External validation, radiological evaluation, and development of deep learning automatic lung segmentation in contrast-enhanced chest CT.

Journal: European radiology
Published Date: Sep 29, 2023

Abstract

OBJECTIVES: There is a need for CT pulmonary angiography (CTPA) lung segmentation models. Clinical translation requires radiological evaluation of model outputs, understanding of limitations, and identification of failure points. This multicentre study aims to develop an accurate CTPA lung segmentation model, with evaluation of outputs in two diverse patient cohorts with pulmonary hypertension (PH) and interstitial lung disease (ILD).

Authors

  • Krit Dwivedi
    Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK.
  • Michael Sharkey
    Department of Entomology, University of Kentucky, Lexington, KY, USA.
  • Samer Alabed
    Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK.
  • Curtis P Langlotz
    Stanford University, University Medical Line, Stanford, CA, 94305, US.
  • Andy J Swift
    Department of Infection, Immunity & Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK.
  • Christian Bluethgen
    Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI), Stanford University, Sheffield, USA.

Keywords

External Resources

Popular Topics
Recent Journals