Official PyTorch implementation of the paper entitled 'THISNet: Tooth Instance Segmentation on 3D Dental Models via Highlighting Tooth Regions'.
- install requirements
- Python >=3.6
- PyTorch = 1.8.0
- pymeshlab = 2022.2
- plyfile = 0.7.4
- conda env installation
conda env create -f environment.yml -n thisnet
You can train and test the model by running the following commands:
# Training steps:
python train.py
# Testing steps:
python test.py
If you have any technical questions, please contact:
- Wechat：lIpen9chen9
- E-mail: [email protected]
If you find THISNet is useful in your research or applications, please consider giving us a star 🌟 and citing THISNet by the following BibTeX entry.
@article{li2023thisnet,
title={THISNet: Tooth Instance Segmentation on 3D Dental Models via Highlighting Tooth Regions},
author={Li, Pengcheng and Gao, Chenqiang and Liu, Fangcen and Meng, Deyu and Yan, Yan},
journal={IEEE Transactions on Circuits and Systems for Video Technology},
page={5229-5241},
year={2023},
publisher={IEEE}
}
Our project is partially based on TSGCNet and SparseInst, and we sincerely thanks for their code and contribution to the community!
This code is only freely available for non-commercial research use. If you have other purpose, please contact:
- Chenqiang Gao
- E-mail: [email protected]
- Copyright: Chongqing University of Posts and Telecommunications