no code implementations • 20 Jan 2023 • Fabian Eitel, Marc-André Schulz, Moritz Seiler, Henrik Walter, Kerstin Ritter
By promising more accurate diagnostics and individual treatment recommendations, deep neural networks and in particular convolutional neural networks have advanced to a powerful tool in medical imaging.
no code implementations • 26 May 2017 • Dajiang Zhu, Brandalyn C. Riedel, Neda Jahanshad, Nynke A. Groenewold, Dan J. Stein, Ian H. Gotlib, Matthew D. Sacchet, Danai Dima, James H. Cole, Cynthia H. Y. Fu, Henrik Walter, Ilya M. Veer, Thomas Frodl, Lianne Schmaal, Dick J. Veltman, Paul M. Thompson
Within each iteration, the classification result and the selected features are collected to update the weighting parameters for each feature.
no code implementations • 8 Sep 2015 • Nicholas Allgaier, Tobias Banaschewski, Gareth Barker, Arun L. W. Bokde, Josh C. Bongard, Uli Bromberg, Christian Büchel, Anna Cattrell, Patricia J. Conrod, Christopher M. Danforth, Sylvane Desrivières, Peter S. Dodds, Herta Flor, Vincent Frouin, Jürgen Gallinat, Penny Gowland, Andreas Heinz, Bernd Ittermann, Scott Mackey, Jean-Luc Martinot, Kevin Murphy, Frauke Nees, Dimitri Papadopoulos-Orfanos, Luise Poustka, Michael N. Smolka, Henrik Walter, Robert Whelan, Gunter Schumann, Hugh Garavan, IMAGEN Consortium
In the present study, we introduce just such a method, called nonlinear functional mapping (NFM), and demonstrate its application in the analysis of resting state fMRI from a 242-subject subset of the IMAGEN project, a European study of adolescents that includes longitudinal phenotypic, behavioral, genetic, and neuroimaging data.