Automatic Segmentation of Stroke Lesions in Non-Contrast Computed Tomography Datasets With Convolutional Neural Networks. - Anup Tuladhar; Serena Schimert; Deepthi Rajashekar; Helge C. Kniep; Jens Fiehler; Nils D. Forkert (IEEE Access, 2020)

Building machine learning models without sharing patient data: A simulation-based analysis of distributed learning by ensembling. - Anup Tuladhar; Sascha Gill; Zahinoor Ismail; Nils D. Forkert; Alzheimer's Disease Neuroimaging Initiative (J. Biomed. Informatics, 2020)

Multi-institutional Travelling Model for Tumor Segmentation in MRI Datasets. - Raissa Souza; Anup Tuladhar; Pauline Mouches; Matthias Wilms; Lakshay Tyagi; Nils D. Forkert (BrainLes@MICCAI (2), 2021)

Federated Learning Using Variable Local Training for Brain Tumor Segmentation. - Anup Tuladhar; Lakshay Tyagi; Raissa Souza; Nils D. Forkert (BrainLes@MICCAI (2), 2021)

Modeling Neurodegeneration in silico With Deep Learning. - Anup Tuladhar; Jasmine A. Moore; Zahinoor Ismail; Nils D. Forkert (Frontiers Neuroinformatics, 2021)

An Analysis of the Vulnerability of Two Common Deep Learning-Based Medical Image Segmentation Techniques to Model Inversion Attacks. - Nagesh Subbanna; Matthias Wilms; Anup Tuladhar; Nils D. Forkert (Sensors, 2021)

Simulating progressive neurodegeneration in silico with deep artificial neural networks. - Anup Tuladhar; Jasmine A. Moore; Zahinoor Ismail; Nils D. Forkert (CogSci, 2022)

Lesion-preserving unpaired image-to-image translation between MRI and CT from ischemic stroke patients. - Alejandro Gutierrez; Anup Tuladhar; Deepthi Rajashekar; Nils D. Forkert (Computer-Aided Diagnosis, 2022)

Stroke lesion localization in 3D MRI datasets with deep reinforcement learning. - Samuel Robertson; Anup Tuladhar; Deepthi Rajashekar; Nils D. Forkert (Computer-Aided Diagnosis, 2022)

Investigating the Vulnerability of Federated Learning-Based Diabetic Retinopathy Grade Classification to Gradient Inversion Attacks. - Christopher Nielsen; Anup Tuladhar; Nils D. Forkert (OMIA@MICCAI, 2022)

An analysis of the effects of limited training data in distributed learning scenarios for brain age prediction. - Raissa Souza; Pauline Mouches; Matthias Wilms; Anup Tuladhar; Sönke Langner; Nils D. Forkert (J. Am. Medical Informatics Assoc., 2022)

Automatic Segmentation of Stroke Lesions in Non-contrast Computed Tomography Datasets with Convolutional Neural Networks. - Anup Tuladhar; Serena Schimert; Deepthi Rajashekar; Helge C. Kniep; Jens Fiehler; Nils D. Forkert (IEEE DataPort, 2022)

Dementia in Convolutional Neural Networks: Using Deep Learning Models to Simulate Neurodegeneration of the Visual System. - Jasmine A. Moore; Anup Tuladhar; Zahinoor Ismail; Pauline Mouches; Matthias Wilms; Nils D. Forkert (Neuroinformatics, 2023)

Lesion-preserving unpaired image-to-image translation between MRI and CT from ischemic stroke patients. - Alejandro Gutierrez; Anup Tuladhar; Matthias Wilms; Deepthi Rajashekar; Michael D. Hill; Andrew Demchuk; Mayank Goyal; Jens Fiehler; Nils D. Forkert (Int. J. Comput. Assist. Radiol. Surg., 2023)