1 citations · 3 across the 3 of their papers we have counts for
4 papers · 1 filter
Harnessing spatial MRI normalization: patch individual filter layers for CNNs
Fabian Eitel, Jan Philipp Albrecht, Friedemann Paul +1
Neuroimaging studies based on magnetic resonance imaging (MRI) typically employ rigorous forms of preprocessing. Images are spatially normalized to a standard template using linear…
Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimer's disease classification
Fabian Eitel, Kerstin Ritter
Attribution methods are an easy to use tool for investigating and validating machine learning models. Multiple methods have been suggested in the literature and it is not yet clear…
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Machine learning-based imaging diagnostics has recently reached or even superseded the level of clinical experts in several clinical domains.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…