Anup Tuladhar

According to our database, Anup Tuladhar authored at least 13 papers between 2020 and 2023.

Collaborative distances:

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

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., May, 2023

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, January, 2023

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

Dataset, May, 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

Investigating the Vulnerability of Federated Learning-Based Diabetic Retinopathy Grade Classification to Gradient Inversion Attacks.

Christopher Nielsen, Anup Tuladhar, Nils D. Forkert

Proceedings of the Ophthalmic Medical Image Analysis - 9th International Workshop, 2022

Stroke lesion localization in 3D MRI datasets with deep reinforcement learning.

Samuel Robertson, Anup Tuladhar, Deepthi Rajashekar, Nils D. Forkert

Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 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

Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022

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

Modeling Neurodegeneration in silico With Deep Learning.

Anup Tuladhar, Jasmine A. Moore, Zahinoor Ismail, Nils D. Forkert

Frontiers Neuroinformatics, 2021

Federated Learning Using Variable Local Training for Brain Tumor Segmentation.

Anup Tuladhar, Lakshay Tyagi, Raissa Souza, Nils D. Forkert

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021

Multi-institutional Travelling Model for Tumor Segmentation in MRI Datasets.

Raissa Souza, Anup Tuladhar, Pauline Mouches, Matthias Wilms, Lakshay Tyagi, Nils D. Forkert

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021

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

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