Nils D. Forkert

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 57

Top Topics

Medical Image Segmentation

Ischemic Stroke

Convolutional Neural Networks

Top Venues

Medical Imaging: Computer-Aided Diagnosis

Medical Image Anal.

Publications

Raissa Souza, Emma A. M. Stanley, Milton Camacho, Richard Camicioli, Oury Monchi, Zahinoor Ismail, Matthias Wilms, Nils D. Forkert
A multi-center distributed learning approach for Parkinson's disease classification using the traveling model paradigm. Frontiers Artif. Intell. 7 (2024)
Alejandro Gutierrez, Kimberly Amador, Anthony J. Winder, Matthias Wilms, Jens Fiehler, Nils D. Forkert
Annotation-free prediction of treatment-specific tissue outcome from 4D CT perfusion imaging in acute ischemic stroke. Comput. Medical Imaging Graph. 114 (2024)
Raissa Souza, Anthony J. Winder, Emma A. M. Stanley, Vibujithan Vigneshwaran, Milton Camacho, Richard Camicioli, Oury Monchi, Matthias Wilms, Nils D. Forkert
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 28 (4) (2024)
Sarmad Maqsood, Robertas Damasevicius, Sana Shahid, Nils D. Forkert
MOX-NET: Multi-stage deep hybrid feature fusion and selection framework for monkeypox classification. Expert Syst. Appl. 255 (2024)
Kimberly Amador, Alejandro Gutierrez, Anthony J. Winder, Jens Fiehler, Matthias Wilms, Nils D. Forkert
Providing clinical context to the spatio-temporal analysis of 4D CT perfusion to predict acute ischemic stroke lesion outcomes. J. Biomed. Informatics 149 (2024)
Banafshe Felfeliyan, Nils D. Forkert, Abhilash Rakkunedeth Hareendranathan, David Cornel, Yuyue Zhou, Gregor Kuntze, Jacob L. Jaremko, Janet Lenore Ronsky
Self-supervised-RCNN for medical image segmentation with limited data annotation. Comput. Medical Imaging Graph. 109 (2023)
Vibujithan Vigneshwaran, Matthias Wilms, Milton Ivan Camacho, Raissa Souza, Nils D. Forkert
Improved multi-site Parkinson's disease classification using neuroimaging data with counterfactual inference. MIDL (2023)
Jasmine A. Moore, Anup Tuladhar, Zahinoor Ismail, Pauline Mouches, Matthias Wilms, Nils D. Forkert
Dementia in Convolutional Neural Networks: Using Deep Learning Models to Simulate Neurodegeneration of the Visual System. Neuroinformatics 21 (1) (2023)
Raissa Souza, Matthias Wilms, Milton Camacho, G. Bruce Pike, Richard Camicioli, Oury Monchi, Nils D. Forkert
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. 30 (12) (2023)
Jasmine A. Moore, Matthias Wilms, Alejandro Gutierrez, Zahinoor Ismail, Kayson Fakhar, Fatemeh Hadaeghi, Claus C. Hilgetag, Nils D. Forkert
Simulation of neuroplasticity in a CNN-based in-silico model of neurodegeneration of the visual system. Frontiers Comput. Neurosci. 17 (2023)
Raissa Souza, Emma A. M. Stanley, Milton Camacho, Matthias Wilms, Nils D. Forkert
An analysis of intensity harmonization techniques for Parkinson's multi-site MRI datasets. Medical Imaging: Computer-Aided Diagnosis (2023)
Emma A. M. Stanley, Raissa Souza, Anthony J. Winder, Vedant Gulve, Kimberly Amador, Matthias Wilms, Nils D. Forkert
Towards objective and systematic evaluation of bias in medical imaging AI. CoRR (2023)
Alejandro Gutierrez, Anup Tuladhar, Matthias Wilms, Deepthi Rajashekar, Michael D. Hill, Andrew Demchuk, Mayank Goyal, Jens Fiehler, Nils D. Forkert
