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Binary polyp-size classification based on deep-learned spatial information.

Hayato ItohMasahiro OdaKai JiangYuichi MoriMasashi MisawaShin-Ei KudoKenichiro ImaiSayo ItoKinichi HottaKensaku Mori
Published in: International journal of computer assisted radiology and surgery (2021)
We developed a binary polyp-size classification method by utilising the estimated three-dimensional shape of a polyp. Experiments demonstrated accurate classification for both protruded- and flat-type polyps, even though the flat type have ambiguous boundary between a polyp and colon wall.
Keyphrases
  • deep learning
  • machine learning
  • high resolution
  • healthcare
  • social media
  • chronic rhinosinusitis