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The Effect of Image Resolution on Deep Learning in Radiography.

Carl F SabottkeBradley M Spieler
Published in: Radiology. Artificial intelligence (2020)
Increasing image resolution for CNN training often has a trade-off with the maximum possible batch size, yet optimal selection of image resolution has the potential for further increasing neural network performance for various radiology-based machine learning tasks. Furthermore, identifying diagnosis-specific tasks that require relatively higher image resolution can potentially provide insight into the relative difficulty of identifying different radiology findings. Supplemental material is available for this article. © RSNA, 2020See also the commentary by Lakhani in this issue.
Keyphrases
  • deep learning
  • artificial intelligence
  • machine learning
  • convolutional neural network
  • neural network
  • single molecule
  • working memory
  • big data
  • risk assessment
  • human health