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KOLAŘÍK, M. BURGET, R. UHER, V. POVODA, L.
Originální název
Superresolution of MRI brain images using unbalanced 3D Dense-U-Net network
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
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.
Klíčová slova
3D; brain; mri; neural networks; superresolution; u-net
Autoři
KOLAŘÍK, M.; BURGET, R.; UHER, V.; POVODA, L.
Vydáno
1. 7. 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" }