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Abstract Introduction: Computed tomography (CT)-based high-risk clinical target volume (HR-CTV) auto-segmentation has been previously investigated, but evidence remains heterogeneous across applicators, target definitions, architectures, and clinical evaluation procedures. A pragmatic within-cohort benchmark of 2D U-Net, 3D U-Net, and nnFormer was performed in a CT-only, applicator-in-situ workflow.
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
