Applying Attention Mechanism and Deep Neural Network for Medical Object Segmentation and Classification in X-Ray Fluoroscopy Images

  • Yong Zhang
  • Jun Yan
  • Haitao HuangEmail author
  • Christopher Yencha
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1072)


We study how to apply attention mechanism and deep neural network for real-time segmentation and classification of balloon objects from X-ray fluoroscopy images during percutaneous balloon compression (PBC) surgical procedures. Fast and accurate identification of balloon shape and its relative location to the Meckel’s cave can be of significant benefit to the success of the PBC procedure. In this work, we combine the most successful region-based convolutional neural network pipeline with attention mechanism to address these challenges.


Percutaneous balloon compression Attention mechanism Deep learning Convolutional neural network 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Yong Zhang
    • 1
  • Jun Yan
    • 2
  • Haitao Huang
    • 3
    Email author
  • Christopher Yencha
    • 1
  1. 1.Weber State UniversityOgdenUSA
  2. 2.Yidu Cloud Technology Co. Ltd.BeijingChina
  3. 3.The People’s Hospital of Liaoning ProvinceShenyangChina

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