Automated reference-free assessment of MR image quality using an active learning approach: Comparison of Support Vector Machine versus Deep Neural Network classification
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%0 Conference Paper
%1 Gatidis2017ISMRM
%A Gatidis, Sergios
%A Liebgott, Annika
%A Schwartz, Martin
%A Martirosian, Petros
%A Schick, Fritz
%A Nikolaou, Konstantin
%A Yang, Bin
%A Küstner, Thomas
%B Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM)
%C Honolulu, Hawaii, USA
%D 2017
%K
%T Automated reference-free assessment of MR image quality using an active learning approach: Comparison of Support Vector Machine versus Deep Neural Network classification
@inproceedings{Gatidis2017ISMRM,
added-at = {2023-08-31T14:18:36.000+0200},
address = {Honolulu, Hawaii, USA},
author = {Gatidis, Sergios and Liebgott, Annika and Schwartz, Martin and Martirosian, Petros and Schick, Fritz and Nikolaou, Konstantin and Yang, Bin and K\"ustner, Thomas},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2074b49f5a5badd9745782ab4a7766409/puma-wartung},
booktitle = {Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM)},
interhash = {cfb465bc7765fa341252a8cfab64ac69},
intrahash = {074b49f5a5badd9745782ab4a7766409},
keywords = {},
month = apr,
timestamp = {2023-08-31T12:18:36.000+0200},
title = {Automated reference-free assessment of MR image quality using an active learning approach: Comparison of Support Vector Machine versus Deep Neural Network classification},
year = 2017
}
