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Variability in accuracy of prostate cancer segmentation among radiologists, urologists, and scientists.

Michael Y ChenMaria A WoodruffProkar DasguptaNicholas J Rukin
Published in: Cancer medicine (2020)
Segmentation of prostate cancers is more difficult than other anatomy such as kidney tumors. Less experienced participants appear to under-segment models and underestimate the size of prostate tumors. Segmentation of prostate cancer is highly variable even among radiologists, and 3D modeling for clinical use must be performed with caution. Further work to develop a methodology to maximize segmentation accuracy is needed.
Keyphrases
  • prostate cancer
  • deep learning
  • convolutional neural network
  • radical prostatectomy
  • artificial intelligence
  • machine learning
  • benign prostatic hyperplasia