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Related Experiment Videos

Selection of a convolution function for Fourier inversion using gridding [computerised tomography application].

J I Jackson1, C H Meyer, D G Nishimura

  • 1Magnetic Resonance Syst. Res. Lab., Stanford Univ., CA.

IEEE Transactions on Medical Imaging
|January 1, 1991
PubMed
Summary
This summary is machine-generated.

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This study compares image artifacts from different gridding kernel functions used in MRI data processing. Researchers identified a novel convolving function that can improve image quality in specific situations.

Area of Science:

  • Medical Imaging
  • Signal Processing

Background:

  • Gridding is essential for reconstructing images from undersampled MRI data.
  • Artifacts can arise during gridding due to the convolution and resampling process.

Purpose of the Study:

  • To evaluate and compare image artifacts generated by various gridding convolving functions.
  • To identify a convolving function that minimizes artifacts more effectively than existing methods.

Main Methods:

  • Data samples were weighted by sampling density and convolved with finite kernels.
  • Comparison of artifacts from Kaiser-Bessel window and zero-order prolate spheroidal wave function (PSWF).
  • Development and testing of a novel convolving function.

Main Results:

Related Experiment Videos

  • Different convolving functions produce varying degrees of image artifacts.
  • The Kaiser-Bessel window and PSWF were evaluated for artifact generation.
  • A new convolving function demonstrated improved performance in certain scenarios.

    • Conclusions:

    • The choice of convolving function significantly impacts image artifact levels in gridding.
    • A novel convolving function offers potential for improved image reconstruction quality in MRI.