Comparing different CT, PET and MRI multi-modality image combinations for deep learning-based head and neck tumor segmentation.

Journal: Acta oncologica (Stockholm, Sweden)
Published Date:

Abstract

BACKGROUND: Manual delineation of gross tumor volume (GTV) is essential for radiotherapy treatment planning, but it is time-consuming and suffers inter-observer variability (IOV). In clinics, CT, PET, and MRI are used to inform delineation accuracy due to their different complementary characteristics. This study aimed to investigate deep learning to assist GTV delineation in head and neck squamous cell carcinoma (HNSCC) by comparing various modality combinations.

Authors

  • Jintao Ren
    Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
  • Jesper Grau Eriksen
    Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
  • Jasper Nijkamp
    Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
  • Stine Sofia Korreman
    Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.