mlsanityData to 14 Oct 2026

Frozen Site-Probe Accuracy Is Not a Standalone Harmonization Score: An Audit of Evaluation Practice for Multi-Site MRI

arXiv 2610.14140 ↗First posted 9 Oct 2026eess.IV cs.CVcited by 0

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Abstract (arXiv)

Image-level MRI harmonization is often evaluated with a frozen site probe, a site classifier trained on raw scans and applied unchanged to harmonized ones: a drop in its accuracy is read as removal of site effects. We audit this practice on ABIDE I (1,112 T1-weighted scans, 17 sites) with ten output sets from seven harmonization methods and controls for chance, head shape, intensity, preprocessing and target alignment. We find that this verdict depends on how the probe is trained, even among probes that classify raw scans well: across random seeds, its balanced accuracy on the same CycleGAN outputs ranges from 0.13 to 0.59 (chance: 0.06). Low frozen-probe accuracy can also arise without harmonization: a Gaussian blur, which increases the intensity distance to the target site, lowers this accuracy to chance. Moreover, where the frozen probe fails, probes trained on the harmonized scans still recover the site, even from intensity histograms alone: on HACA3 outputs, the frozen probe scores 0.25, a probe trained on those outputs 0.75, and one using only their intensity histograms 0.71. Low frozen-probe accuracy therefore does not show that site information has been removed. We recommend reporting several probes trained to convergence, probes trained on harmonized scans, and target alignment.

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References · 12

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  3. 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,937
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  7. 2019Machine Learning with Multi-Site Imaging Data: An Empirical Study on the Impact of Scanner Effectscited by 43
  8. 2022HACA3: A Unified Approach for Multi-site MR Image Harmonizationcited by 18
  9. 2022Efficacy of MRI data harmonization in the age of machine learning. A multicenter study across 36 datasetscited by 6
  10. 2024Disentangled Latent Energy-Based Style Translation: An Image-Level Structural MRI Harmonization Frameworkcited by 5
  11. 2024Unpaired Volumetric Harmonization of Brain MRI with Conditional Latent Diffusioncited by 5
  12. 2024PRISM: Privacy-preserving Inter-Site MRI Harmonization via Disentangled Representation Learningcited by 1

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