AI RESEARCH
An Open Multi-Center Whole-Body FDG PET/CT Foundation Model for Tumor Segmentation
arXiv CS.CV
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ArXi:2605.21835v1 Announce Type: cross The synergistic interpretation of anatomical information from computed tomography (CT) and metabolic information from positron emission tomography (PET) is important to oncologic imaging. However, existing deep learning methods for PET/CT remain largely task-specific, are often trained on single-center cohorts, or adopt dual-branch fusion schemes that delay cross-modal interaction and underutilize early spatial correspondence between PET and CT.