Qualitative evaluation of automatic liver segmentation in computed tomography images for clinical use in radiation therapy.

Journal: Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Published Date: Jun 14, 2025

Abstract

PURPOSE: Segmentation of target volumes and organs at risk on computed tomography (CT) images constitutes an important step in the radiotherapy workflow. Artificial intelligence-based methods have significantly improved organ segmentation in medical images. Automatic segmentations are frequently evaluated using geometric metrics. Before a clinical implementation in the radiotherapy workflow, automatic segmentations must also be evaluated by clinicians. The aim of this study was to investigate the correlation between geometric metrics used for segmentation evaluation and the assessment performed by clinicians.

Authors

  • Dorea Maria Khalal
    Laboratory of Dosing, Analysis and Characterization in High Resolution, Department of Physics, Faculty of Sciences, Ferhat-Abbas-Sétif 1 University, El Baz Campus, 19137 Sétif, Algeria. Electronic address: doreamaria.khalal@univ-setif.dz.
  • Souleyman Slimani
    Radiotherapy Department, HCA Hospital, Algiers, Algeria.
  • Zine Eddine Bouraoui
    Radiotherapy Department, HCA Hospital, Algiers, Algeria.
  • Hacene Azizi
    Laboratory of Dosing, Analysis and Characterization in High Resolution, Department of Physics, Faculty of Sciences, Ferhat-Abbas-Sétif 1 University, El Baz Campus, 19137 Sétif, Algeria.

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