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Abstract
Imaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
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Authors (9)
-
Sergii Girnyi
-
Dariusz Świetlik
-
Jakub Woźniak
-
Weronika Szczecińska
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Janusz Jaśkiewicz
-
Jacek Zielinski
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Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
EJSO-EUR J SURG ONC
no. 48,
pages e147 - e148,
ISSN: 0748-7983 - Language:
- English
- Publication year:
- 2022
- Bibliographic description:
- Girnyi S., Brzeski A., Cychnerski J., Świetlik D., Woźniak J., Szczecińska W., Jaśkiewicz J., Zielinski J., Dziubich T.: Creating a radiological database for automatic liver segmentation using artificial intelligence.// EJSO-EUR J SURG ONC -Vol. 48,iss. 2 (2022), s.e147-e148
- DOI:
- Digital Object Identifier (open in new tab) 10.1016/j.ejso.2021.12.287
- Verified by:
- Gdańsk University of Technology
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