TDF-Net

This repository is an official implementation of the paper "TDF-Net: Trusted Dynamic Feature Fusion Network for Breast Cancer Diagnosis using Incomplete Multimodal Ultrasound."

Pengfei Yan, Wushuang Gong, Minglei Li, Jiusi Zhang, Xiang Li, Yuchen Jiang, Hao Luo, and Hang Zhou. (2024). TDF-Net: Trusted Dynamic Feature Fusion Network for breast cancer diagnosis using incomplete multimodal ultrasound. Information Fusion, 102592.

Dataset

We collected a multimodal ultrasound image dataset for classification in breast cancer, including 145 benign and 103 malignant cases. This dataset is available for only non-commercial use in research or educational purposes. As long as you use the dataset for these purposes, you can edit or process images in the dataset. (Note that the full dataset will be made publicly available upon the publication of the manuscript)

Code Usage

Installation

Requirements

Linux, CUDA>=11.3, GCC>=7.5.0
Python>=3.8
PyTorch>=1.11.0, torchvision>=0.12.0 (following instructions here)
Other requirements
```
pip install -r requirements.txt
```

Dataset preparation

Please organize the dataset as follows:

code_root/
└── 001/
      ├── BUS_1.jpg
      ├── DUS_1.jpg
      └── EUS_1.jpg

Training

For example, the command for the training TDF-Net is as follows:

python model_train.py

The configs in model_train.py or other files can be changed.

Evaluation

After obtaining the trained TDF-Net, then run the following command to evaluate it on the validation set:

python model_valid.py

Notes

The code of this repository is built on https://github.com/TimesXY/TDF_Net.

TimesXY / TDF_Net

readme