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Quantity and quality of image artifacts in optical coherence tomography angiography.

Christian EndersGabriele E LangJens DreyhauptMax LoidlGerhard K LangJens U Werner
Published in: PloS one (2019)
Various artifacts appear at different frequencies in OCTA images. Nevertheless, a qualitative assessment of the OCTA images is almost always possible. Good knowledge of possible artifacts and critical analysis of the complete OCTA dataset are essential for correct clinical interpretation and determining a precise clinical diagnosis.
Keyphrases
  • deep learning
  • convolutional neural network
  • image quality
  • healthcare
  • optical coherence tomography
  • cone beam
  • magnetic resonance
  • quality improvement
  • machine learning
  • clinical evaluation