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Poulami Somanya Ganguly1, Daniël M Pelt1, Doga Gürsoy2

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Filtered backprojection and Fourier-based algorithms are standard for tomographic reconstruction. Optimizing filters reduces quantitative differences between software, enhancing reproducibility in scientific imaging.

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filter optimizationfiltered backprojectiongridrecsynchrotron tomographytomographic reconstruction

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Area of Science:

  • Image Reconstruction
  • Computational Imaging
  • Scientific Data Processing

Background:

  • Filtered backprojection and Fourier-based algorithms are widely used for tomographic dataset reconstruction due to their robustness and efficiency.
  • Variations in discretization and interpolation across different software packages lead to quantitative differences in reconstructed images, hindering reproducibility.
  • Ensuring reproducible experimental results across facilities and software is challenging due to these reconstruction discrepancies.

Purpose of the Study:

  • To propose a method for reducing quantitative differences in tomographic reconstructions obtained from different software.
  • To enhance the reproducibility of scientific results derived from tomographic imaging.
  • To develop implementation-adapted filters for analytical reconstruction algorithms.

Main Methods:

  • Developed a technique to optimize filters within analytical reconstruction algorithms.
  • Utilized a wrapper routine to compute implementation-adapted filters for black-box reconstruction software.
  • Validated the approach using simulated phantoms and real-world synchrotron data across multiple open-source implementations.

Main Results:

  • Optimized filters significantly reduce quantitative differences between reconstructions from different software packages.
  • Demonstrated the effectiveness of the approach on both simulated and experimental synchrotron tomography data.
  • Achieved quantitatively similar reconstructions by applying implementation-adapted filters.

Conclusions:

  • The proposed filter optimization method improves the quantitative similarity of tomographic reconstructions.
  • This approach serves as a crucial building block for establishing fully reproducible synchrotron tomography data processing pipelines.
  • Enhancing reproducibility in the reconstruction step is vital for reliable scientific discovery.