Performance evaluation of a deep learning image reconstruction (DLIR) algorithm in "double low" chest CTA in children: a feasibility study.

Journal: La Radiologia medica
Published Date: Jun 16, 2021

Abstract

BACKGROUND: Chest CT angiography (CTA) is a convenient clinical examination for children with an increasing need to reduce both radiation and contrast medium doses. Iterative Reconstruction algorithms are often used to reduce image noise but encounter limitations under low radiation dose and conventional 100 kVp tube voltage may not provide adequate enhancement under low contrast dose.

Authors

  • Jihang Sun
    Imaging Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, No. 56, Nanlishi Road, Xicheng District, Beijing, 100045, China.
  • Haoyan Li
    Imaging Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, No. 56, Nanlishi Road, Xicheng District, Beijing, 100045, China.
  • Jun Gao
    Physics of Complex Fluids, MESA+ Institute for Nanotechnology, University of Twente, Enschede 7500 AE, The Netherlands.
  • Jianying Li
    CT Research Center, GE Healthcare China, Beijing 100176, China.
  • Michelle Li
    Stanford University, Palo Alto, CA, USA.
  • Zuofu Zhou
    Department of Radiology, Fujian Provincial Maternity and Children's Hospital, Affiliated Hospital of Fujian Medical University, No. 18 Daoshan Road, Gulou District, Fujian, 350000, China.
  • Yun Peng
    Department of Radiology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.

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