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Radiomics as a measure superior to common similarity metrics for tumor segmentation performance evaluation.

Rukhsora AkramovaYoichi Watanabe
Published in: Journal of applied clinical medical physics (2024)
This study demonstrates the superiority of radiomics features with ICC as a measure for evaluating a physician's tumor segmentation ability and the performance of auto-segmentation tools. Radiomics features offer a more sensitive and comprehensive evaluation, providing valuable insights into tumor characteristics. Therefore, the new metrics can be used to evaluate new auto-segmentation methods and enhance trainees' segmentation skills in medical training and education.
Keyphrases
  • deep learning
  • convolutional neural network
  • healthcare
  • lymph node metastasis
  • machine learning
  • magnetic resonance imaging
  • magnetic resonance
  • quality improvement