README.md

metadata

license: odc-by
task_categories:
  - image-segmentation
tags:
  - medical
  - ct
  - lung
  - covid
  - long-covid
  - segmentation
pretty_name: LongCIU
dataset_info:
  features:
    - name: slice_index
      dtype: int32
    - name: split
      dtype: string
    - name: image
      dtype: image
    - name: mask_staple
      dtype: image
    - name: overlay_staple
      dtype: image
    - name: mask_annotator1
      dtype: image
    - name: mask_annotator2
      dtype: image
    - name: mask_annotator3
      dtype: image
    - name: ggo_pixels_staple
      dtype: int32
    - name: consolidation_pixels_staple
      dtype: int32
  splits:
    - name: train
      num_bytes: 11546931
      num_examples: 30
    - name: val
      num_bytes: 7131799
      num_examples: 20
    - name: test
      num_bytes: 15555193
      num_examples: 40
  download_size: 34305458
  dataset_size: 34233923
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: val
        path: data/val-*
      - split: test
        path: data/test-*

Long COVID Iowa-UNICAMP (LongCIU)

Long COVID Iowa-UNICAMP dataset: 90 axial chest CT slices with manual segmentation of ground glass opacities (GGO) and parenchymal consolidations, independently annotated by three expert annotator pairs. Provides both the three individual annotations and a STAPLE consensus recommended as ground truth.

Overview

• Modality: CT (axial)
• Body part: Lung (GGO / consolidation in Long COVID patients)
• Samples: 90 axial CT slices (stacked along axis 2 of a single NIfTI volume)
• Classes: 0 = background, 1 = GGO, 2 = consolidation

Files

File	Description
longciu_img.nii.gz	Image volume (512, 512, 90) — each slice is an independent patient
longciu_STAPLE_tgt.nii.gz	Recommended ground truth (STAPLE consensus of the 3 annotators)
longciu_1_tgt.nii.gz	Annotator pair 1 mask (for inter-rater study)
longciu_2_tgt.nii.gz	Annotator pair 2 mask (for inter-rater study)
longciu_3_tgt.nii.gz	Annotator pair 3 mask (for inter-rater study)
longciu_medpseg_output.nii.gz	MedPSeg baseline model prediction (for comparison)
longciu_splits.json	Train / val / test split indices over slice axis
staple_pub_stats.json	STAPLE statistics published with the paper
README.txt	Original dataset README from the authors

Splits (indices into slice axis of longciu_img.nii.gz)

• train: 30 slices
• val: 20 slices
• test: 40 slices

License

Open Data Commons Attribution License (ODC-By) v1.0.

Citation

Carmo, D. S., Pezzulo, A. A, Villacreses, P. A., Comellas A. P., Eisenbeisz, M. L., Anderson, R. L., Van Dorin, S. E., Rittner, L., Lotufo, R. A., Gerard, S. E., Reinhardt, J. M., Comellas, A. P. (2024). Long COVID Iowa-UNICAMP [dataset]. University of Iowa. https://doi.org/10.25820/data.007301

Paper (Scientific Data, Nature, 2025): https://www.nature.com/articles/s41597-025-04709-2

Source code: https://github.com/MICLab-Unicamp/LongCIU