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Research Notes

CT Dataset Collection: A Comprehensive Reference

A curated reference of 90+ publicly available CT datasets for medical and industrial imaging research, including download links, dataset sizes, and usage notes.

Published Updated 7 min read

Last Updated: February 2026 Total Datasets: 90+ publicly available datasets Coverage: Medical CT imaging, industrial CT non-destructive testing, surface defect detection

Warning: All datasets are for academic research purposes only. Always verify the license agreement and privacy policy before use. Commercial use requires explicit authorization.

📋 Table of Contents

  1. Medical CT Datasets
  2. Industrial CT and Defect Detection Datasets
  3. Comprehensive Resource Platforms
  4. Important Notes

🏥 Medical CT Datasets

Whole-Body Multi-Organ Segmentation

1. TotalSegmentator 系列

  • Name: TotalSegmentator / TotalSegmentator v2
  • Scale: 1204例 CT图像 (v1) / 1228例 (v2)
  • Annotations: 104个解剖结构 (v1) / 117个结构 (v2)
  • Split: 1082训练 + 57验证 + 65测试
  • Notes: 目前最大的三维医学图像分割数据集
  • Download: https://zenodo.org/records/10047292
  • GitHub: https://github.com/wasserth/TotalSegmentator
  • Paper: Wasserthal et al., Radiology: Artificial Intelligence, 2023

2. AbdomenCT-1K

Lung Datasets

3. LIDC-IDRI (肺图像数据库联盟)

  • Scale: 1018例 CT扫描
  • Notes: 诊断和肺癌筛查胸部CT，标注病灶
  • Annotations: 4位经验丰富的放射科医生标注
  • Applications: 肺癌检测和诊断CAD方法
  • Download: https://www.cancerimagingarchive.net/collection/lidc-idri/
  • Organized by: 美国国家癌症研究所(NCI)

4. MSD肺癌分割

5. LoLa11

6. StructSeg2019

7. QIN Lung CT

8. COVID-19 CT相关

9. 肺炎相关数据集

Liver Datasets

10. Sliver07

11. 3D-IRCADB

12. CHAOS (腹部器官)

13. MSD肝脏血管分割

  • Task: 肝脏和肝血管精细分割
  • Applications: 肝脏手术规划
  • Download: http://medicaldecathlon.com/
  • Source: Medical Segmentation Decathlon任务05

14. TCGA-LIHC

Brain Datasets

15. BraTS系列

  • Name: BraTS 2013/2015/2021等
  • Task: 脑肿瘤分割和生存分析
  • Modality: MR (主要)
  • Scale: 400+ 例患者
  • Challenge: MICCAI年度挑战
  • Download: https://www.med.upenn.edu/cbica/brats/

16. Kaggle RSNA-MICCAI Brain Tumor

17. MSD脑肿瘤分割

18. MSD海马体分割

Abdominal Organ Datasets

20. FLARE 2022 (Fast Abdominal Lesion Recognition)

  • Scale: 2300例 CT (50例标注+2000例无标注+50验证+200测试)
  • Source: 20+ 医学中心
  • Task: 13种腹部器官分割
  • Notes: 跨中心、多供应商、多模态、多期、多疾病
  • Challenge: MICCAI 2022
  • Website: https://flare22.grand-challenge.org/Dataset/

21. AMOS 2022 (Abdominal Multi-Organ Segmentation)

22. WORD (Whole abdominal Organs Recognition in CT)

23. RAOS dataset

  • Website: https://github.com/Luoxd1996/RAOS
  • Note: RAOS real CT dataset unzip password: "RAOS@2023"; synthetic MRI: "raos@2023". MICCAI2024 accepted; cite WORD (MedIA2023) when using.

24. Pancreas-CT

25. Kidney-Tumor (KiTS)

Chest CT Datasets

27. CT-RATE (Chest CT Reports And Text)

  • Scale: 50,188例 (47,149训练+3,039验证)
  • Notes: 第一个包含CT图像、诊断报告、异常标签的大规模数据集
  • Patients: 21,304例不同患者
  • Annotations: 18种异常条件
  • Time span: 2015年5月 - 2023年1月
  • Download: https://huggingface.co/datasets/ibrahimhamamci/CT-RATE

28. RAD-ChestCT

29. Chest CT-Scan Images

30. CheXpert

  • Scale: 224K图像 + 36M文本token
  • Annotations: 肺部、胸部、心脏疾病
  • Download: Stanford AIMI

31. MIMIC-CXR

  • Scale: 377,110张胸部X光 (227,835例研究)
  • Notes: DICOM格式，带自由文本放射报告；满足HIPAA Safe Harbor要求
  • Download: https://physionet.org/content/mimic-cxr/2.1.0/
  • Note: 需要request，需要导师的reference

