Using Convolutional Encoder Networks to Determine the Optimal Magnetic Resonance Image for the Automatic Segmentation of Multiple Sclerosis Article

Ghosh, Shaurnav, Huo, Marc, Shawkat, Mst Shamim Ara et al. (2021). Using Convolutional Encoder Networks to Determine the Optimal Magnetic Resonance Image for the Automatic Segmentation of Multiple Sclerosis . Applied Sciences (Switzerland), 11(18), 10.3390/app11188335

Open Access

cited authors

  • Ghosh, Shaurnav; Huo, Marc; Shawkat, Mst Shamim Ara; McCalla, Serena

sustainable development goals

authors

publication date

  • September 1, 2021

published in

keywords

  • Chemistry
  • Chemistry, Multidisciplinary
  • Engineering
  • Engineering, Multidisciplinary
  • Materials Science
  • Materials Science, Multidisciplinary
  • Physical Sciences
  • Physics
  • Physics, Applied
  • Science & Technology
  • Technology
  • U-NET
  • convolutional encoder networks
  • convolutional neural networks
  • machine learning
  • magnetic resonance image
  • multiple sclerosis
  • segmentation
  • white matter lesions

Digital Object Identifier (DOI)

volume

  • 11

issue

  • 18