deerta0103 / HiFuse

HiFuse: Hierarchical Multi-Scale Feature Fusion Network for Medical Image Classification

HiFuse

This repo. is the official implementation of HiFuse: Hierarchical Multi-Scale Feature Fusion Network for Medical Image Classification
Authors: Xiangzuo Huo, Gang Sun, Shengwei Tian, Yan Wang, Long Yu, Jun Long, Wendong Zhang and Aolun Li.
Enjoy the code and find its convenience to produce more awesome works!

Overview

HFF Block

Visual Inspection of HiFuse

Run

0. Requirements:

• python3
• pytorch 1.10
• torchvision 0.11.1

1. Training:

• Prepare the required images and store them in categories, set up training image folders and validation image folders respectively
• Run python train.py

2. Resume training:

• Modify parser.add_argument('--RESUME', type=bool, default=True) in python train.py
• Run python train.py

3. Testing:

• Run python test.py

TensorBoard

Run tensorboard --logdir runs --port 6006 to view training progress

Reference

Some of the codes in this repo are borrowed from:

• Swin Transformer
• ConvNeXt
• WZMIAOMIAO

Citation

If you find our paper/code is helpful, please consider citing:

@article{huo2024hifuse,
  title={HiFuse: Hierarchical multi-scale feature fusion network for medical image classification},
  author={Huo, Xiangzuo and Sun, Gang and Tian, Shengwei and Wang, Yan and Yu, Long and Long, Jun and Zhang, Wendong and Li, Aolun},
  journal={Biomedical Signal Processing and Control},
  volume={87},
  pages={105534},
  year={2024},
  publisher={Elsevier}
}