Mwinc-Mamba

Convolutional State Space Model with Multi-Window Cross-Scan to Advance the Automated Diagnosis of Skeletal Fluorosis

Hao Xu^1,2, Yun Wu^{1,2, 📧}, Rui Xie⁴, Jun Xu³, Junpeng Wu⁴, Rongpin Wang⁵, Youliang Tian^1,2

¹ State Key Laboratory of Public Big Data, Guizhou University
² College of Computer Science and Technology, Guizhou University
³ School of Artificial Intelligence, Nanjing University of Information Science and Technology
⁴ Zhijin County People’s Hospital
⁵ Department of Medical Imaging, Guizhou Provincial People’s Hospital
( 📧 ) Corresponding author.

Notes

• This study has been publiced by Biomedical Signal Processing and Control (BSPC).
• We are currently organising the code and dataset, which is expected to be released in February 2025. Stay tuned!
• If you have any questions, feel free to contact us via email [email protected].

Dataset Usage Statement

• If you use the SFXRay dataset provided by this study, you must cite the following two studies in the corresponding paper.

@article{xu2025107439,
  title={Convolutional state space model with multi-window cross-scan to advance the automated 	diagnosis of skeletal fluorosis},
  author={Xu, Hao and Wu, Yun and Xie, Rui and Xu, Jun and Wu, Junpeng and Wang, Rongpin and Tian, Youliang},
  journal={Biomedical Signal Processing and Control},
  volume={103},
  pages={107439},
  year={2025},
  publisher={Elsevier},
  doi={https://doi.org/10.1016/j.bspc.2024.107439},
}
@article{xu2024g2vit,
  title={G2ViT: Graph Neural Network-Guided Vision Transformer Enhanced Network for retinal vessel and coronary angiograph segmentation},
  author={Xu, Hao and Wu, Yun},
  journal={Neural Networks},
  volume={176},
  pages={106356},
  year={2024},
  publisher={Elsevier},
  doi={https://doi.org/10.1016/j.neunet.2024.106356}
}