Hydranet: Data Augmentation for Regression Neural Networks

Florian Dubost; Gerda Bortsova; Hieab Adams; Arfan Ikram; Wiro Niessen; Meike Vernooij; Marleen de Bruijne

doi:10.1007/978-3-030-32251-9_48

Hydranet: Data Augmentation for Regression Neural Networks

Florian Dubost, Gerda Bortsova, Hieab Adams, Arfan Ikram, Wiro Niessen, Meike Vernooij, Marleen de Bruijne

Research output: Chapter/Conference proceeding › Conference proceeding › Academic › peer-review

4 Citations (Scopus)

Original language	Undefined/Unknown
Title of host publication	International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
Place of Publication	[S.l.]
Publisher	Springer Nature
Pages	438-446
ISBN (Print)	9783030322502
DOIs	https://doi.org/10.1007/978-3-030-32251-9_48
Publication status	Published - 2019

Publication series

Series	Lecture Notes in Computer Science
Volume	11767

Access to Document

10.1007/978-3-030-32251-9_48

Cite this

Dubost, F., Bortsova, G., Adams, H., Ikram, A., Niessen, W., Vernooij, M., & de Bruijne, M. (2019). Hydranet: Data Augmentation for Regression Neural Networks. In International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 (pp. 438-446). Springer Nature. Lecture Notes in Computer Science Vol. 11767 https://doi.org/10.1007/978-3-030-32251-9_48

Dubost, Florian ; Bortsova, Gerda ; Adams, Hieab et al. / Hydranet: Data Augmentation for Regression Neural Networks. International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. [S.l.] : Springer Nature, 2019. pp. 438-446 (Lecture Notes in Computer Science, Vol. 11767).

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title = "Hydranet: Data Augmentation for Regression Neural Networks",

author = "Florian Dubost and Gerda Bortsova and Hieab Adams and Arfan Ikram and Wiro Niessen and Meike Vernooij and {de Bruijne}, Marleen",

year = "2019",

doi = "10.1007/978-3-030-32251-9_48",

language = "Undefined/Unknown",

isbn = "9783030322502",

series = "Lecture Notes in Computer Science",

publisher = "Springer Nature",

pages = "438--446",

booktitle = "International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019",

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Dubost, F, Bortsova, G , Adams, H , Ikram, A , Niessen, W , Vernooij, M & de Bruijne, M 2019, Hydranet: Data Augmentation for Regression Neural Networks. in International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. Springer Nature, [S.l.], Lecture Notes in Computer Science, vol. 11767, pp. 438-446. https://doi.org/10.1007/978-3-030-32251-9_48

Hydranet: Data Augmentation for Regression Neural Networks. / Dubost, Florian; Bortsova, Gerda ; Adams, Hieab et al.
International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. [S.l.]: Springer Nature, 2019. p. 438-446 (Lecture Notes in Computer Science, Vol. 11767).

Research output: Chapter/Conference proceeding › Conference proceeding › Academic › peer-review

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AU - Dubost, Florian

AU - Bortsova, Gerda

AU - Adams, Hieab

AU - Ikram, Arfan

AU - Niessen, Wiro

AU - Vernooij, Meike

AU - de Bruijne, Marleen

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BT - International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019

PB - Springer Nature

CY - [S.l.]

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Dubost F, Bortsova G , Adams H , Ikram A , Niessen W , Vernooij M et al. Hydranet: Data Augmentation for Regression Neural Networks. In International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. [S.l.]: Springer Nature. 2019. p. 438-446. (Lecture Notes in Computer Science, Vol. 11767). doi: 10.1007/978-3-030-32251-9_48