Kerstin Ritter

According to our database, Kerstin Ritter authored at least 18 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

TLIMB - A Transfer Learning Framework for IMage Analysis of the Brain.

Marc-Andre Schulz, Jan Philipp Albrecht, Alpay Yilmaz, Alexander Koch, Dagmar Kainmüller, Ulf Leser, Kerstin Ritter

Proceedings of the Workshops of the EDBT/ICDT 2024 Joint Conference co-located with the EDBT/ICDT 2024 Joint Conference, 2024

2023

Deep neural network heatmaps capture Alzheimer's disease patterns reported in a large meta-analysis of neuroimaging studies.

Di Wang, Nicolas Honnorat, Peter T. Fox, Kerstin Ritter, Simon B. Eickhoff, Sudha Seshadri, Mohamad Habes

NeuroImage, April, 2023

Identifying confounders in deep-learning-based model predictions using DeepRepViz.

Roshan Prakash Rane, JiHoon Kim, Arjun Umesha, Didem Stark, Marc-André Schulz, Kerstin Ritter

CoRR, 2023

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

Marta Oliveira, Rick Wilming, Benedict Clark, Céline Budding, Fabian Eitel, Kerstin Ritter, Stefan Haufe

CoRR, 2023

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

Fabian Eitel, Marc-André Schulz, Moritz Seiler, Henrik Walter, Kerstin Ritter

CoRR, 2023

2022

Generating 3D TOF-MRA volumes and segmentation labels using generative adversarial networks.

Pooja Subramaniam, Tabea Kossen, Kerstin Ritter, Anja Hennemuth, Kristian Hildebrand, Adam Hilbert, Jan Sobesky, Michelle Livne, Ivana Galinovic, Ahmed A. Khalil, Jochen B. Fiebach, Dietmar Frey, Vince I. Madai

Medical Image Anal., 2022

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

Fabian Eitel, Anna Melkonyan, Kerstin Ritter

CoRR, 2022

Data Augmentation via Partial Nonlinear Registration for Brain-Age Prediction.

Marc-Andre Schulz, Alexander Koch, Vanessa Emanuela Guarino, Dagmar Kainmueller, Kerstin Ritter

Proceedings of the Machine Learning in Clinical Neuroimaging - 5th International Workshop, 2022

2021

The Collaborative Research Center FONDA.

Ulf Leser, Marcus Hilbrich, Claudia Draxl, Peter Eisert, Lars Grunske, Patrick Hostert, Dagmar Kainmüller, Odej Kao, Birte Kehr, Timo Kehrer, Christoph Koch, Volker Markl, Henning Meyerhenke, Tilmann Rabl, Alexander Reinefeld, Knut Reinert, Kerstin Ritter, Björn Scheuermann, Florian Schintke, Nicole Schweikardt, Matthias Weidlich

Datenbank-Spektrum, 2021

Evaluating saliency methods on artificial data with different background types.

Céline Budding, Fabian Eitel, Kerstin Ritter, Stefan Haufe

CoRR, 2021

MRI Image Registration Considerably Improves CNN-Based Disease Classification.

Malte Klingenberg, Didem Stark, Fabian Eitel, Kerstin Ritter

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.

Fabian Eitel, Jan Philipp Albrecht, Martin Weygandt, Friedemann Paul, Kerstin Ritter

CoRR, 2020

2019

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

Fabian Eitel, Jan Philipp Albrecht, Friedemann Paul, Kerstin Ritter

CoRR, 2019

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

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

CoRR, 2019

Predicting Fluid Intelligence in Adolescent Brain MRI Data: An Ensemble Approach.

Shikhar Srivastava, Fabian Eitel, Kerstin Ritter

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.

Fabian Eitel, Kerstin Ritter

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.

Johannes Rieke, Fabian Eitel, Martin Weygandt, John-Dylan Haynes, Kerstin Ritter

Proceedings of the Understanding and Interpreting Machine Learning in Medical Image Computing Applications, 2018

2015

Impulse control in the dorsolateral prefrontal cortex counteracts post-diet weight regain in obesity.

Martin Weygandt, Knut Mai, Esther Dommes, Kerstin Ritter, Verena Leupelt, Joachim Spranger, John-Dylan Haynes

NeuroImage, 2015