A hybrid VAE with architectural annealing learns discrete clusters aligned with scanner and protocol differences in a dataset of 7416 structural connectomes spanning 13 studies.
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Large-scale structured visual QC on dMRI pipelines shows that upstream processing failures can propagate undetected and that QC granularity must match each algorithm's spatial output structure.
citing papers explorer
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Unsupervised learning of acquisition variability in structural connectomes via hybrid latent space modeling
A hybrid VAE with architectural annealing learns discrete clusters aligned with scanner and protocol differences in a dataset of 7416 structural connectomes spanning 13 studies.
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Large-Scale Deployment and Analytical Implications of Structured Quality Control in Diffusion Magnetic Resonance Imaging
Large-scale structured visual QC on dMRI pipelines shows that upstream processing failures can propagate undetected and that QC granularity must match each algorithm's spatial output structure.