Deep Learning Architecture to Improve Edge Accuracy of Auto-Contouring for Head and Neck Radiotherapy

Deep learning (DL) methods have shown great promise in auto-segmentation problems. However, for head and neck cancer, we show that DL methods fail at the axial edges of the gross tumor volume (GTV) where the segmentation is dependent on information closer to the center of the tumor. These failures m...

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Detalles Bibliográficos
Autores principales: Gifford, Ryan, Jhawar, Sachin R., Krening, Samantha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10340458/
https://www.ncbi.nlm.nih.gov/pubmed/37443553
http://dx.doi.org/10.3390/diagnostics13132159

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10340458/
https://www.ncbi.nlm.nih.gov/pubmed/37443553
http://dx.doi.org/10.3390/diagnostics13132159

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