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Author

F. Löfman

2 papers indexed here

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Review Open access Oct 2026

Multicenter Evaluation of a Deep Learning Model for Automatic Contouring of Cardiac Substructures in Adults.

PURPOSE Efficient delineation of cardiac substructures is essential for assessing radiation-induced cardiac toxicity in thoracic radiotherapy. We clinically evaluated a deep learning model designed for automated segmentation of these structures. METHODS AND MATERIALS The model built in collaboration with XXX (XXX) ge...

A. Moignier, A. Licha, F. Felici et al. · 0 citations
#software testing Open access Sep 2026

Clinical evaluation and regression test of a commercial deep‐learning auto‐segmentation model

Regression testing of head and neck, thorax, and male pelvis sites showed consistent performance after the software upgrade and the DLS models for abdominal site were commissioned in this study for clinical use; while the DLS models for breast site were not recommended.

R. Barati, J. Duan, Song Gao et al. · 0 citations

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