Feb. 6, 2024, 5:47 a.m. | Vincent Roca Gr\'egory Kuchcinski Jean-Pierre Pruvo Dorian Manouvriez Renaud Lopes

cs.LG updates on arXiv.org arxiv.org

In MRI studies, the aggregation of imaging data from multiple acquisition sites enhances sample size but may introduce site-related variabilities that hinder consistency in subsequent analyses. Deep learning methods for image translation have emerged as a solution for harmonizing MR images across sites. In this study, we introduce IGUANe (Image Generation with Unified Adversarial Networks), an original 3D model that leverages the strengths of domain translation and straightforward application of style transfer methods for multicenter brain MR image harmonization. IGUANe …

acquisition aggregation brain cs.ai cs.cv cs.lg cyclegan data deep learning hinder image images imaging mri multiple sample solution studies study translation

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