314 citations · 407 across the 3 of their papers we have counts for
4 papers
Harnessing spatial homogeneity of neuroimaging data: patch individual filter layers for CNNs
Fabian Eitel, Jan Philipp Albrecht, Martin Weygandt +2
Neuroimaging data, e.g. obtained from magnetic resonance imaging (MRI), is comparably homogeneous due to (1) the uniform structure of the brain and (2) additional efforts to spatia…
Uncovering convolutional neural network decisions for diagnosing multiple sclerosis on conventional MRI using layer-wise relevance propagation
Fabian Eitel, Emily Soehler, Judith Bellmann-Strobl +10
Machine learning-based imaging diagnostics has recently reached or even superseded the level of clinical experts in several clinical domains. However, classification decisions of a…
Layer-Wise Relevance Propagation for Explaining Deep Neural Network Decisions in MRI-Based Alzheimer's Disease Classification
Moritz Böhle, Fabian Eitel, Martin Weygandt +1
Deep neural networks have led to state-of-the-art results in many medical imaging tasks including Alzheimer's disease (AD) detection based on structural magnetic resonance imaging…
Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer's Disease
Johannes Rieke, Fabian Eitel, Martin Weygandt +2
Visualizing and interpreting convolutional neural networks (CNNs) is an important task to increase trust in automatic medical decision making systems. In this study, we train a 3D…