Application of deep neural networks for automatic planning in radiation oncology treatments

A. M. Barragán-Montero; D. Nguyen; W. Lu; M. Lin; X. Geets; E. Sterpin; S. Jiang

Application of deep neural networks for automatic planning in radiation oncology treatments

A. M. Barragán-Montero, D. Nguyen, W. Lu, M. Lin, X. Geets, E. Sterpin, S. Jiang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Treatment planning for radiotherapy patients is a time-consuming and manual process. In this work, we investigate the use of deep neural networks to learn from previous clinical cases and directly predict the optimal dose distribution for a new patient. The proposed model combines two architectures, UNet and DenseNet, and used mean squared error as loss function. Ten input channels were used to include dosimetric and anatomical information. A set of 100 patients was used for training/validation and 29 for testing. Dice similarity coefficients ≥ 0.9 for the isodose-lines in the predicted versus the clinical dose showed the excellent accuracy of the model.

Original language	English (US)
Title of host publication	ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Publisher	ESANN (i6doc.com)
Pages	161-166
Number of pages	6
ISBN (Electronic)	9782875870650
State	Published - 2019
Event	27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2019 - Bruges, Belgium Duration: Apr 24 2019 → Apr 26 2019

Publication series

Name	ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

Conference

Conference	27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2019
Country/Territory	Belgium
City	Bruges
Period	4/24/19 → 4/26/19

ASJC Scopus subject areas

Artificial Intelligence
Information Systems

Cite this

Barragán-Montero, A. M., Nguyen, D., Lu, W., Lin, M., Geets, X., Sterpin, E., & Jiang, S. (2019). Application of deep neural networks for automatic planning in radiation oncology treatments. In ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (pp. 161-166). (ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning). ESANN (i6doc.com).

Application of deep neural networks for automatic planning in radiation oncology treatments. / Barragán-Montero, A. M.; Nguyen, D.; Lu, W. et al.
ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. ESANN (i6doc.com), 2019. p. 161-166 (ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Barragán-Montero, AM, Nguyen, D , Lu, W , Lin, M, Geets, X, Sterpin, E & Jiang, S 2019, Application of deep neural networks for automatic planning in radiation oncology treatments. in ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN (i6doc.com), pp. 161-166, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2019, Bruges, Belgium, 4/24/19.

Barragán-Montero AM, Nguyen D , Lu W , Lin M, Geets X, Sterpin E et al. Application of deep neural networks for automatic planning in radiation oncology treatments. In ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. ESANN (i6doc.com). 2019. p. 161-166. (ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).

Barragán-Montero, A. M. ; Nguyen, D. ; Lu, W. et al. / Application of deep neural networks for automatic planning in radiation oncology treatments. ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. ESANN (i6doc.com), 2019. pp. 161-166 (ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).

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Application of deep neural networks for automatic planning in radiation oncology treatments

Abstract

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Conference

ASJC Scopus subject areas

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