Interactive contouring through contextual deep learning.

Journal: Medical physics
Published Date: May 3, 2021

Abstract

PURPOSE: To investigate a deep learning approach that enables three-dimensional (3D) segmentation of an arbitrary structure of interest given a user provided two-dimensional (2D) contour for context. Such an approach could decrease delineation times and improve contouring consistency, particularly for anatomical structures for which no automatic segmentation tools exist.

Authors

  • Michael J Trimpl
    Mirada Medical Ltd, Oxford, UK.
  • Djamal Boukerroui
    Mirada Medical Ltd, Oxford, UK.
  • Eleanor P J Stride
    Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
  • Katherine A Vallis
    Oxford Institute for Radiation Oncology, University of Oxford, Oxford, UK.
  • Mark J Gooding
    2 Mirada Medical Ltd, Oxford, UK.

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