Lesion-preserving unpaired image-to-image translation between MRI and CT from ischemic stroke patients. Int. J. Comput. Assist. Radiol. Surg. 18 (5) (2023)
Raissa Souza, Emma A. M. Stanley, Nils D. Forkert
On the Relationship Between Open Science in Artificial Intelligence for Medical Imaging and Global Health Equity. CLIP/FAIMI/EPIMI@MICCAI (2023)
Emma A. M. Stanley, Matthias Wilms, Nils D. Forkert
A Flexible Framework for Simulating and Evaluating Biases in Deep Learning-Based Medical Image Analysis. MICCAI (2) (2023)
Matthias Wilms, Pauline Mouches, Jordan J. Bannister, Sönke Langner, Nils D. Forkert
Disentangling Factors of Morphological Variation in an Invertible Brain Aging Model. MAD@MICCAI (2022)
Gabrielle Dagasso, Matthias Wilms, Nils D. Forkert
A morphometrics approach for inclusion of localised characteristics from medical imaging studies into genome-wide association studies. BIBM (2022)
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
A Deep Invertible 3-D Facial Shape Model for Interpretable Genetic Syndrome Diagnosis. IEEE J. Biomed. Health Informatics 26 (7) (2022)
Alejandro Gutierrez, Anup Tuladhar, Deepthi Rajashekar, Nils D. Forkert
Lesion-preserving unpaired image-to-image translation between MRI and CT from ischemic stroke patients. Medical Imaging: Computer-Aided Diagnosis (2022)
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
Detecting 3D syndromic faces as outliers using unsupervised normalizing flow models. Artif. Intell. Medicine 134 (2022)
Christopher Nielsen, Anup Tuladhar, Nils D. Forkert
Investigating the Vulnerability of Federated Learning-Based Diabetic Retinopathy Grade Classification to Gradient Inversion Attacks. OMIA@MICCAI (2022)
Matthias Wilms, Jan Ehrhardt, Nils D. Forkert
Localized Statistical Shape Models for Large-Scale Problems With Few Training Data. IEEE Trans. Biomed. Eng. 69 (9) (2022)
Banafshe Felfeliyan, Abhilash Rakkunedeth Hareendranathan, Gregor Kuntze, David Cornell, Nils D. Forkert, Jacob L. Jaremko, Janet Lenore Ronsky
Self-Supervised-RCNN for Medical Image Segmentation with Limited Data Annotation. CoRR (2022)
Matthias Wilms, Jordan J. Bannister, Pauline Mouches, M. Ethan MacDonald, Deepthi Rajashekar, Sönke Langner, Nils D. Forkert
Invertible Modeling of Bidirectional Relationships in Neuroimaging With Normalizing Flows: Application to Brain Aging. IEEE Trans. Medical Imaging 41 (9) (2022)
Kimberly Amador, Anthony J. Winder, Jens Fiehler, Matthias Wilms, Nils D. Forkert
Hybrid Spatio-Temporal Transformer Network for Predicting Ischemic Stroke Lesion Outcomes from 4D CT Perfusion Imaging. MICCAI (3) (2022)
Raissa Souza, Pauline Mouches, Matthias Wilms, Anup Tuladhar, Sönke Langner, Nils D. Forkert
An analysis of the effects of limited training data in distributed learning scenarios for brain age prediction. J. Am. Medical Informatics Assoc. 30 (1) (2022)
Kimberly Amador, Matthias Wilms, Anthony J. Winder, Jens Fiehler, Nils D. Forkert
Predicting treatment-specific lesion outcomes in acute ischemic stroke from 4D CT perfusion imaging using spatio-temporal convolutional neural networks. Medical Image Anal. 82 (2022)
