3 papers
eess.IV2025
Identifying Alzheimer's Disease Prediction Strategies of Convolutional Neural Network Classifiers using R2* Maps and Spectral Clustering
Christian Tinauer, Maximilian Sackl, Stefan Ropele +1
Deep learning models have shown strong performance in classifying Alzheimer's disease (AD) from R2* maps, but their decision-making remains opaque, raising concerns about interpret…
eess.IV2025
Skull-stripping induces shortcut learning in MRI-based Alzheimer's disease classification
Christian Tinauer, Maximilian Sackl, Rudolf Stollberger +3
Objectives: High classification accuracy of Alzheimer's disease (AD) from structural MRI has been achieved using deep neural networks, yet the specific image features contributing…
cs.CV2024
Explainable concept mappings of MRI: Revealing the mechanisms underlying deep learning-based brain disease classification
Christian Tinauer, Anna Damulina, Maximilian Sackl +9
Motivation. While recent studies show high accuracy in the classification of Alzheimer's disease using deep neural networks, the underlying learned concepts have not been investiga…