Effect of altered oct image quality on deep learning boundary segmentation

HIGHLIGHTS

  • who: JASON KUGELMAN and collaborators from the Lens and Optics Laboratory, School of Optometry and Vision, Queensland University of Technology, Brisbane, QLD, Australia have published the paper: Effect of Altered OCT Image Quality on Deep Learning Boundary Segmentation, in the Journal: (JOURNAL)
  • what: This study examined a range of factors that can affect standard OCT image quality and determined how and why the performance of an existing neural network based segmentation method can subsequently degrade as a result. The authors provide a comprehensive simulation of the effects of degraded OCT image_quality and present a detailed . . .

     

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