Published December 14, 2020 | Version v1
Dataset Open

CTPelvic1K Dataset

  • 1. Institute of Computing Technology, Chinese Academy of Sciences
  • 2. George Mason University
  • 3. Beijing Electronic Science and Technology Institute
  • 4. Beijing Jishuitan Hospital

Description

Annotations and new collected clinical data in CTPelvic1K dataset.

Details can be found in https://github.com/ICT-MIRACLE-lab/CTPelvic1K.

Files

Files (17.0 GB)

Name Size Download all
md5:d82eb3428e4121cb855ce93f898faaf2
2.1 MB Download
md5:c1a9c576dba087c08f3d92ea1bfc2e42
182.8 MB Download
md5:348173abc9296d93c6399da2de15847a
7.9 MB Download
md5:9f2466e4356e1873dddd4d7c2f87b229
6.9 MB Download
md5:299326c05f4b674e758dffb5a2a83f86
2.3 MB Download
md5:7696eb7c4da91f989d6842d7b422efd9
21.9 MB Download
md5:6b6121e3094cb97bc452db99dd1abf56
8.8 GB Download
md5:7dc3b2223ab8c618c746fe90ced299f6
6.0 GB Download
md5:d706d26ca3820165c6e883a3777a78a2
3.2 MB Download
md5:343a23eda059ad71c7bd2174016ee5fc
1.9 GB Download

Additional details

References

  • Pengbo Liu, Hu Han, Yuanqi Du, Heqin Zhu, Yinhao Li, Feng Gu, Honghu Xiao, Jun Li, Chunpeng Zhao, Li Xiao, Xinbao Wu, S. Kevin Zhou. Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Models. International Journal of Computer Assisted Radiology and Surgery (IJCARS) pp. 1-8 (2021).