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Updated: Feb 7, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
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Technical Note: Retrospective reduction in systematic differences across scanner changes by accounting for noise

Ken Sakaie1, Xiaopeng Zhou1, Jian Lin1

  • 1Imaging Institute, Cleveland Clinic Main Campus, Mail Code U-15, Cleveland, OH, 44195, USA.

Medical Physics
|July 13, 2018
PubMed
Summary

Retrospective correction for noise floor effects in diffusion tensor imaging (DTI) can improve measurement consistency across scanner changes. This noise floor rectification enhances DTI data reliability for neurological disease studies.

Keywords:
diffusion tensor imaging (DTI)noise floorscanner upgrade

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Area of Science:

  • Medical Imaging
  • Neuroimaging
  • Biophysics

Background:

  • Scanner configuration changes introduce systematic differences in quantitative MRI, impacting biological interpretation.
  • Noise floor rectification is a potential source of systematic differences in diffusion tensor imaging (DTI).

Purpose of the Study:

  • To assess if retrospective noise floor correction reduces systematic differences and improves DTI reproducibility after major scanner changes.
  • To evaluate the impact of noise floor rectification on quantitative MRI measures.

Main Methods:

  • Healthy volunteers underwent DTI scanning before and after a major scanner upgrade at four sites.
  • DTI measures of tissue microstructure were computed using standard and maximum likelihood estimation (MLE) approaches, with and without noise floor correction.
  • Voxelwise systematic differences and reproducibility were assessed.

Main Results:

  • Noise floor correction reduced systematic differences and improved reproducibility, particularly when the signal-to-noise-floor ratio (SNFR) was below 3.
  • However, noise floor correction had a detrimental effect at high signal levels.

Conclusions:

  • Accounting for noise floor effects enhances the robustness of DTI measurements during scanner transitions.
  • This improved reliability of DTI is crucial for longitudinal studies of neurological diseases.