Answers are grounded in this paper and cite their sources.
Observational analysis of tumor segmentation accuracy in FDG-PET imaging, indicating improvements through predictive models that account for disease burden.
These results are consistent with previous reports on PET-based segmentation, further validating nnU-Net as a reliable approach for detecting hypermetabolic lesions and assessing global disease burden in FDG-PET imaging. Moreover, the significant relationship between TBR and segmentation accuracy suggests the possibility of further improvements by integrating metabolic profile into the predictive model.
No takes yet. Share an insight, caveat, or question.
Donatella Masciale (2025) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: