Nils D. Forkert

82 papers B 1Journal 49Unranked 32

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A novel gradient inversion attack framework to investigate privacy vulnerabilities during retinal image-based federated learning. Medical Image Anal. Christopher Nielsen, Matthias Wilms, Nils D. Forkert
2026	J	`jnl`	Distinct visual biases affect humans and artificial intelligence in medical imaging diagnoses. npj Digit. Medicine Graham A. McLeod, Emma A. M. Stanley, Tom Rosenal, Nils D. Forkert
2025	J	`jnl`	A cross-attention-based deep learning approach for predicting functional stroke outcomes using 4D CTP imaging and clinical metadata. Medical Image Anal. Kimberly Amador, Noah Pinel, Anthony J. Winder, Jens Fiehler, Matthias Wilms, Nils D. Forkert
2025	J	`jnl`	Accounting for population structure in deep learning models for genomic analysis. J. Biomed. Informatics Gabrielle Dagasso, Matthias Wilms, Raissa Souza, Nils D. Forkert
2025	J	`jnl`	Assessment of demographic bias in retinal age prediction machine learning models. Frontiers Artif. Intell. Christopher Nielsen, Emma A. M. Stanley, Matthias Wilms, Nils D. Forkert
2025	J	`jnl`	CRAwDAD: Causal Reasoning Augmentation with Dual-Agent Debate. CoRR Finn G. Vamosi, Nils D. Forkert
2025	J	`jnl`	Csec-net: a novel deep features fusion and entropy-controlled firefly feature selection framework for leukemia classification. Health Inf. Sci. Syst. Sarmad Maqsood, Robertas Damasevicius, Rytis Maskeliunas, Nils D. Forkert, Shahab Haider, Shahid Latif
2025	J	`jnl`	Deep Learning for Retinal Degeneration Assessment: A Comprehensive Analysis of the MARIO AMD Progression Challenge. CoRR Rachid Zeghlache, Ikram Brahim, Pierre-Henri Conze, Mathieu Lamard, Mohammed El Amine Lazouni, Elaouaber Zineb Aziza, Leila Ryma Lazouni, Christopher Nielsen, Ahmad O. Ahsan, Matthias Wilms, Nils D. Forkert, Lovre Antonio Budimir, Ivana Zadro Matovinovic, Donik Vrsnak, Sven Loncaric, Philippe Zhang, Weili Jiang, Yihao Li, Yiding Hao, Markus Frohmann, Patrick Binder, Marcel Huber, Taha Emre, Teresa Araújo, Marzieh Oghbaie, Hrvoje Bogunovic, Amerens A. Bekkers, Nina M. van Liebergen, Hugo J. Kuijf, Abdul Qayyum, Moona Mazher, Steven A. Niederer, Alberto J. Beltrán-Carrero, Juan J. Gómez-Valverde, Javier Torresano-Rodríguez, Álvaro Caballero-Sastre, María J. Ledesma-Carbayo, Yosuke Yamagishi, Yi Ding, Robin Peretzke, Alexandra Ertl, Maximilian Fischer, Jessica Kächele, Sofiane Zehar, Karim Boukli Hacene, Thomas Monfort, Béatrice Cochener, Mostafa El Habib Daho, Anas-Alexis Benyoussef, Gwenolé Quellec
2025	—	`conf`	Exploring the Interplay of Label Bias with Subgroup Size and Separability: A Case Study in Mammographic Density Classification. FAIMI@MICCAI Emma A. M. Stanley, Raghav Mehta, Mélanie Roschewitz, Nils D. Forkert, Ben Glocker
2025	J	`jnl`	Exploring the interplay of label bias with subgroup size and separability: A case study in mammographic density classification. CoRR Emma A. M. Stanley, Raghav Mehta, Mélanie Roschewitz, Nils D. Forkert, Ben Glocker
2025	J	`jnl`	Self-supervised identification and elimination of harmful datasets in distributed machine learning for medical image analysis. npj Digit. Medicine Raissa Souza, Emma A. M. Stanley, Anthony J. Winder, Chris Kang, Kimberly Amador, Erik Y. Ohara, Gabrielle Dagasso, Richard Camicioli, Oury Monchi, Zahinoor Ismail, Matthias Wilms, Nils D. Forkert
2025	—	`conf`	Semi-disentangled Spatiotemporal Implicit Neural Representations of Longitudinal Neuroimaging Data for Trajectory Classification. LMID@MICCAI Agampreet Aulakh, Nils D. Forkert, Matthias Wilms
2025	J	`jnl`	Semi-disentangled spatiotemporal implicit neural representations of longitudinal neuroimaging data for trajectory classification. CoRR Agampreet Aulakh, Nils D. Forkert, Matthias Wilms
2025	—	`conf`	Simulating Inter-observer Variability Across Clinical Experience Levels for Brain Tumour Segmentation. HAIC@MICCAI Haley Gillett, Emma A. M. Stanley, Raissa Souza, Matthias Wilms, Nils D. Forkert
2025	J	`jnl`	Structural network measures reveal the emergence of heavy-tailed degree distributions in lottery ticket multilayer perceptrons. Neural Networks Chris Kang, Jasmine A. Moore, Samuel Robertson, Matthias Wilms, Emma K. Towlson, Nils D. Forkert
2025	—	`conf`	Synthetic Ground Truth Counterfactuals for Comprehensive Evaluation of Causal Generative Models in Medical Imaging. MICCAI (8) Emma A. M. Stanley, Vibujithan Vigneshwaran, Erik Y. Ohara, Finn G. Vamosi, Nils D. Forkert, Matthias Wilms
2024	—	`conf`	A Lightweight 3D Conditional Diffusion Model for Self-explainable Brain Age Prediction in Adults and Children. MLCN@MICCAI Matthias Wilms, Ahmad O. Ahsan, Erik Y. Ohara, Gabrielle Dagasso, Elizabeth Macavoy, Emma A. M. Stanley, Vibujithan Vigneshwaran, Nils D. Forkert
2024	—	`conf`	A Novel Multimodal Deep Learning Fusion Framework for Predicting Neovascular Activity Evolution in Exudative Age-Related Macular Degeneration. DIAMOND/MARIO@MICCAI Christopher Nielsen, Ahmad O. Ahsan, Matthias Wilms, Nils D. Forkert
2024	J	`jnl`	A multi-center distributed learning approach for Parkinson's disease classification using the traveling model paradigm. Frontiers Artif. Intell. Raissa Souza, Emma A. M. Stanley, Milton Camacho, Richard Camicioli, Oury Monchi, Zahinoor Ismail, Matthias Wilms, Nils D. Forkert
2024	J	`jnl`	Annotation-free prediction of treatment-specific tissue outcome from 4D CT perfusion imaging in acute ischemic stroke. Comput. Medical Imaging Graph. Alejandro Gutierrez, Kimberly Amador, Anthony J. Winder, Matthias Wilms, Jens Fiehler, Nils D. Forkert
2024	J	`jnl`	Application of a localized morphometrics approach to imaging-derived brain phenotypes for genotype-phenotype associations in pediatric mental health and neurodevelopmental disorders. Frontiers Big Data Gabrielle Dagasso, Matthias Wilms, Sarah J. MacEachern, Nils D. Forkert
2024	—	`conf`	Assessing the Impact of Sociotechnical Harms in AI-Based Medical Image Analysis. FAIMI/EPIMI@MICCAI Emma A. M. Stanley, Raissa Souza, Anthony J. Winder, Matthias Wilms, G. Bruce Pike, Gabrielle Dagasso, Christopher Nielsen, Sarah J. MacEachern, Nils D. Forkert
2024	—	`conf`	Do Sites Benefit Equally from Distributed Learning in Medical Image Analysis? FAIMI/EPIMI@MICCAI Raissa Souza, Emma A. M. Stanley, Richard Camicioli, Oury Monchi, Zahinoor Ismail, Matthias Wilms, Nils D. Forkert
2024	J	`jnl`	Foundation model-driven distributed learning for enhanced retinal age prediction. J. Am. Medical Informatics Assoc. Christopher Nielsen, Raissa Souza, Matthias Wilms, Nils D. Forkert
2024	J	`jnl`	Identifying Biases in a Multicenter MRI Database for Parkinson's Disease Classification: Is the Disease Classifier a Secret Site Classifier? IEEE J. Biomed. Health Informatics Raissa Souza, Anthony J. Winder, Emma A. M. Stanley, Vibujithan Vigneshwaran, Milton Camacho, Richard Camicioli, Oury Monchi, Matthias Wilms, Nils D. Forkert
