Collimation border with U-Net segmentation on chest radiographs compared to radiologists.

Journal: Radiography (London, England : 1995)
Published Date: May 2, 2023

Abstract

INTRODUCTION: Chest Radiography (CXR) is a common radiographic procedure. Radiation exposure to patients should be kept as low as reasonably achievable (ALARA), and monitored continuously as part of quality assurance (QA) programs. One of the most effective dose reduction tools is proper collimation practice. The purpose of this study is to determine whether a U-Net convolutional neural networks (U-CNN) can be trained to automatically segment the lungs and calculate an optimized collimation border on a limited CXR dataset.

Authors

  • A E Pedersen
    Department of Radiology and Nuclear Medicine, Hospital of South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark.
  • M W Kusk
    Department of Radiology and Nuclear Medicine, Hospital of South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark.
  • G H Knudsen
    Department of Radiology and Nuclear Medicine, Hospital of South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark; Department of Regional Health Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark; Imaging Research Initiative Southwest (IRIS), Hospital of South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark.
  • C A G R Busk
    Department of Radiology and Nuclear Medicine, Hospital of South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark; Department of Regional Health Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark; Imaging Research Initiative Southwest (IRIS), Hospital of South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark.
  • S Lysdahlgaard
    Department of Radiology and Nuclear Medicine, Hospital of South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark; Department of Regional Health Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark; Imaging Research Initiative Southwest (IRIS), Hospital of South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark. Electronic address: Simon.Lysdahlgaard@rsyd.dk.

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