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QUANTITATIVE METRICS FOR BENCHMARKING MEDICAL IMAGE HARMONIZATION.

Abhijeet Parida1, Zhifan Jiang1, Roger J Packer1

  • 1Children's National Hospital, Washington, DC, USA.

Proceedings. IEEE International Symposium on Biomedical Imaging
|January 12, 2026
PubMed
Summary
This summary is machine-generated.

We developed new metrics to evaluate medical image harmonization without needing ground truth data. These metrics help standardize performance assessment for different imaging techniques.

Keywords:
BenchmarkingDomain TranslationMRI HarmonizationMetrics

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Area of Science:

  • Medical Imaging
  • Image Processing
  • Quantitative Analysis

Background:

  • Medical image harmonization addresses domain shifts from diverse acquisition protocols.
  • Benchmarking harmonization techniques is difficult due to the lack of standardized ground truth datasets.

Purpose of the Study:

  • To propose novel, ground truth-free metrics for evaluating medical image harmonization.
  • To assess the utility of these metrics in real-world scenarios.

Main Methods:

  • Developed two intensity harmonization metrics and one anatomy preservation metric.
  • Validated metrics against established image quality assessment metrics using a dataset with ground truth.
  • Demonstrated application in scenarios lacking ground truth.

Main Results:

  • Proposed metrics show correlation with established image quality assessment metrics.
  • Metrics are applicable to real-world medical imaging harmonization tasks without ground truth.
  • Provided interpretation guidelines for metric values.

Conclusions:

  • Advocate for the adoption of these quantitative harmonization metrics.
  • These metrics can serve as a standard for benchmarking harmonization technique performance.
  • Facilitates more reliable evaluation of medical image harmonization.