NEWS · RESEARCH · #386
SYNAPS-I fine-tunes Meta’s SAM 3 and DINOv3 to deliver near‑real‑time segmentation at DOE beamlines
The SYNAPS-I multi‑lab project led by Berkeley Lab fine-tuned Meta’s open‑source models (Segment Anything Model 3 and DINOv3) on DOE beamline imaging, then deployed the pipeline across 300 A100 GPUs at national supercomputing facilities to produce semantically labeled 3D volumes in approximately 15 minutes. The system was demonstrated on micro‑CT scans of grapevine stems to automatically identify xylem vessels, shrinking a month‑long annotation task to minutes and enabling live experiment interpretation at the beamline.
KEY POINTS
- The SYNAPS-I multi‑lab project led by Berkeley Lab fine-tuned Meta’s open‑source models (Segment Anything Model 3 and DINOv3) on DOE beamline imaging, then deployed the pipeline across 300 A100 GPUs at national supercomputing facilities to produce semantically labeled 3D volumes in approximately 15 minutes.
- The system was demonstrated on micro‑CT scans of grapevine stems to automatically identify xylem vessels, shrinking a month‑long annotation task to minutes and enabling live experiment interpretation at the beamline.
- Turning months of expert image annotation into ~15‑minute, beamline‑side results can enable real‑time experiment steering and greatly accelerate scientific discovery across X‑ray and neutron facilities.
WHY IT MATTERS
Turning months of expert image annotation into ~15‑minute, beamline‑side results can enable real‑time experiment steering and greatly accelerate scientific discovery across X‑ray and neutron facilities.