Fabian Eitel

Orcid: 0000-0003-2630-9172

According to our database1, Fabian Eitel authored at least 13 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Benchmarking the influence of pre-training on explanation performance in MR image classification.
Frontiers Artif. Intell., 2024

2023
Benchmark data to study the influence of pre-training on explanation performance in MR image classification.
CoRR, 2023

Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research.
CoRR, 2023

2022
Explainable deep learning classifiers for disease detection based on structural brain MRI data
PhD thesis, 2022

Feature visualization for convolutional neural network models trained on neuroimaging data.
CoRR, 2022

2021
Evaluating saliency methods on artificial data with different background types.
CoRR, 2021

MRI Image Registration Considerably Improves CNN-Based Disease Classification.
Proceedings of the Machine Learning in Clinical Neuroimaging - 4th International Workshop, 2021

2020
Harnessing spatial homogeneity of neuroimaging data: patch individual filter layers for CNNs.
CoRR, 2020

2019
Harnessing spatial MRI normalization: patch individual filter layers for CNNs.
CoRR, 2019

Uncovering convolutional neural network decisions for diagnosing multiple sclerosis on conventional MRI using layer-wise relevance propagation.
CoRR, 2019

Predicting Fluid Intelligence in Adolescent Brain MRI Data: An Ensemble Approach.
Proceedings of the Adolescent Brain Cognitive Development Neurocognitive Prediction, 2019

Testing the Robustness of Attribution Methods for Convolutional Neural Networks in MRI-Based Alzheimer's Disease Classification.
Proceedings of the Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support, 2019

2018
Visualizing Convolutional Networks for MRI-Based Diagnosis of Alzheimer's Disease.
Proceedings of the Understanding and Interpreting Machine Learning in Medical Image Computing Applications, 2018


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