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Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: Evaluation in Alzheimer's disease


Dec 18, 2020
Martin Dyrba, Moritz Hanzig, Slawek Altenstein, Sebastian Bader, Tommaso Ballarini, Frederic Brosseron, Katharina Buerger, Daniel Cantré, Peter Dechent, Laura Dobisch, Emrah Düzel, Michael Ewers, Klaus Fliessbach, Wenzel Glanz, John D. Haynes, Michael T. Heneka, Daniel Janowitz, Deniz Baris Keles, Ingo Kilimann, Christoph Laske, Franziska Maier, Coraline D. Metzger, Matthias H. Munk, Robert Perneczky, Oliver Peters, Lukas Preis, Josef Priller, Boris Rauchmann, Nina Roy, Klaus Scheffler, Anja Schneider, Björn H. Schott, Annika Spottke, Eike J. Spruth, Marc-André Weber, Birgit Ertl-Wagner, Michael Wagner, Jens Wiltfang, Frank Jessen, Stefan J. Teipel

* 19 pages, 9 figures/tables, source code available on GitHub 

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Learning Shape Features and Abstractions in 3D Convolutional Neural Networks for Detecting Alzheimer's Disease


Sep 10, 2020
Md Motiur Rahman Sagar, Martin Dyrba


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Comparison of Convolutional neural network training parameters for detecting Alzheimers disease and effect on visualization


Aug 18, 2020
Arjun Haridas Pallath, Martin Dyrba


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