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:
Editorials
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
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author Jackson, Price
Kron, Tomas
Hardcastle, Nicholas
author_facet Jackson, Price
Kron, Tomas
Hardcastle, Nicholas
author_sort Jackson, Price
collection PubMed
description 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]
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spelling pubmed-69206872019-12-30 A future of automated image contouring with machine learning in radiation therapy Jackson, Price Kron, Tomas Hardcastle, Nicholas J Med Radiat Sci Editorials 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] John Wiley and Sons Inc. 2019-12-19 2019-12 /pmc/articles/PMC6920687/ /pubmed/31854138 http://dx.doi.org/10.1002/jmrs.365 Text en 2019 The Authors. Journal of Medical Radiation Sciences published by John Wiley & Sons Australia, Ltd on behalf of Australian Society of Medical Imaging and Radiation Therapy and New Zealand Institute of Medical Radiation Technology This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Editorials
Jackson, Price
Kron, Tomas
Hardcastle, Nicholas
A future of automated image contouring with machine learning in radiation therapy
title A future of automated image contouring with machine learning in radiation therapy
title_full A future of automated image contouring with machine learning in radiation therapy
title_fullStr A future of automated image contouring with machine learning in radiation therapy
title_full_unstemmed A future of automated image contouring with machine learning in radiation therapy
title_short A future of automated image contouring with machine learning in radiation therapy
title_sort future of automated image contouring with machine learning in radiation therapy
topic Editorials
url 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
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