Portal de Periódicos da CAPES

Development and comprehensive evaluation of a national DBCG consensus-based auto-segmentation model for lymph node levels in breast cancer radiotherapy

2024; Elsevier BV; Volume: 201; Linguagem: Inglês

10.1016/j.radonc.2024.110567

1879-0887

Emma Skarsø Buhl, Ebbe Laugaard Lorenzen, Lasse Refsgaard, Anders W. Mølby Nielsen, Annette Torbøl Lund Brixen, Else Maae, Hanne Spangsberg Holm, Joachim Schøler, Linh My Hoang Thai, Louise Wichmann Matthiessen, Maja V. Maraldo, Mathias Maximiliano Nielsen, Marianne Besserman Johansen, Marie Louise Holm Milo, Marie Benzon Mogensen, Mette Holck Nielsen, Mette Møller, Maja V. Sand, Peter Schultz, Sami Al-Rawi, Saskia Eßer-Naumann, Sophie Yammeni, Stine E. Petersen, Birgitte Vrou Offersen, Stine Korreman,

Advanced Radiotherapy Techniques

This study aimed at training and validating a multi-institutional deep learning (DL) auto segmentation model for nodal clinical target volume (CTVn) in high-risk breast cancer (BC) patients with both training and validation dataset created with multi-institutional participation, with the overall aim of national clinical implementation in Denmark.