README.md

metadata

license: gpl-2.0
task_categories:
  - image-segmentation
tags:
  - medical-imaging
  - ct
  - kidney
  - segmentation

CT2USforKidneySeg

CT (source-domain) slices with kidney segmentation masks used in Song et al., "CT2US: Cross-modal transfer learning for kidney segmentation in ultrasound images with synthesized data." Ultrasonics 122 (2022) 106706. DOI: 10.1016/j.ultras.2022.106706.

Mirror of the public Kaggle release siatsyx/ct2usforkidneyseg.

Contents

• 4586 paired samples at 256x256, single split train.
• image: grayscale CT slice (PNG, 8-bit).
• mask: kidney segmentation mask (PNG, 8-bit; mostly binary with minor anti-aliasing artifacts; threshold at 127 to recover the binary label).
• id: original Kaggle filename stem (non-contiguous, drawn from multiple CT volumes).

License

GPL-2.0 (per the original Kaggle dataset).

Citation

@article{song2022ct2us,
  title   = {CT2US: Cross-modal transfer learning for kidney segmentation in ultrasound images with synthesized data},
  author  = {Song, Yuxin and Zheng, Jing and Lei, Long and Ni, Zihan and Zhao, Baoliang and Hu, Ying},
  journal = {Ultrasonics},
  volume  = {122},
  pages   = {106706},
  year    = {2022},
  doi     = {10.1016/j.ultras.2022.106706}
}