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Objective <p>The Polar Fourier Transform (PFT) has been proposed as a direct alternative to gridding for reconstructing radially acquired MRI data. This study evaluates the feasibility of inline PFT implementation on a clinical MRI scanner and assesses its computational performance and image quality under acceleration.</p> Materials and methods <p>PFT was implemented as modular components within the Siemens Image Calculation Environment, using a recursive numerical Hankel transform. Phantom and in vivo brain datasets acquired with 2D radial trajectories were reconstructed using both PFT and vendor-supplied gridding. Reconstruction time, SNR, artifact behavior, and spatial resolution were assessed across multiple undersampling levels (up to 8 ×), using simulations and repeated scans.</p> Results <p>PFT was successfully integrated with a runtime of ~ 6–9 × acquisition time. It exhibited spatially variant behavior, concentrating resolution in central region while shifting undersampling-induced blurring outward. Compared to gridding, PFT reduced structured streaks and better preserved image quality under acceleration. Gradient delay artifacts were reduced by alternating spoke polarity. Notably, the pituitary gland and basilar artery remained visible at high acceleration, highlighting preserved central fidelity.</p> Discussion <p>PFT enables effective inline reconstruction for radial MRI and preserves image quality in small central regions of interest under aggressive undersampling—supporting dynamic and ROI-focused applications.</p>

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Polar Fourier transform in practice: its efficiency and characteristics in reconstructing radially acquired MRI images

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月12日

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  • Fatemeh Rastegar Jooybari,
  • Ali Aghaeifar,
  • Elham Mohammadi,
  • Klaus Scheffler,
  • Abbas Nasiraei-Moghaddam

摘要

Objective

The Polar Fourier Transform (PFT) has been proposed as a direct alternative to gridding for reconstructing radially acquired MRI data. This study evaluates the feasibility of inline PFT implementation on a clinical MRI scanner and assesses its computational performance and image quality under acceleration.

Materials and methods

PFT was implemented as modular components within the Siemens Image Calculation Environment, using a recursive numerical Hankel transform. Phantom and in vivo brain datasets acquired with 2D radial trajectories were reconstructed using both PFT and vendor-supplied gridding. Reconstruction time, SNR, artifact behavior, and spatial resolution were assessed across multiple undersampling levels (up to 8 ×), using simulations and repeated scans.

Results

PFT was successfully integrated with a runtime of ~ 6–9 × acquisition time. It exhibited spatially variant behavior, concentrating resolution in central region while shifting undersampling-induced blurring outward. Compared to gridding, PFT reduced structured streaks and better preserved image quality under acceleration. Gradient delay artifacts were reduced by alternating spoke polarity. Notably, the pituitary gland and basilar artery remained visible at high acceleration, highlighting preserved central fidelity.

Discussion

PFT enables effective inline reconstruction for radial MRI and preserves image quality in small central regions of interest under aggressive undersampling—supporting dynamic and ROI-focused applications.