From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data

arXiv cs.AI · 6 hours ago

Researchers developed a zero-setup framework using a pretrained semantic segmentation network to automatically segment X-ray tomography images without manual thresholding or retraining for each new dataset. The framework generates segmentation masks within minutes of reconstruction and works across previously unseen datasets without user input. This enables rapid assessment of scan quality and material properties during ongoing experiments, supporting real-time beamline feedback and scalable scientific imaging workflows.