Deep learning-based digital subtraction angiography image generation.

Journal: International journal of computer assisted radiology and surgery
Published Date: Oct 1, 2019

Abstract

PURPOSE: Digital subtraction angiography (DSA) is a powerful technique for diagnosing cardiovascular disease. In order to avoid image artifacts caused by patient movement during imaging, we take deep learning-based methods to generate DSA image from single live image without the mask image.

Authors

  • Yufeng Gao
    Laboratory of Image Science and Technology, Southeast University, Nanjing, 210096, China.
  • Yu Song
    Department of Systems Management, Fukuoka Institute of Technology, Fukuoka, Japan.
  • Xiangrui Yin
  • Weiwen Wu
    Key Lab of Optoelectronic Technology and Systems, Ministry of Education, Chongqing University, Chongqing, 400044, China.
  • Lu Zhang
    Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX, United States.
  • Yang Chen
    Orthopedics Department of the First Affiliated Hospital of Tsinghua University, Beijing, China.
  • Wanyin Shi
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, No. 218 Jixi Road, Hefei, 230022, China. shwy110@163.com.

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