
This dataset comprises models for TotalSegmentator (TS2D) Tool (see Github).The model checkpoints have been trained on the v2.0.1 TotalSegmentator dataset and constitute the initial release (R001). The checkpoints were generated using nnU-Net, which is also used within TS2D for inference. Each model was trained on a specific subset of labels from the TotalSegmentator dataset.This release includes: Cardiac: 18 cardiovascular structures, trained using mean and max intensity images Muscles: 23 musculoskeletal structures, including the brain and spinal-cord, using mean and max intensity images Organs: 24 organ structures, using mean and max intensity images Ribs: 26 ribs, including sternum and costal-cartilages, using mean and max intensity images Vertebrae: 26 vertebrae, including the sacrum, using mean and max intensity images
TotalSegmentator, Segmentation, TS2D
TotalSegmentator, Segmentation, TS2D
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
