Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule Characterization.

Journal: Tomography (Ann Arbor, Mich.)
PMID: 39997996

Abstract

BACKGROUND/OBJECTIVES: Correct pulmonary nodule volumetry and categorization is paramount for accurate diagnosis in lung cancer screening programs. CT scanners with slice thicknesses of multiple millimetres are still common worldwide, and slice thickness has an adverse effect on the accuracy of the pulmonary nodule volumetry.

Authors

  • Dongok Kim
    Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul, Republic of Korea.
  • Chulkyun Ahn
    Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea.
  • Jong Hyo Kim
    Interdisciplinary Program of Radiation Applied Life Science, Seoul National University College of Medicine.

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