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Kodama-XUUB: an informative classification for alveolar echinococcosis hepatic lesions on magnetic resonance imaging.

Éléonore BrumptWenya LiuTilmann GraeterPaul CalameShi RongYi JiangWeixia LiHaihua BaoÉric Delabroussenull null
Published in: Parasite (Paris, France) (2021)
The Kodama classification needed to be modified because of the existence of a significant proportion of unclassifiable lesions. This is especially true since the presence of microcysts is an informative element of parasite activity. Therefore, this study proposes a Kodama-XUUB classification with type IIIa lesions having microcysts and type IIIb lesions not having microcysts.
Keyphrases
  • machine learning
  • deep learning
  • magnetic resonance imaging
  • computed tomography
  • magnetic resonance