Emma A. M. Stanley, Deepthi Rajashekar, Pauline Mouches, Matthias Wilms, Kira Plettl, Nils D. Forkert
A fully convolutional neural network for explainable classification of attention deficit hyperactivity disorder. Medical Imaging: Computer-Aided Diagnosis (2022)
Emma A. M. Stanley, Matthias Wilms, Nils D. Forkert
Disproportionate Subgroup Impacts and Other Challenges of Fairness in Artificial Intelligence for Medical Image Analysis. EPIMI/ML-CDS@MICCAI (2022)
Banafshe Felfeliyan, Abhilash Rakkunedeth Hareendranathan, Gregor Kuntze, Stephanie Wichuk, Nils D. Forkert, Jacob L. Jaremko, Janet Lenore Ronsky
Weakly Supervised Medical Image Segmentation with Soft Labels and Noise Robust Loss. ICPR Workshops (2) (2022)
Hristina Uzunova, Matthias Wilms, Nils D. Forkert, Heinz Handels, Jan Ehrhardt
A systematic comparison of generative models for medical images. Int. J. Comput. Assist. Radiol. Surg. 17 (7) (2022)
Anup Tuladhar, Jasmine A. Moore, Zahinoor Ismail, Nils D. Forkert
Simulating progressive neurodegeneration in silico with deep artificial neural networks. CogSci (2022)
Banafshe Felfeliyan, Abhilash Rakkunedeth Hareendranathan, Gregor Kuntze, Stephanie Wichuk, Nils D. Forkert, Jacob L. Jaremko, Janet Lenore Ronsky
Weakly Supervised Medical Image Segmentation With Soft Labels and Noise Robust Loss. CoRR (2022)
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
Segmentation of Tissues and Proliferating Cells in Light-Sheet Microscopy Images of Mouse Embryos Using Convolutional Neural Networks. IEEE Access 10 (2022)
Samuel Robertson, Anup Tuladhar, Deepthi Rajashekar, Nils D. Forkert
Stroke lesion localization in 3D MRI datasets with deep reinforcement learning. Medical Imaging: Computer-Aided Diagnosis (2022)
Bryce A. Besler, Andrew S. Michalski, Michael T. Kuczynski, Aleena Abid, Nils D. Forkert, Steven K. Boyd
Bone and joint enhancement filtering: Application to proximal femur segmentation from uncalibrated computed tomography datasets. Medical Image Anal. 67 (2021)
Anup Tuladhar, Lakshay Tyagi, Raissa Souza, Nils D. Forkert
Federated Learning Using Variable Local Training for Brain Tumor Segmentation. BrainLes@MICCAI (2) (2021)
Samaneh Nobakht, Morgan Schaeffer, Nils D. Forkert, Sean M. Nestor, Sandra E. Black, Philip Barber, Alzheimer's Disease Neuroimaging Initiative
Combined Atlas and Convolutional Neural Network-Based Segmentation of the Hippocampus from MRI According to the ADNI Harmonized Protocol. Sensors 21 (7) (2021)
Anup Tuladhar, Jasmine A. Moore, Zahinoor Ismail, Nils D. Forkert
Modeling Neurodegeneration in silico With Deep Learning. Frontiers Neuroinformatics 15 (2021)
Matthias Wilms, Pauline Mouches, Jordan J. Bannister, Deepthi Rajashekar, Sönke Langner, Nils D. Forkert
Towards Self-explainable Classifiers and Regressors in Neuroimaging with Normalizing Flows. MLCN@MICCAI (2021)
Hristina Uzunova, Jesse Kruse, Paul Kaftan, Matthias Wilms, Nils D. Forkert, Heinz Handels, Jan Ehrhardt
Analysis of Generative Shape Modeling Approaches - Latent Space Properties and Interpretability. Bildverarbeitung für die Medizin (2021)
Bryce A. Besler, Tannis D. Kemp, Andrew S. Michalski, Nils D. Forkert, Steven K. Boyd
Local Morphometry of Closed, Implicit Surfaces. CoRR (2021)
Bryce A. Besler, Tannis D. Kemp, Nils D. Forkert, Steven K. Boyd
Constructing High-Order Signed Distance Maps from Computed Tomography Data with Application to Bone Morphometry. CoRR (2021)
Kimberly Amador, Matthias Wilms, Anthony J. Winder, Jens Fiehler, Nils D. Forkert
Stroke Lesion Outcome Prediction Based on 4D CT Perfusion Data Using Temporal Convolutional Networks. MIDL (2021)
Nagesh Subbanna, Matthias Wilms, Anup Tuladhar, Nils D. Forkert
An Analysis of the Vulnerability of Two Common Deep Learning-Based Medical Image Segmentation Techniques to Model Inversion Attacks. Sensors 21 (11) (2021)
Raissa Souza, Anup Tuladhar, Pauline Mouches, Matthias Wilms, Lakshay Tyagi, Nils D. Forkert
Multi-institutional Travelling Model for Tumor Segmentation in MRI Datasets. BrainLes@MICCAI (2) (2021)
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
Fully Automatic Landmarking of Syndromic 3D Facial Surface Scans Using 2D Images. Sensors 20 (11) (2020)
Matthias Wilms, Jordan J. Bannister, Pauline Mouches, M. Ethan MacDonald, Deepthi Rajashekar, Sönke Langner, Nils D. Forkert
Bidirectional Modeling and Analysis of Brain Aging with Normalizing Flows. CoRR (2020)
Anup Tuladhar, Sascha Gill, Zahinoor Ismail, Nils D. Forkert, Alzheimer's Disease Neuroimaging Initiative
Building machine learning models without sharing patient data: A simulation-based analysis of distributed learning by ensembling. J. Biomed. Informatics 106 (2020)
Hristina Uzunova, Paul Kaftan, Matthias Wilms, Nils D. Forkert, Heinz Handels, Jan Ehrhardt
Quantitative Comparison of Generative Shape Models for Medical Images. Bildverarbeitung für die Medizin (2020)
Anup Tuladhar, Serena Schimert, Deepthi Rajashekar, Helge C. Kniep, Jens Fiehler, Nils D. Forkert
Automatic Segmentation of Stroke Lesions in Non-Contrast Computed Tomography Datasets With Convolutional Neural Networks. IEEE Access 8 (2020)
Matthias Wilms, Jan Ehrhardt, Nils D. Forkert
A Kernelized Multi-level Localization Method for Flexible Shape Modeling with Few Training Data. MICCAI (4) (2020)
Matthias Wilms, Jordan J. Bannister, Pauline Mouches, M. Ethan MacDonald, Deepthi Rajashekar, Sönke Langner, Nils D. Forkert
Bidirectional Modeling and Analysis of Brain Aging with Normalizing Flows. MLCN/RNO-AI@MICCAI (2020)
Renzo Phellan, Thomas Lindner, Michael Helle, Alexandre X. Falcão, Nils D. Forkert
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 (2019)
Renzo Phellan, Thomas Lindner, Michael Helle, Alexandre X. Falcão, Thomas W. Okell, Nils D. Forkert
A methodology for generating four-dimensional arterial spin labeling MR angiography virtual phantoms. Medical Image Anal. 56 (2019)
Jonathan Doucette, Luxi Wei, Enedino Hernández-Torres, Christian Kames, Nils D. Forkert, Rasmus Aamand, Torben Ellegaard Lund, Brian Hansen, Alexander Rauscher
Rapid solution of the Bloch-Torrey equation in anisotropic tissue: Application to dynamic susceptibility contrast MRI of cerebral white matter. NeuroImage 185 (2019)
Giles Tetteh, Velizar Efremov, Nils D. Forkert, Matthias Schneider, Jan Kirschke, Bruno Weber, Claus Zimmer, Marie Piraud, Bjoern H. Menze
DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes. CoRR (2018)