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Fabian Eitel
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2020 – today
- 2024
- [j1]Marta Oliveira, Rick Wilming, Benedict Clark, Céline Budding, Fabian Eitel, Kerstin Ritter
, Stefan Haufe
:
Benchmarking the influence of pre-training on explanation performance in MR image classification. Frontiers Artif. Intell. 7 (2024) - 2023
- [i9]Fabian Eitel, Marc-André Schulz, Moritz Seiler, Henrik Walter, Kerstin Ritter:
Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research. CoRR abs/2301.08525 (2023) - [i8]Marta Oliveira, Rick Wilming, Benedict Clark, Céline Budding, Fabian Eitel, Kerstin Ritter, Stefan Haufe:
Benchmark data to study the influence of pre-training on explanation performance in MR image classification. CoRR abs/2306.12150 (2023) - 2022
- [b1]Fabian Eitel:
Explainable deep learning classifiers for disease detection based on structural brain MRI data. HU Berlin, Germany, 2022 - [i7]Fabian Eitel, Anna Melkonyan, Kerstin Ritter:
Feature visualization for convolutional neural network models trained on neuroimaging data. CoRR abs/2203.13120 (2022) - 2021
- [c4]Malte Klingenberg, Didem Stark, Fabian Eitel, Kerstin Ritter:
MRI Image Registration Considerably Improves CNN-Based Disease Classification. MLCN@MICCAI 2021: 44-52 - [i6]Céline Budding, Fabian Eitel, Kerstin Ritter, Stefan Haufe:
Evaluating saliency methods on artificial data with different background types. CoRR abs/2112.04882 (2021) - 2020
- [i5]Fabian Eitel, Jan Philipp Albrecht, Martin Weygandt, Friedemann Paul, Kerstin Ritter:
Harnessing spatial homogeneity of neuroimaging data: patch individual filter layers for CNNs. CoRR abs/2007.11899 (2020)
2010 – 2019
- 2019
- [c3]Fabian Eitel, Kerstin Ritter:
Testing the Robustness of Attribution Methods for Convolutional Neural Networks in MRI-Based Alzheimer's Disease Classification. iMIMIC/ML-CDS@MICCAI 2019: 3-11 - [c2]Shikhar Srivastava
, Fabian Eitel
, Kerstin Ritter
:
Predicting Fluid Intelligence in Adolescent Brain MRI Data: An Ensemble Approach. ABCD-NP@MICCAI 2019: 74-82 - [i4]Fabian Eitel, Emily Soehler, Judith Bellmann-Strobl, Alexander Ulrich Brandt, Klemens Ruprecht, René M. Giess, Joseph Kuchling, Susanna Asseyer, Martin Weygandt, John-Dylan Haynes, Michael Scheel, Friedemann Paul, Kerstin Ritter:
Uncovering convolutional neural network decisions for diagnosing multiple sclerosis on conventional MRI using layer-wise relevance propagation. CoRR abs/1904.08771 (2019) - [i3]Fabian Eitel, Kerstin Ritter:
Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimer's disease classification. CoRR abs/1909.08856 (2019) - [i2]Fabian Eitel
, Jan Philipp Albrecht, Friedemann Paul, Kerstin Ritter:
Harnessing spatial MRI normalization: patch individual filter layers for CNNs. CoRR abs/1911.06278 (2019) - 2018
- [c1]Johannes Rieke, Fabian Eitel
, Martin Weygandt, John-Dylan Haynes, Kerstin Ritter
:
Visualizing Convolutional Networks for MRI-Based Diagnosis of Alzheimer's Disease. MLCN/DLF/iMIMIC@MICCAI 2018: 24-31 - [i1]Johannes Rieke, Fabian Eitel, Martin Weygandt, John-Dylan Haynes, Kerstin Ritter:
Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer's Disease. CoRR abs/1808.02874 (2018)
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last updated on 2024-08-05 20:22 CEST by the dblp team
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