Urinary Sediment Dataset

a dataset consisting of 5,376 annotated images corresponding to 7 categories of urinary sediment particle

• cast
• cryst (crystals)
• epith (epithelial cell)
• epithn (epithelial nuclei)
• eryth (erythrocyte)
• leuko (leukocyte)
• mycete

Format

The dataset is in the PASCAL VOC format.

/VOCdevkit
└── Urinary Sediment Dataset
    ├── Annotations
    ├── ImageSets
    │   └── Main
    │       ├── test.txt
    │       ├── train.txt
    │       └── val.txt
    └── JPEGImages

• train set: 4256 images
• val set: 852 images
• test set: 268 images

Downloading Dataset

https://drive.google.com/drive/folders/18VqmoqK7dVSdxiyEE6qCfIpS8UOqqIBS?usp=sharing

Citing Dataset

If you find Dataset useful in your research, please consider citing:

@article{liang2018object,
  title={Object detection based on deep learning for urine sediment examination},
  author={Liang, Yixiong and Tang, Zhihong and Yan, Meng and Liu, Jianfeng},
  journal={Biocybernetics and Biomedical Engineering},
  volume={38},
  number={3},
  pages={661--670},
  year={2018},
  publisher={Elsevier}
}

@article{liang2018end,
  title={An End-to-End System for Automatic Urinary Particle Recognition with Convolutional Neural Network},
  author={Liang, Yixiong and Kang, Rui and Lian, Chunyan and Mao, Yuan},
  journal={Journal of medical systems},
  volume={42},
  number={9},
  pages={165},
  year={2018},
  publisher={Springer}
}

@INPROCEEDINGS{9054367, 
  author={M. {Yan} and Q. {Liu} and Z. {Yin} and D. {Wang} and Y. {Liang}}, 
  booktitle={ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, 
  title={A Bidirectional Context Propagation Network for Urine Sediment Particle Detection in Microscopic Images}, 
  year={2020}, 
  volume={}, 
  number={}, 
  pages={981-985}
}