WiseSeg: weakly supervised whole-body PET/CT segmentation of 147 anatomical structures

Whole‑body organ segmentation is critical for radiotherapy planning and systemic disease assessment, but existing PET/CT‑tailored segmentation methods suffer from insufficient anatomical coverage, severe annotation bottlenecks, and an unfavorable trade‑off between accuracy and speed, limiting their clinical translation. To address these issues, we developed a weakly supervised framework for whole‑body segmentation of 147 anatomical structures on PET/CT and established normative SUV reference ranges in healthy individuals. This retrospective study included 2308 18 F‑FDG PET/CT scans from two hospitals and 1746 public CT scans. Model development used 1846 scans for pseudo‑label training (1746 public CT + 100 PET/CT) and 2000 unlabeled PET/CT scans for weakly supervised learning; independent testing used 110 PET/CT scans. A healthy cohort of 98 individuals was included to establish normal SUV reference ranges. An uncertainty‑guided pseudo‑label learning algorithm was trained to segment 147 anatomical structures. Dice scores were calculated between model predictions and expert annotations. Paired t‑tests or Wilcoxon tests with Bonferroni correction were used for statistical analysis. The model achieved a mean Dice score of 0.874 across 147 structures on the test set, with segmentation completed within 120 s per scan. For 113 structures matched to TotalSegmentator, it outperformed TotalSegmentator (0.895 vs. 0.884; P < 0.001). The uncertainty-weighting strategy improved segmentation of small vascular structures (0.702 vs. 0.651; P < 0.001). The model also showed a lower absolute deviation in the 95th-percentile SUV (SUV 95 ; 0.018 vs. 0.021) than TotalSegmentator in PET quantification. Normal SUV reference ranges for 147 structures were established from the healthy cohort. The proposed weakly supervised framework enables precise and efficient whole-body segmentation of 147 structures on PET/CT. The established normal SUV reference ranges provide a standardized benchmark for quantitative PET/CT interpretation. The source code and pretrained weights are publicly available at https://github.com/Wpx01/WiseSeg .