Systematic Clinical Evaluation of a Deep Learning Method for Medical Image Segmentation: Radiosurgery Application

@article{Shirokikh2022SystematicCE,
  title={Systematic Clinical Evaluation of a Deep Learning Method for Medical Image Segmentation: Radiosurgery Application},
  author={Boris Shirokikh and Alexandra Dalechina and Alexey Shevtsov and Egor Krivov and Valery Kostjuchenko and Amayak Durgaryan and M. V. Galkin and Andrey V. Golanov and Mikhail Belyaev},
  journal={IEEE Journal of Biomedical and Health Informatics},
  year={2022},
  volume={26},
  pages={3037-3046}
}
We systematically evaluate a Deep Learning model in a 3D medical image segmentation task. With our model, we address the flaws of manual segmentation: high inter-rater contouring variability and time consumption of the contouring process. The main extension over the existing evaluations is the careful and detailed analysis that could be further generalized on other medical image segmentation tasks. Firstly, we analyze the changes in the inter-rater detection agreement. We show that the model… 

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