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TotalSegmentator

The TotalSegmentator dataset is a radiology image-segmentation dataset with 1228 3D images and corresponding masks with 117 different anatomical structures. It can be used for segmentation and multilabel classification tasks.

Raw data

Key stats
Modality Vision (radiology, CT scans)
Task Segmentation / multilabel classification (117 classes)
Data size total: 23.6GB
Image dimension ~300 x ~300 x ~350 (number of slices) x 1 (grey scale) *
Files format .nii ("NIFTI") images
Number of images 1228
Splits in use one labeled split

/* image resolution and number of slices per image vary

Organization

The data Totalsegmentator_dataset_v201.zip from zenodo is organized as follows:

Totalsegmentator_dataset_v201
├── s0011                               # one image
│   ├── ct.nii.gz                       # CT scan
│   ├── segmentations                   # directory with segmentation masks
│   │   ├── adrenal_gland_left.nii.gz   # segmentation mask 1st anatomical structure
│   │   ├── adrenal_gland_right.nii.gz  # segmentation mask 2nd anatomical structure
│   │   └── ...
└── ...

Download and preprocessing

  • The dataset class TotalSegmentator supports download the data on runtime with the initialized argument download: bool = True.
  • For the multilabel classification task, every mask with at least one positive pixel it gets the label "1", all others get the label "0".
  • For the multilabel classification task, the TotalSegmentator class creates a manifest file with one row/slice and the columns: path, slice, split and additional 117 columns for each class.
  • The 3D images are treated as 2D. Every 25th slice is sampled and treated as individual image
  • The splits with the following sizes are created after ordering images by filename:
Splits Train Validation Test
#Samples 737 (60%) 246 (20%) 245 (20%)

License

Creative Commons Attribution 4.0 International