection processes as serial or parallel blocks.
  • Derivation of gain factors and parameters from user-defined detector characteristics, system geometry, and x-ray spectra.

Main Results:

  • Experimental validation with a-Se and CsI detectors showed high accuracy.
  • Modeled MTF errors below 6% and normalized NPS errors below 3% for a-Se detectors.
  • Modeled MTF errors of 5.4% and normalized NPS errors of 5.8% for CsI detectors.

Conclusions:

  • CASYMIR offers a flexible and accurate solution for x-ray detector modeling.
  • The open-source package facilitates integration into simulation pipelines and virtual clinical trials.
  • Ideal for optimizing x-ray system design and acquisition techniques through batch simulations.