Spectrum reconstruction method based on the detector response model calibrated by x-ray fluorescence

Area of Science:

• Medical Physics
• Spectroscopy
• Detector Physics

Background:

• Accurate spectral estimation is crucial for applications like spectral computed tomography.
• Reconstructing incident spectra requires addressing detector energy response and ill-posed reconstruction problems.
• Existing methods for obtaining detector response and spectral reconstruction have limitations.

Purpose of the Study:

• To develop a feasible method for obtaining detector energy response using an optimized parametric model for CdZnTe or CdTe detectors.
• To introduce a maximum likelihood-expectation maximization (MLEM) iterative algorithm for accurate incident spectrum reconstruction.
• To improve the accuracy of X-ray fluorescence (XRF) spectra compared to existing methods.

Main Methods:

• Developed an optimized parametric model for CdZnTe or CdTe detector energy response, inspired by XRF spectrum modeling.
• Implemented a maximum likelihood-expectation maximization (MLEM) iterative algorithm based on a Poisson noise model for spectrum reconstruction.
• Validated the method using simulation and experimental results.

Main Results:

• The proposed method effectively reconstructs incident spectra.
• Significantly increased the accuracy of XRF spectra compared to the spectrum stripping method.
• Demonstrated the feasibility and promising results of the developed approach.

Conclusions:

• The developed method provides an effective solution for accurate spectral estimation and reconstruction.
• The MLEM algorithm offers a robust approach to handle ill-posed reconstruction problems with noisy data.
• The study highlights the potential applicability of the proposed technique in various spectral applications.