Advancing deep learning-based segmentation for multiple lung cancer lesions in real-world multicenter CT scans.
Journal:
European radiology experimental
Published Date:
Aug 18, 2025
Abstract
BACKGROUND: Accurate segmentation of lung cancer lesions in computed tomography (CT) is essential for precise diagnosis, personalized therapy planning, and treatment response assessment. While automatic segmentation of the primary lung lesion has been widely studied, the ability to segment multiple lesions per patient remains underexplored. In this study, we address this gap by introducing a novel, automated approach for multi-instance segmentation of lung cancer lesions, leveraging a heterogeneous cohort with real-world multicenter data.
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