2024	J	`jnl`	MOX-NET: Multi-stage deep hybrid feature fusion and selection framework for monkeypox classification. Expert Syst. Appl. Sarmad Maqsood, Robertas Damasevicius, Sana Shahid, Nils D. Forkert
2024	J	`jnl`	Providing clinical context to the spatio-temporal analysis of 4D CT perfusion to predict acute ischemic stroke lesion outcomes. J. Biomed. Informatics Kimberly Amador, Alejandro Gutierrez, Anthony J. Winder, Jens Fiehler, Matthias Wilms, Nils D. Forkert
2024	—	`conf`	Spatio-Temporal Deep Learning for Final Infarct Prediction Using Acute Stroke CT Perfusion Data. SWITCH/ISLES@MICCAI Kimberly Amador, Anthony J. Winder, Nils D. Forkert
2024	J	`jnl`	Towards objective and systematic evaluation of bias in artificial intelligence for medical imaging. J. Am. Medical Informatics Assoc. Emma A. M. Stanley, Raissa Souza, Anthony J. Winder, Vedant Gulve, Kimberly Amador, Matthias Wilms, Nils D. Forkert
2024	—	`conf`	Unveiling the Temporal Patterns of a 4D CTP Stroke Lesion Outcome Prediction Model Through Attention Analysis. ISBI Kimberly Amador, Anthony J. Winder, Noah Pinel, Jens Fiehler, Matthias Wilms, Nils D. Forkert
2023	—	`conf`	A Flexible Framework for Simulating and Evaluating Biases in Deep Learning-Based Medical Image Analysis. MICCAI (2) Emma A. M. Stanley, Matthias Wilms, Nils D. Forkert
2023	—	`conf`	An analysis of intensity harmonization techniques for Parkinson's multi-site MRI datasets. Computer-Aided Diagnosis Raissa Souza, Emma A. M. Stanley, Milton Camacho, Matthias Wilms, Nils D. Forkert
2023	J	`jnl`	Dementia in Convolutional Neural Networks: Using Deep Learning Models to Simulate Neurodegeneration of the Visual System. Neuroinformatics Jasmine A. Moore, Anup Tuladhar, Zahinoor Ismail, Pauline Mouches, Matthias Wilms, Nils D. Forkert
2023	J	`jnl`	Image-encoded biological and non-biological variables may be used as shortcuts in deep learning models trained on multisite neuroimaging data. J. Am. Medical Informatics Assoc. Raissa Souza, Matthias Wilms, Milton Camacho, G. Bruce Pike, Richard Camicioli, Oury Monchi, Nils D. Forkert
2023	—	`conf`	Improved multi-site Parkinson's disease classification using neuroimaging data with counterfactual inference. MIDL Vibujithan Vigneshwaran, Matthias Wilms, Milton Ivan Camacho, Raissa Souza, Nils D. Forkert
2023	J	`jnl`	Lesion-preserving unpaired image-to-image translation between MRI and CT from ischemic stroke patients. Int. J. Comput. Assist. Radiol. Surg. Alejandro Gutierrez, Anup Tuladhar, Matthias Wilms, Deepthi Rajashekar, Michael D. Hill, Andrew Demchuk, Mayank Goyal, Jens Fiehler, Nils D. Forkert
2023	—	`conf`	On the Relationship Between Open Science in Artificial Intelligence for Medical Imaging and Global Health Equity. CLIP/FAIMI/EPIMI@MICCAI Raissa Souza, Emma A. M. Stanley, Nils D. Forkert
2023	J	`jnl`	Self-supervised-RCNN for medical image segmentation with limited data annotation. Comput. Medical Imaging Graph. Banafshe Felfeliyan, Nils D. Forkert, Abhilash Rakkunedeth Hareendranathan, David Cornel, Yuyue Zhou, Gregor Kuntze, Jacob L. Jaremko, Janet Lenore Ronsky
2023	J	`jnl`	Simulation of neuroplasticity in a CNN-based in-silico model of neurodegeneration of the visual system. Frontiers Comput. Neurosci. Jasmine A. Moore, Matthias Wilms, Alejandro Gutierrez, Zahinoor Ismail, Kayson Fakhar, Fatemeh Hadaeghi, Claus C. Hilgetag, Nils D. Forkert
2023	J	`jnl`	Towards objective and systematic evaluation of bias in medical imaging AI. CoRR Emma A. M. Stanley, Raissa Souza, Anthony J. Winder, Vedant Gulve, Kimberly Amador, Matthias Wilms, Nils D. Forkert
2022	J	`jnl`	A Deep Invertible 3-D Facial Shape Model for Interpretable Genetic Syndrome Diagnosis. IEEE J. Biomed. Health Informatics Jordan J. Bannister, Matthias Wilms, J. David Aponte, David C. Katz, Ophir D. Klein, Francois P. J. Bernier, Richard A. Spritz, Benedikt Hallgrímsson, Nils D. Forkert
2022	—	`conf`	A fully convolutional neural network for explainable classification of attention deficit hyperactivity disorder. Computer-Aided Diagnosis Emma A. M. Stanley, Deepthi Rajashekar, Pauline Mouches, Matthias Wilms, Kira Plettl, Nils D. Forkert
2022	—	`conf`	A morphometrics approach for inclusion of localised characteristics from medical imaging studies into genome-wide association studies. BIBM Gabrielle Dagasso, Matthias Wilms, Nils D. Forkert
2022	J	`jnl`	A systematic comparison of generative models for medical images. Int. J. Comput. Assist. Radiol. Surg. Hristina Uzunova, Matthias Wilms, Nils D. Forkert, Heinz Handels, Jan Ehrhardt
2022	J	`jnl`	An analysis of the effects of limited training data in distributed learning scenarios for brain age prediction. J. Am. Medical Informatics Assoc. Raissa Souza, Pauline Mouches, Matthias Wilms, Anup Tuladhar, Sönke Langner, Nils D. Forkert
2022	J	`jnl`	Detecting 3D syndromic faces as outliers using unsupervised normalizing flow models. Artif. Intell. Medicine Jordan J. Bannister, Matthias Wilms, J. David Aponte, David C. Katz, Ophir D. Klein, Francois P. J. Bernier, Richard A. Spritz, Benedikt Hallgrímsson, Nils D. Forkert
2022	—	`conf`	Disentangling Factors of Morphological Variation in an Invertible Brain Aging Model. MAD@MICCAI Matthias Wilms, Pauline Mouches, Jordan J. Bannister, Sönke Langner, Nils D. Forkert
2022	—	`conf`	Disproportionate Subgroup Impacts and Other Challenges of Fairness in Artificial Intelligence for Medical Image Analysis. EPIMI/ML-CDS@MICCAI Emma A. M. Stanley, Matthias Wilms, Nils D. Forkert
2022	—	`conf`	Hybrid Spatio-Temporal Transformer Network for Predicting Ischemic Stroke Lesion Outcomes from 4D CT Perfusion Imaging. MICCAI (3) Kimberly Amador, Anthony J. Winder, Jens Fiehler, Matthias Wilms, Nils D. Forkert
2022	J	`jnl`	Invertible Modeling of Bidirectional Relationships in Neuroimaging With Normalizing Flows: Application to Brain Aging. IEEE Trans. Medical Imaging Matthias Wilms, Jordan J. Bannister, Pauline Mouches, M. Ethan MacDonald, Deepthi Rajashekar, Sönke Langner, Nils D. Forkert
2022	—	`conf`	Investigating the Vulnerability of Federated Learning-Based Diabetic Retinopathy Grade Classification to Gradient Inversion Attacks. OMIA@MICCAI Christopher Nielsen, Anup Tuladhar, Nils D. Forkert
2022	—	`conf`	Lesion-preserving unpaired image-to-image translation between MRI and CT from ischemic stroke patients. Computer-Aided Diagnosis Alejandro Gutierrez, Anup Tuladhar, Deepthi Rajashekar, Nils D. Forkert
2022	J	`jnl`	Localized Statistical Shape Models for Large-Scale Problems With Few Training Data. IEEE Trans. Biomed. Eng. Matthias Wilms, Jan Ehrhardt, Nils D. Forkert
2022	J	`jnl`	Predicting treatment-specific lesion outcomes in acute ischemic stroke from 4D CT perfusion imaging using spatio-temporal convolutional neural networks. Medical Image Anal. Kimberly Amador, Matthias Wilms, Anthony J. Winder, Jens Fiehler, Nils D. Forkert
2022	J	`jnl`	Segmentation of Tissues and Proliferating Cells in Light-Sheet Microscopy Images of Mouse Embryos Using Convolutional Neural Networks. IEEE Access Lucas Lo Vercio, Rebecca M. Green, Samuel Robertson, Sienna Guo, Andreas Dauter, Marta Marchini, Marta Vidal-García, Xiang Zhao, Anandita Mahika, Ralph S. Marcucio, Benedikt Hallgrímsson, Nils D. Forkert
2022	J	`jnl`	Self-Supervised-RCNN for Medical Image Segmentation with Limited Data Annotation. CoRR Banafshe Felfeliyan, Abhilash Rakkunedeth Hareendranathan, Gregor Kuntze, David Cornell, Nils D. Forkert, Jacob L. Jaremko, Janet Lenore Ronsky
2022	B	`conf`	Simulating progressive neurodegeneration in silico with deep artificial neural networks. CogSci Anup Tuladhar, Jasmine A. Moore, Zahinoor Ismail, Nils D. Forkert
2022	—	`conf`	Stroke lesion localization in 3D MRI datasets with deep reinforcement learning. Computer-Aided Diagnosis Samuel Robertson, Anup Tuladhar, Deepthi Rajashekar, Nils D. Forkert
2022	J	`jnl`	Weakly Supervised Medical Image Segmentation With Soft Labels and Noise Robust Loss. CoRR Banafshe Felfeliyan, Abhilash Rakkunedeth Hareendranathan, Gregor Kuntze, Stephanie Wichuk, Nils D. Forkert, Jacob L. Jaremko, Janet Lenore Ronsky
2022	—	`conf`	Weakly Supervised Medical Image Segmentation with Soft Labels and Noise Robust Loss. ICPR Workshops (2) Banafshe Felfeliyan, Abhilash Rakkunedeth Hareendranathan, Gregor Kuntze, Stephanie Wichuk, Nils D. Forkert, Jacob L. Jaremko, Janet Lenore Ronsky
2021	J	`jnl`	An Analysis of the Vulnerability of Two Common Deep Learning-Based Medical Image Segmentation Techniques to Model Inversion Attacks. Sensors Nagesh Subbanna, Matthias Wilms, Anup Tuladhar, Nils D. Forkert
2021	—	`conf`	Analysis of Generative Shape Modeling Approaches - Latent Space Properties and Interpretability. Bildverarbeitung für die Medizin Hristina Uzunova, Jesse Kruse, Paul Kaftan, Matthias Wilms, Nils D. Forkert, Heinz Handels, Jan Ehrhardt
2021	J	`jnl`	Bone and joint enhancement filtering: Application to proximal femur segmentation from uncalibrated computed tomography datasets. Medical Image Anal. Bryce A. Besler, Andrew S. Michalski, Michael T. Kuczynski, Aleena Abid, Nils D. Forkert, Steven K. Boyd
2021	J	`jnl`	Combined Atlas and Convolutional Neural Network-Based Segmentation of the Hippocampus from MRI According to the ADNI Harmonized Protocol. Sensors Samaneh Nobakht, Morgan Schaeffer, Nils D. Forkert, Sean M. Nestor, Sandra E. Black, Philip A. Barber, Alzheimer's Disease Neuroimaging Initiative
2021	J	`jnl`	Constructing High-Order Signed Distance Maps from Computed Tomography Data with Application to Bone Morphometry. CoRR Bryce A. Besler, Tannis D. Kemp, Nils D. Forkert, Steven K. Boyd
2021	—	`conf`	Federated Learning Using Variable Local Training for Brain Tumor Segmentation. BrainLes@MICCAI (2) Anup Tuladhar, Lakshay Tyagi, Raissa Souza, Nils D. Forkert
2021	J	`jnl`	Local Morphometry of Closed, Implicit Surfaces. CoRR Bryce A. Besler, Tannis D. Kemp, Andrew S. Michalski, Nils D. Forkert, Steven K. Boyd
2021	J	`jnl`	Modeling Neurodegeneration in silico With Deep Learning. Frontiers Neuroinformatics Anup Tuladhar, Jasmine A. Moore, Zahinoor Ismail, Nils D. Forkert
2021	—	`conf`	Multi-institutional Travelling Model for Tumor Segmentation in MRI Datasets. BrainLes@MICCAI (2) Raissa Souza, Anup Tuladhar, Pauline Mouches, Matthias Wilms, Lakshay Tyagi, Nils D. Forkert
2021	—	`conf`	Stroke Lesion Outcome Prediction Based on 4D CT Perfusion Data Using Temporal Convolutional Networks. MIDL Kimberly Amador, Matthias Wilms, Anthony J. Winder, Jens Fiehler, Nils D. Forkert
2021	—	`conf`	Towards Self-explainable Classifiers and Regressors in Neuroimaging with Normalizing Flows. MLCN@MICCAI Matthias Wilms, Pauline Mouches, Jordan J. Bannister, Deepthi Rajashekar, Sönke Langner, Nils D. Forkert
2020	—	`conf`	A Kernelized Multi-level Localization Method for Flexible Shape Modeling with Few Training Data. MICCAI (4) Matthias Wilms, Jan Ehrhardt, Nils D. Forkert
2020	J	`jnl`	Automatic Segmentation of Stroke Lesions in Non-Contrast Computed Tomography Datasets With Convolutional Neural Networks. IEEE Access Anup Tuladhar, Serena Schimert, Deepthi Rajashekar, Helge C. Kniep, Jens Fiehler, Nils D. Forkert
2020	—	`conf`	Bidirectional Modeling and Analysis of Brain Aging with Normalizing Flows. MLCN/RNO-AI@MICCAI Matthias Wilms, Jordan J. Bannister, Pauline Mouches, M. Ethan MacDonald, Deepthi Rajashekar, Sönke Langner, Nils D. Forkert
2020	J	`jnl`	Bidirectional Modeling and Analysis of Brain Aging with Normalizing Flows. CoRR Matthias Wilms, Jordan J. Bannister, Pauline Mouches, M. Ethan MacDonald, Deepthi Rajashekar, Sönke Langner, Nils D. Forkert
2020	J	`jnl`	Building machine learning models without sharing patient data: A simulation-based analysis of distributed learning by ensembling. J. Biomed. Informatics Anup Tuladhar, Sascha Gill, Zahinoor Ismail, Nils D. Forkert, Alzheimer's Disease Neuroimaging Initiative
2020	J	`jnl`	Fully Automatic Landmarking of Syndromic 3D Facial Surface Scans Using 2D Images. Sensors Jordan J. Bannister, Sebastian Crites, J. David Aponte, David C. Katz, Matthias Wilms, Ophir D. Klein, Francois P. J. Bernier, Richard A. Spritz, Benedikt Hallgrímsson, Nils D. Forkert
2020	—	`conf`	Quantitative Comparison of Generative Shape Models for Medical Images. Bildverarbeitung für die Medizin Hristina Uzunova, Paul Kaftan, Matthias Wilms, Nils D. Forkert, Heinz Handels, Jan Ehrhardt
2019	J	`jnl`	A methodology for generating four-dimensional arterial spin labeling MR angiography virtual phantoms. Medical Image Anal. Renzo Phellan, Thomas Lindner, Michael Helle, Alexandre X. Falcão, Thomas W. Okell, Nils D. Forkert
2019	J	`jnl`	Rapid solution of the Bloch-Torrey equation in anisotropic tissue: Application to dynamic susceptibility contrast MRI of cerebral white matter. NeuroImage Jonathan Doucette, Luxi Wei, Enedino Hernández-Torres, Christian Kames, Nils D. Forkert, Rasmus Aamand, Torben Ellegaard Lund, Brian Hansen, Alexander Rauscher
2019	—	`conf`	The Effect of Labeling Duration and Temporal Resolution on Arterial Transit Time Estimation Accuracy in 4D ASL MRA Datasets - A Flow Phantom Study. MLMECH/CVII-STENT@MICCAI Renzo Phellan, Thomas Lindner, Michael Helle, Alexandre X. Falcão, Nils D. Forkert
2018	J	`jnl`	DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes. CoRR Giles Tetteh, Velizar Efremov, Nils D. Forkert, Matthias Schneider, Jan Kirschke, Bruno Weber, Claus Zimmer, Marie Piraud, Bjoern H. Menze