Generalizability, robustness, and correction bias of segmentations of thoracic organs at risk in CT images.
Journal:
European radiology
Published Date:
Dec 31, 2024
Abstract
OBJECTIVE: This study aims to assess and compare two state-of-the-art deep learning approaches for segmenting four thoracic organs at risk (OAR)-the esophagus, trachea, heart, and aorta-in CT images in the context of radiotherapy planning.
