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X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
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Ray contribution masks for structure adaptive sinogram filtering.

Michael Balda1, Joachim Hornegger, Bjoern Heismann

  • 1Metrilus GmbH, 91052 Erlangen, Germany. michael.balda@metrilus.de

IEEE Transactions on Medical Imaging
|February 16, 2012
PubMed
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A new structure adaptive sinogram (SAS) filter effectively reduces computed tomography (CT) noise by 13.6% without impacting image quality. This advanced filtering method preserves essential details, enhancing diagnostic accuracy in medical imaging.

Area of Science:

  • Medical Imaging
  • Image Processing
  • Radiology

Background:

  • Patient dose in computed tomography (CT) is directly related to measurement noise.
  • Existing noise-reduction techniques, such as anisotropic diffusion and bilateral filters, are adapted for CT noise properties.
  • There is a need for filters that preserve image quality while reducing noise.

Purpose of the Study:

  • To introduce and evaluate a novel structure adaptive sinogram (SAS) filter for CT imaging.
  • To assess the SAS filter's ability to reduce noise while preserving image quality, including edge information and high-frequency components.
  • To demonstrate the filter's robustness against reconstruction artifacts and its performance across various contrast levels.

Main Methods:

  • Developed a structure adaptive sinogram (SAS) filter utilizing a point-based forward projector to create ray contribution masks (RCMs).

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  • Employed an enhanced bilateral filtering concept, replacing photometric similarity with structural similarity based on neighboring RCMs.
  • Evaluated filter performance using a high-resolution phantom, in vivo patient scans, a simulated phantom, and a simulated edge phantom.

    • Main Results:

    • The SAS filter achieved a 13.6% noise reduction without altering the modulation transfer function (MTF) or introducing artifacts.
    • Visual and quantitative assessments showed the SAS filter preserves edge information and high-frequency organ textures better than standard bilateral filters.
    • Noise reduction exceeded 80% for a simple edge phantom, with MTF fully preserved for contrasts of approximately 100 HU and above.

    Conclusions:

    • The SAS filter offers effective noise reduction in CT imaging while maintaining crucial image quality metrics.
    • Its structure-adaptive approach ensures preservation of fine details and high-frequency textures, outperforming standard filters.
    • The SAS filter demonstrates robustness and applicability across different imaging scenarios and contrast levels.