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Applying 3D U-Net Architecture to the Task of Multi-Organ Segmentation in Computed Tomography Cover

Applying 3D U-Net Architecture to the Task of Multi-Organ Segmentation in Computed Tomography

Applied Computer Systems
Volume 25 (2020): Issue 1 (May 2020)
By: Pavlo Radiuk  
Open Access
|Jun 2020

Authors

Pavlo Radiuk

radiukpavlo@gmail.com

Khmelnytskyi National University, Khmelnytskyi, Ukraine
DOI: https://doi.org/10.2478/acss-2020-0005 | Journal eISSN: 2255-8691 | Journal ISSN: 2255-8683
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Language: English
Page range: 43 - 50
Published on: Jun 5, 2020
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Computed tomography volumetric images,
fully convolutional neural networks,
medical image analysis,
multi-organ segmentation,
Sørensen-Dice similarity coefficient
Related subjects:
Computer sciences,
Artificial intelligence,
Information technology,
Project management,
Software development

© 2020 Pavlo Radiuk, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.

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