Are Convolutional Neural Networks Trained on ImageNet Images Wearing Rose-Colored Glasses?: A Quantitative Comparison of ImageNet, Computed Tomographic, Magnetic Resonance, Chest X-Ray, and Point-of-Care Ultrasound Images for Quality.

Journal: Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Published Date:

Abstract

OBJECTIVES: Deep learning for medical imaging analysis uses convolutional neural networks pretrained on ImageNet (Stanford Vision Lab, Stanford, CA). Little is known about how such color- and scene-rich standard training images compare quantitatively to medical images. We sought to quantitatively compare ImageNet images to point-of-care ultrasound (POCUS), computed tomographic (CT), magnetic resonance (MR), and chest x-ray (CXR) images.

Authors

  • Laura Blaivas
    Michigan State University, East Lansing, Michigan, USA.
  • Michael Blaivas
    Department of Emergency Medicine, University of South Carolina School of Medicine, Columbia, South Carolina, USA.