Reduction of radiation exposure in chest radiography using deep learning-based noise reduction processing: A phantom and retrospective clinical study.

Journal: Radiography (London, England : 1995)
Published Date: Apr 24, 2025

Abstract

INTRODUCTION: Intelligent noise reduction (INR), a deep learning-based noise reduction developed by Canon, is used in planar radiography to improve image quality and reduce patient exposure dose. This study aimed to evaluate the reduction of patient exposure dose in planar chest radiography using INR.

Authors

  • K Mori
    Department of Radiological Technology, Saiseikai Kawaguchi General Hospital, 5-11-5 Nishikawaguchi, Kawaguchi, Saitama, 332-8558, Japan; Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, 7-2-10 Higashi-Ogu, Arakawa, Tokyo, 116-8551, Japan. Electronic address: mori-kazuya@ed.tmu.ac.jp.
  • T Negishi
    Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, 7-2-10 Higashi-Ogu, Arakawa, Tokyo, 116-8551, Japan.
  • R Sekiguchi
    Department of Radiological Technology, Saiseikai Kawaguchi General Hospital, 5-11-5 Nishikawaguchi, Kawaguchi, Saitama, 332-8558, Japan.
  • M Suzaki
    Department of Radiological Technology, Saiseikai Kawaguchi General Hospital, 5-11-5 Nishikawaguchi, Kawaguchi, Saitama, 332-8558, Japan.

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