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- Nils Daniel Forkert
aka: Nils D. Forkert
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Publication search results
found 100 matches
- 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: 102376 (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: 124584 (2024) - 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) - 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: 104567 (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): 2047-2054 (2024) - Kimberly Amador, Anthony J. Winder, Noah Pinel, Jens Fiehler, Matthias Wilms, Nils D. Forkert:
Unveiling the Temporal Patterns of a 4D CTP Stroke Lesion Outcome Prediction Model Through Attention Analysis. ISBI 2024: 1-5 - 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): 827-836 (2023) - 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: 102297 (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, 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): 1925-1933 (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): 45-55 (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: 289-300 - 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, Matthias Wilms, Nils D. Forkert:
A Flexible Framework for Simulating and Evaluating Biases in Deep Learning-Based Medical Image Analysis. MICCAI (2) 2023: 489-499 - 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: 1304-1317 - 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 abs/2311.02115 (2023) - 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: 105084-105100 (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: 102425 (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): 1213-1224 (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): 112-119 (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: 102610 (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): 2947-2957 (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): 3229-3239 (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): 2331-2347 (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: 3622-3628 - 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. ICPR Workshops (2) 2022: 603-617 - 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 - 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 - 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
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