DenseNucleiDet

The Code for "Position-based anchor optimization for point supervised dense nuclei detection"

Requirements

• Linux (Windows is not officially supported)
• Python 3.5+ (Python 2 is not supported)
• PyTorch 1.1 or higher
• CUDA 9.0 or higher
• NCCL 2
• GCC(G++) 4.9 or higher
• mmcv

Train a dataset in COCO format

./tools/dist_train.sh ${CONFIG_FILE} ${GPU_NUM} [optional arguments]

Test a dataset in COCO format

./tools/dist_test.sh ${CONFIG_FILE} ${CHECKPOINT_FILE} ${GPU_NUM} [--out ${RESULT_FILE}] [--eval ${EVAL_METRICS}]

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Citation

Please consider citing our paper in your publications if the project helps your research.

@article{yao2024position,
  title={Position-based anchor optimization for point supervised dense nuclei detection},
  author={Yao, Jieru and Han, Longfei and Guo, Guangyu and Zheng, Zhaohui and Cong, Runmin and Huang, Xiankai and Ding, Jin and Yang, Kaihui and Zhang, Dingwen and Han, Junwei},
  journal={Neural Networks},
  volume={171},
  pages={159--170},
  year={2024},
  publisher={Elsevier}
}