# DLGNet

**Repository Path**: snakecy/DLGNet

## Basic Information

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

## Statistics

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

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# DLGNet
DLGNet: A dual-branch lesion-aware network with the supervised Gaussian Mixture model for colon lesions classification in colonoscopy images

Our paper has been accepted by Medical Image Analysis.

## Training the Model

python train_test.py

train_dataset-root: Folder to which you downloaded and extracted the training data

val_datapath-root: Folder to which you downloaded and extracted the val data

record_path: The path where the training results are stored

model_path = The path where the model is stored

best_path = The path where the model with the best result on the validation set is stored

First go into the train_test and adapt all the paths to match your file system and the download locations of training and test sets.

Then python train_test.py to train your dataset.

## Citation

If you find the code useful for your research, please cite our paper.

Wang, Kai-Ni, et al. "DLGNet: A dual-branch lesion-aware network with the supervised Gaussian Mixture model for colon lesions classification in colonoscopy images." Medical Image Analysis 87 (2023): 102832.