CheXNet: Combing Transformer and CNN for Thorax Disease Diagnosis from Chest X-ray Images

DOI: 10.1007/978-981-99-8558-6_7 supp

Xin W, Yue F, et al. (2023 Chinese Conference on Pattern Recognition and Computer Vision, CCF-C)   Code

Abstract

Multi-label chest X-ray (CXR) image classification aims to perform multiple disease label prediction tasks. This concept is more challenging than single-label classification problems. For instance, convolutional neural networks (CNNs) often struggle to capture the statistical dependencies between labels. Furthermore, the drawback of concatenating CNN and Transformer is the lack of direct interaction and information exchange between the two models…

Keywords

Hybird network Multi-label Chest X-ray image

Model

@inproceedings{wu2023chexnet,
  title={CheXNet: Combing Transformer and CNN for Thorax Disease Diagnosis from Chest X-ray Images},
  author={Wu, Xin and Feng, Yue and Xu, Hong and Lin, Zhuosheng and Li, Shengke and Qiu, Shihan and Liu, QiChao and Ma, Yuangang},
  booktitle={Chinese Conference on Pattern Recognition and Computer Vision (PRCV)},
  pages={73--84},
  year={2023},
  organization={Springer},
  location={Singapore},
  doi={10.1007/978-981-99-8558-6_7}
}