Improving Image Quality and Nodule Characterization in Ultra-low-dose Lung CT with Deep Learning Image Reconstruction.

Journal: Academic radiology
Published Date: Feb 29, 2024

Abstract

RATIONALE AND OBJECTIVE: To investigate the influence of the deep learning image reconstruction (DLIR) on the image quality and quantitative analysis of pulmonary nodules under ultra-low dose lung CT conditions.

Authors

  • Guangming Ma
    Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China.
  • Yuequn Dou
    Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China.
  • Shan Dang
    Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China.
  • Nan Yu
    Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, PR China.
  • Yanbing Guo
    Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China.
  • Dong Han
    Department of Radiology, Affiliated Hospital of Chengde Medical College, Chengde Hebei, 067000, P.R.China.
  • Qiuju Fan
    Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, China. fanqiuju858700@gmail.com.

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