Scanner-agnostic MRI harmonization via SSIM-guided disentanglement
IntroductionThe variability introduced by differences in MRI scanner models, acquisition protocols, and imaging sites hinders consistent analysis and generalizability across multicenter studies.MethodsWe present a novel image-based harmonization framework for 3D T1-weighted brain MRI, which disentangles anatomical content from scanner- and site-specific variations. The model incorporates a differentiable loss based on the Structural Similarity Index Measure (SSIM) to preserve biologically meanin
Record details
Published: 10 August 2026
Source: Frontiers in Artificial Intelligence
Category: Research
Topics: Biotech
Retrieved: 11 August 2026
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ethics.ai (10 August 2026), “Scanner-agnostic MRI harmonization via SSIM-guided disentanglement,” evidence record 18077, https://ethics.ai/record/18077 (originally published by Frontiers in Artificial Intelligence).
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