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Automated thresholding algorithms outperform manual thresholding in macular optical coherence tomography angiography image analysis.

Jan Henrik TerheydenMaximilian W M WintergerstPeyman FalahatMoritz BergerFrank G HolzRobert P Finger
Published in: PloS one (2020)
Automated thresholding algorithms yield a higher reproducibility of OCTA parameters and allow for a more sensitive diagnosis of macular pathology. However, different algorithms are not interchangeable nor results readily comparable. Especially the Mean algorithm should be investigated in further detail. Automated thresholding algorithms are preferable but more standardization is needed for clinical use.
Keyphrases
  • machine learning
  • deep learning
  • optical coherence tomography
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