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High-quality 3D biomedical instance segmentation is now possible in annotation-scarce domains, thanks to a biophysics-driven data synthesis pipeline that bridges the gap between synthetic and real microscopy data.
Automating deep learning pipeline design for 3D biomedical imaging slashes manual annotation effort by intelligently leveraging predicted segmentation instances for assisted classifier training.
