Tractography from ex vivo dMRI is used as a generative prior to create synthetic patches that, when mixed with real data and domain randomization, train a U-Net to segment fiber bundles in tracer histology with 3x less manual annotation.
arXiv preprint arXiv:2407.01419 (2024) 4
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MaskGen improves domain generalization for biomedical image segmentation by using source intensities plus domain-stable foundation model representations with minimal added complexity.
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Tractography-Driven Synthetic Data Generation for Fiber Bundle Segmentation in Tracer Histology
Tractography from ex vivo dMRI is used as a generative prior to create synthetic patches that, when mixed with real data and domain randomization, train a U-Net to segment fiber bundles in tracer histology with 3x less manual annotation.
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Why Invariance is Not Enough for Biomedical Domain Generalization and How to Fix It
MaskGen improves domain generalization for biomedical image segmentation by using source intensities plus domain-stable foundation model representations with minimal added complexity.