A comparison of deep learning u-net architectures for posterior segment oct retinal layer segmentation

HIGHLIGHTS

• who: Jason Kugelman from the Centre Queensland University have published the research: A comparison of deep learning U-Net architectures for posterior segment OCT retinal layer segmentation, in the Journal: Scientific Reports Scientific Reports
• what: The overall goal of this study is to determine general conclusions for semantic OCT retinal layer segmentation using U-Net architectures which can be applied to any OCT dataset and result in significant time savings for future studies. Data was sourced across four separate visits over a period of approximately 18 months, however for the purposes of this study, the . . .
  

   

  

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