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Annotating thousands of objects in 3D microscopy volumes is now 100x faster, enabling promptable segmentation workflows at unprecedented scale.
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.