Deep learning-based auto-delineation of gross tumour volumes and involved nodes in PET/CT images of head and neck cancer patients.

Journal: European journal of nuclear medicine and molecular imaging
Published Date: Feb 9, 2021

Abstract

PURPOSE: Identification and delineation of the gross tumour and malignant nodal volume (GTV) in medical images are vital in radiotherapy. We assessed the applicability of convolutional neural networks (CNNs) for fully automatic delineation of the GTV from FDG-PET/CT images of patients with head and neck cancer (HNC). CNN models were compared to manual GTV delineations made by experienced specialists. New structure-based performance metrics were introduced to enable in-depth assessment of auto-delineation of multiple malignant structures in individual patients.

Authors

  • Yngve Mardal Moe
    Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway.
  • Aurora Rosvoll Groendahl
    Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway.
  • Oliver Tomic
    Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway.
  • Einar Dale
    Department of Oncology, Oslo University Hospital, Oslo, Norway.
  • Eirik Malinen
    b Department of Physics , University of Oslo , Oslo , Norway.
  • Cecilia Marie Futsaether
    Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway. cecilia.futsaether@nmbu.no.

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