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Detail publikačního výsledku
KOLAŘÍK, M.; BURGET, R.; UHER, V.; POVODA, L.
Originální název
Superresolution of MRI brain images using unbalanced 3D Dense-U-Net network
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
This paper proposes an unbalanced end-to-end trained 3D Dense-U-Net network for brain MRI images superresolution. We evaluated capabilites of the proposed architecture on upsampling the MRI brain scans in the factor of 2, 4 and 8 and compared the results with resampled images using lanczos, spline and bilinear interpolation achieving best results. While the network does not exceed superresolution capabilites of state-of-the-art GAN networks, it does not require large dataset, is easy to train and capable of processing 3D images in resolution suitable for medical image processing.
Anglický abstrakt
Klíčová slova
3D; brain; mri; neural networks; superresolution; u-net
Klíčová slova v angličtině
Autoři
Rok RIV
2020
Vydáno
01.07.2019
ISBN
978-1-7281-1864-2
Kniha
2019 42nd International Conference on Telecommunications and Signal Processing (TSP)
Strany od
643
Strany do
646
Strany počet
4
URL
https://ieeexplore.ieee.org/abstract/document/8768829
BibTex
@inproceedings{BUT157997, author="Martin {Kolařík} and Radim {Burget} and Václav {Uher} and Lukáš {Povoda}", title="Superresolution of MRI brain images using unbalanced 3D Dense-U-Net network", booktitle="2019 42nd International Conference on Telecommunications and Signal Processing (TSP)", year="2019", pages="643--646", doi="10.1109/TSP.2019.8768829", isbn="978-1-7281-1864-2", url="https://ieeexplore.ieee.org/abstract/document/8768829" }
Dokumenty
08768829