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A future of automated image contouring with machine learning in radiation therapy

Automated image contouring is showing improvements in efficiency for a number of clinical tasks in radiotherapy. While atlas segmentation has proven moderately beneficial, the next generation of algorithms based on convolutional neural networks is already pointing to improvements in precision and ef...

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Detalles Bibliográficos
Autores principales: Jackson, Price, Kron, Tomas, Hardcastle, Nicholas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6920687/
https://www.ncbi.nlm.nih.gov/pubmed/31854138
http://dx.doi.org/10.1002/jmrs.365
Descripción
Sumario:Automated image contouring is showing improvements in efficiency for a number of clinical tasks in radiotherapy. While atlas segmentation has proven moderately beneficial, the next generation of algorithms based on convolutional neural networks is already pointing to improvements in precision and efficiency. This work provides a broad overview of the benefits of machine learning when applied to these tasks.[Image: see text]