The diagnostic and prognostic value of radiomics and deep learning technologies for patients with solid pulmonary nodules in chest CT images.

Journal: BMC cancer
Published Date:

Abstract

BACKGROUND: Solid pulmonary nodules are different from subsolid nodules and the diagnosis is much more challenging. We intended to evaluate the diagnostic and prognostic value of radiomics and deep learning technologies for solid pulmonary nodules.

Authors

  • Rui Zhang
    Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Ying Wei
    School of Information Science and Engineering, Northeastern University, Shenyang 110004, China ; Key Laboratory of Medical Imaging Calculation of the Ministry of Education, Shenyang 110004, China.
  • Feng Shi
    Department of Research and Development, Shanghai United Imaging Intelligence, Co., Ltd. Shanghai, China.
  • Jing Ren
    College of Life Science and Engineering, Lanzhou University of TechnologyLanzhou 730050, P. R. China; The Key Lab of Screening, Evaluation and Advanced Processing of TCM and Tibetan Medicine, Education Department of Gansu Provincial GovernmentLanzhou 730050, P. R. China.
  • Qing Zhou
    Cardiac MR PET CT Program, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Weimin Li
    Department of Psychiatry, Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Bojiang Chen
    Department of Respiratory and Critical Care Medicine, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, 610041 Chengdu, Sichuan, China.