Authors
Esther E Bron, Marion Smits, Wiesje M van der Flier, Hugo Vrenken, Frederik Barkhof, Philip Scheltens, Janne M Papma, Rebecca ME Steketee, Carolina Méndez Orellana, Rozanna Meijboom, Madalena Pinto, Joana R Meireles, Carolina Garrett, António J Bastos-Leite, Ahmed Abdulkadir, Olaf Ronneberger, Nicola Amoroso, Roberto Bellotti, David Cárdenas-Peña, Andrés M Álvarez-Meza, Chester V Dolph, Khan M Iftekharuddin, Simon F Eskildsen, Pierrick Coupé, Vladimir S Fonov, Katja Franke, Christian Gaser, Christian Ledig, Ricardo Guerrero, Tong Tong, Katherine R Gray, Elaheh Moradi, Jussi Tohka, Alexandre Routier, Stanley Durrleman, Alessia Sarica, Giuseppe Di Fatta, Francesco Sensi, Andrea Chincarini, Garry M Smith, Zhivko V Stoyanov, Lauge Sørensen, Mads Nielsen, Sabina Tangaro, Paolo Inglese, Christian Wachinger, Martin Reuter, John C van Swieten, Wiro J Niessen, Stefan Klein, Alzheimer’s Disease Neuroimaging Initiative
Publication date
2015/1/31
Journal
NeuroImage
Publisher
Academic Press
Description
Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment …
Scholar articles
EE Bron, M Smits, WM Van Der Flier, H Vrenken… - NeuroImage, 2015