Multi-Modal Active Learning For Automatic Liver Fibrosis Diagnosis Based On Ultrasound Shear Wave Elastography

@article{Gao2020MultiModalAL,
  title={Multi-Modal Active Learning For Automatic Liver Fibrosis Diagnosis Based On Ultrasound Shear Wave Elastography},
  author={Lufei Gao and Rui Zhou and Changfeng Dong and Cheng Feng and Zhuguo Li and Xiang Wan and Li Liu},
  journal={2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)},
  year={2020},
  pages={410-414}
}
  • Lufei GaoRui Zhou Li Liu
  • Published 2 November 2020
  • Computer Science
  • 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)
With the development of radiomics, noninvasive diagnosis like ultrasound (US) imaging plays a very important role in automatic liver fibrosis diagnosis (ALFD). Due to the noisy data, expensive annotations of US images, the application of Artificial Intelligence (AI) assisting approaches encounters a bottleneck. Besides, the use of single-modal US data limits the further improve of the classification results. In this work, we innovatively propose a multi-modal fusion network with active learning… 

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