Evaluation of multiple-vendor AI autocontouring solutions.

Journal: Radiation oncology (London, England)
Published Date: May 31, 2024

Abstract

BACKGROUND: Multiple artificial intelligence (AI)-based autocontouring solutions have become available, each promising high accuracy and time savings compared with manual contouring. Before implementing AI-driven autocontouring into clinical practice, three commercially available CT-based solutions were evaluated.

Authors

  • Lee Goddard
    Department of Radiation Oncology, Montefiore Medical Center, Bronx, NY, 10467, USA.
  • Christian Velten
    Department of Radiation Oncology, Montefiore Medical Center, Bronx, NY, 10467, USA.
  • Justin Tang
    Department of Orthopedics, Icahn School of Medicine at Mount Sinai, New York, NY.
  • Karin A Skalina
    Department of Radiation Oncology, Montefiore Medical Center, Bronx, NY, 10467, USA.
  • Robert Boyd
    Institute of Human Origins, Arizona State University, Tempe, Arizona 85287, USA.
  • William Martin
    Department of Radiation Oncology, Montefiore Medical Center, Bronx, NY, 10467, USA.
  • Amar Basavatia
    Department of Radiation Oncology, Montefiore Medical Center, Bronx, NY, 10467, USA.
  • Madhur Garg
    Department of Radiation Oncology, Montefiore Medical Center, Bronx, NY, 10467, USA.
  • Wolfgang A Tomé

Keywords

External Resources

Popular Topics
Recent Journals