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Labeling Vertebrae with Two-dimensional Reformations of Multidetector CT Images: An Adversarial Approach for Incorporating Prior Knowledge of Spine Anatomy.

Anjany SekuboyinaMarkus RempflerAlexander ValentinitschBjoern H MenzeJan Stefan Kirschke
Published in: Radiology. Artificial intelligence (2020)
An identification performance comparable to existing three-dimensional approaches was achieved when labeling vertebrae on two-dimensional MIPs. The performance was further improved using the proposed adversarial training regimen that effectively enforced local spine a priori knowledge during training. Spine localization increased the generalizability of our approach by homogenizing the content in the MIPs.Supplemental material is available for this article.© RSNA, 2020.
Keyphrases
  • computed tomography
  • healthcare
  • virtual reality
  • deep learning
  • contrast enhanced
  • image quality
  • magnetic resonance imaging
  • dual energy
  • bioinformatics analysis