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Enhanced imagistic methodologies augmenting radiological image processing in interstitial lung diseases Cover

Enhanced imagistic methodologies augmenting radiological image processing in interstitial lung diseases

Acta Universitatis Sapientiae, Informatica
Volume 15 (2023): Issue 1 (August 2023)
By: József Palatka,  Levente Kovács and  László Szilágyi  
Open Access
|Aug 2023

Authors

József Palatka

jozsef.palatka@syneoshealth.com

Doctoral School of Applied Informatics and Applied Mathematics, University Research, Innovation and Service Center, Óbuda University, Budapest, Hungary

Levente Kovács

kovacs@uni-obuda.hu

University Research, Innovation and Service Center, Óbuda University, Budapest, Hungary

László Szilágyi

lalo@ms.sapientia.ro

Computational Intelligence Research Group, Sapientia Hungarian University of Transylvania, University Research, Innovation and Service Center, Óbuda University, Department of Mechanical Engineering, University of Canterbury, Târgu Mureş
DOI: https://doi.org/10.2478/ausi-2023-0011 | Journal eISSN: 2066-7760
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Language: English
Page range: 146 - 169
Submitted on: Jun 29, 2023
|
Published on: Aug 8, 2023
Published by: Sapientia Hungarian University of Transylvania
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Keywords:
interstitial lung diseases,
high-resolution computed tomography,
radiography image processing,
complex networks,
convolutional neural networks,
computer-aided diagnostics,
deep learning,
machine learning
Related subjects:
Computer sciences,
Computer sciences, other

© 2023 József Palatka, Levente Kovács, László Szilágyi, published by Sapientia Hungarian University of Transylvania
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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