Deep-learning-based estimation of attenuation map improves attenuation correction performance over direct attenuation estimation for myocardial perfusion SPECT.

Journal: Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
PMID: 36097242

Abstract

BACKGROUND: Deep learning (DL)-based attenuation correction (AC) is promising to improve myocardial perfusion (MP) SPECT. We aimed to optimize and compare the DL-based direct and indirect AC methods, with and without SPECT and CT mismatch.

Authors

  • Yu Du
    State Key Lab of CAD&CG, College of Computer Science and Technology, Zhejiang University, Hangzhou, China.
  • Jingjie Shang
    Department of Nuclear Medicine and PET/CT-MRI Centre, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
  • Jingzhang Sun
    Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau SAR, China.
  • Lu Wang
    Department of Laboratory, Akesu Center of Disease Control and Prevention, Akesu, China.
  • Yi-Hwa Liu
    Department of Internal Medicine (Cardiology), Yale University, New Haven, CT, USA.
  • Hao Xu
    Department of Nuclear Medicine, the First Affiliated Hospital, Jinan University, Guangzhou 510632, P.R.China.gdhyx2012@126.com.
  • Greta S P Mok
    Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macao SAR, China.

Keywords

External Resources

Popular Topics
Recent Journals