Other Organ Segmentation

32. SegRap 2023 (头颈部)

  • Scale: 200例 CT
  • Annotations: 45类头颈部危险器官 + 2类鼻咽癌和淋巴结
  • Applications: 头颈癌放射治疗规划
  • Website: https://segrap2023.grand-challenge.org/
  • Challenge: MICCAI 2023

33. HaN-Seg (Head and Neck)

34. ToothFairy 2023 (牙科)

35. Colon-CT & 肠道相关

37. 椎间盘与脊椎相关

🏭 Industrial CT and Defect Detection Datasets

Non-Destructive Testing Datasets

38. 2DeteCT (2D可扩展实验CT)

39. LoDoPaB-CT

40. 医学MNIST-3100

41. CBCTLiTS (合成CBCT肝脏)

🌐 Comprehensive Resource Platforms

Key GitHub Projects

Project URL Coverage
Awesome-Medical-Dataset https://github.com/openmedlab/Awesome-Medical-Dataset 100+ datasets, CT/MRI/X-ray/ultrasound/pathology
医学影像数据集集锦 https://github.com/linhandev/dataset 71+ datasets, Chinese descriptions
Awesome-Medical-Image-Segmentation-Dataset https://github.com/ziyangwang007/Awesome-Medical-Image-Segmentation-Dataset 200+ segmentation datasets
Medical-Imaging-Datasets https://github.com/m-aryayi/Medical-Imaging-Datasets With license and download info

Data Access Platforms

76. The Cancer Imaging Archive (TCIA)

77. Grand Challenges

78. Kaggle医学影像数据集

79. Zenodo学术数据库

80. OpenDataLab

83. Medical Segmentation Decathlon

  • URL: http://medicaldecathlon.com/
  • Scale: 10个不同分割任务
  • 器官: 脑、心脏、肝脏、肺、胰腺、胰腺肿瘤、肠膜肿瘤、脾脏、骶骨、结肠

📌 Important Notes

Data Usage Guidelines

Danger: All datasets are for academic research purposes only. Strictly comply with each dataset's license agreement. Commercial use requires explicit authorization.

HIPAA Privacy Protection:

  • Medical data has been de-identified
  • Complies with HIPAA Safe Harbor requirements
  • Does not contain protected health information (PHI)

Citation Guidelines:

  • Always cite the original paper when using a dataset
  • Provide data source and institutional acknowledgment

Data Type Notes

Characteristic Medical CT Industrial CT
Format DICOM or NIfTI (.nii.gz) PNG, JPG, TIFF, or proprietary
Resolution 512×512 or higher 200×200 to 4096×4096
Slice thickness Typically 1–5 mm Varies by application
Annotations 3D segmentation masks Segmentation masks or bounding boxes

🔧 Common Tools

Category Tools
Visualization ITK-SNAP, 3D Slicer
Python processing SimpleITK, MONAI, pydicom, nibabel
Data augmentation imgaug, albumentations
Format conversion dcmread (DICOM), nibabel (NIfTI)

Dataset Selection Guide

By Task:

  • Segmentation: TotalSegmentator, AMOS, FLARE series
  • Classification: ChestCT-Scan, COVID-CT
  • Detection: LIDC-IDRI, DeepLesion, KiTS

By Scale:

  • Large-scale (>1000 scans): TotalSegmentator, FLARE, CT-RATE
  • Medium-scale (100–1000): LiTS, LIDC-IDRI, BraTS
  • Small-scale (<100): Specific organs or rare diseases

Special Requirements:

  • Multi-modal: AMOS (CT+MRI), CHAOS
  • Multi-center: FLARE, AMOS, CT-RATE
  • Industrial/NDT: 2DeteCT, LoDoPaB-CT

🔗 Quick Links

Resource URL
Awesome-Medical-Dataset https://github.com/openmedlab/Awesome-Medical-Dataset
TCIA https://www.cancerimagingarchive.net/
Grand Challenges https://grand-challenge.org/
OpenDataLab https://opendatalab.com/
TotalSegmentator https://zenodo.org/record/6802614
LIDC-IDRI https://www.cancerimagingarchive.net/collection/lidc-idri/
CT-RATE https://huggingface.co/datasets/ibrahimhamamci/CT-RATE

Last updated: February 2026 — 90+ datasets indexed. Part of my CT reconstruction research notes series.

Disclaimer: This document is for academic reference only. All dataset copyrights belong to their respective institutions. Before using any dataset, confirm compliance with its license agreement and privacy policy.

Tags

  • #Medical Imaging

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