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Journals
Journal of Artificial Intelligence and Soft Computing Research
Volume 12 (2022): Issue 1 (January 2022)
Open Access
Mixup (Sample Pairing) Can Improve the Performance of Deep Segmentation Networks
Lars J. Isaksson
Lars J. Isaksson
Division of Radiotherapy, European Institute of Oncology IRCCS
Milan, Italy
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Isaksson, Lars J.
,
Paul Summers
Paul Summers
Division of Radiology, European Institute of Oncology IRCCS
Milan, Italy
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Summers, Paul
,
Sara Raimondi
Sara Raimondi
Department of Experimental Oncology, European Institute of Oncology IRCCS
Milan, Italy
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Raimondi, Sara
,
Sara Gandini
Sara Gandini
Department of Experimental Oncology, European Institute of Oncology IRCCS
Milan, Italy
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Gandini, Sara
,
Abhir Bhalerao
Abhir Bhalerao
Department of Computer Science, University of Warwick
Warwick,
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Bhalerao, Abhir
,
Giulia Marvaso
Giulia Marvaso
Division of Radiotherapy, European Institute of Oncology IRCCS
Milan, Italy
Department of Oncology and Hemato-oncology, University of Milan
Milan, Italy
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Marvaso, Giulia
,
Giuseppe Petralia
Giuseppe Petralia
Division of Radiology, European Institute of Oncology IRCCS
Milan, Italy
Department of Oncology and Hemato-oncology, University of Milan
Milan, Italy
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Petralia, Giuseppe
,
Matteo Pepa
Matteo Pepa
Division of Radiotherapy, European Institute of Oncology IRCCS
Milan, Italy
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Pepa, Matteo
and
Barbara A. Jereczek-Fossa
Barbara A. Jereczek-Fossa
Division of Radiotherapy, European Institute of Oncology IRCCS
Milan, Italy
Department of Oncology and Hemato-oncology, University of Milan
Milan, Italy
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Jereczek-Fossa, Barbara A.
Oct 08, 2021
Journal of Artificial Intelligence and Soft Computing Research
Volume 12 (2022): Issue 1 (January 2022)
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Published Online:
Oct 08, 2021
Page range:
29 - 39
Received:
Mar 11, 2021
Accepted:
Jul 02, 2021
DOI:
https://doi.org/10.2478/jaiscr-2022-0003
Keywords
magnetic resonance imaging
,
segmentation
,
prostate
,
data augmentation
,
mixup
© 2022 Lars J. Isaksson et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.