Iterative reconstruction in X-ray fluorescence tomography based on radon inversion

Area of Science:

• Medical Imaging
• Computational Physics
• Tomographic Reconstruction

Background:

• X-ray fluorescence computed tomography (XFCT) requires accurate image reconstruction.
• Existing inversion algorithms for the generalized attenuated radon transform in XFCT have limitations in speed and image quality.

Purpose of the Study:

• To develop a novel and efficient approach for the inversion of the generalized attenuated radon transform in XFCT.
• To improve the accuracy and speed of XFCT image reconstruction.

Main Methods:

• Utilized the radon inverse as an initial approximation, followed by iterative refinement.
• Developed a novel alternating method for direct attenuation map retrieval from emission data.
• Applied and compared the approach to real and simulated XFCT data.

Main Results:

• The proposed method yields better image quality compared to existing analytic methods.
• The approach demonstrates significantly faster computation times than traditional iterative methods in the discrete setting.
• Successfully reconstructed attenuation maps directly from emission data.

Conclusions:

• The new inversion approach offers a superior balance of image quality and computational efficiency for XFCT.
• This method provides a valuable advancement for XFCT data analysis and image generation.