# TSGCNet

**Repository Path**: ai-models-cn/TSGCNet

## Basic Information

- **Project Name**: TSGCNet
- **Description**: No description available
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-07-16
- **Last Updated**: 2024-08-14

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Two-Stream Graph Convolutional Network for Intra-Oral Scanner Image Segmentation

## Prequisites
* python 3.7.4
* pytorch 1.4.0
* numpy 1.19.0
* plyfile 0.7.1

## Introduction
This work is the pytorch implementation of **TSGCN**, which has been published in IEEE Transactions on Medical Imaging (https://ieeexplore.ieee.org/abstract/document/9594785/) and CVPR 2021 (https://openaccess.thecvf.com/content/CVPR2021/html/Zhang_TSGCNet_Discriminative_Geometric_Feature_Learning_With_Two-Stream_Graph_Convolutional_Network_CVPR_2021_paper.html).
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## Usage
To train the TSGCN, please put the trainning data and testing data into data/train and data/test, respectively. Then, you can start to train a TSGCN model by following command.

```shell
python train.py
```
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## Citation
If you find our work useful in your research, please cite:
* Y. Zhao et al., "Two-Stream Graph Convolutional Network for Intra-Oral Scanner Image Segmentation," in IEEE Transactions on Medical Imaging, vol. 41, no. 4, pp. 826-835, April 2022, doi: 10.1109/TMI.2021.3124217.
* Zhang L, Zhao Y, Meng D, et al. TSGCNet: Discriminative Geometric Feature Learning with Two-Stream Graph Convolutional Network for 3D Dental Model Segmentation[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021: 6699-6708.