AI RESEARCH
Cross-Source Supervision for Bone Infection Segmentation in Dual-Modality PET-CT
arXiv CS.LG
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ArXi:2605.16373v1 Announce Type: cross Early and accurate diagnosis and lesion localization of bone infections are crucial for clinical treatment. PET-CT integrates anatomical information from CT with metabolic information from PET, making it an important imaging modality for diagnosing bone infections. However, accurate lesion segmentation remains challenging due to indistinct lesion boundaries and inconsistencies in annotations generated by different experts or automated systems. In this work, we investigate multimodal segmentation of bone infections under annotation discrepancy.