CT Image Conversion among Different Reconstruction Kernels without a Sinogram by Using a Convolutional Neural Network.

Journal: Korean journal of radiology
Published Date: Feb 1, 2019

Abstract

OBJECTIVE: The aim of our study was to develop and validate a convolutional neural network (CNN) architecture to convert CT images reconstructed with one kernel to images with different reconstruction kernels without using a sinogram.

Authors

  • Sang Min Lee
    Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
  • June Goo Lee
    Department of Convergence Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
  • Gaeun Lee
    Department of Convergence Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
  • Jooae Choe
    Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
  • Kyung Hyun Do
    Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
  • Namkug Kim
    Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Joon Beom Seo
    Department of Radiology, Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea.

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