| --- |
| 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](https://doi.org/10.1016/j.ultras.2022.106706). |
|
|
| Mirror of the public Kaggle release |
| [siatsyx/ct2usforkidneyseg](https://www.kaggle.com/datasets/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} |
| } |
| ``` |
|
|
