Benjamin C. Wagner

According to our database1, Benjamin C. Wagner authored at least 17 papers between 2011 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2021
MEGnet: Automatic ICA-based artifact removal for MEG using spatiotemporal convolutional neural networks.
NeuroImage, 2021

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results.
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CoRR, 2021

Disparity Autoencoders for Multi-class Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021

Federated Learning for Brain Tumor Segmentation Using MRI and Transformers.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021

2020
BrainNET: Inference of Brain Network Topology Using Machine Learning.
Brain Connect., 2020

Multidimensional and Multiresolution Ensemble Networks for Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020

2019
A Deep Learning Pipeline for Automatic Skull Stripping and Brain Segmentation.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Fully Automated Brain Tumor Segmentation and Survival Prediction of Gliomas Using Deep Learning and MRI.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

Multidimensional and Multiresolution Ensemble Networks for Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

2018
Quantifying the association between white matter integrity changes and subconcussive head impact exposure from a single season of youth and high school football using 3D convolutional neural networks.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

Single season changes in resting state network power and the connectivity between regions distinguish head impact exposure level in high school and youth football players.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

2017
Automatic 1D convolutional neural network-based detection of artifacts in MEG acquired without electrooculography or electrocardiography.
Proceedings of the 2017 International Workshop on Pattern Recognition in Neuroimaging, 2017

Quantifying the Impact of Type 2 Diabetes on Brain Perfusion Using Deep Neural Networks.
Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017

Using Convolutional Neural Networks to Automatically Detect Eye-Blink Artifacts in Magnetoencephalography Without Resorting to Electrooculography.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Changes in resting state MRI networks from a single season of football distinguishes controls, low, and high head impact exposure.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Automatic identification of successful memory encoding in stereo-eeg of refractory, mesial temporal lobe epilepsy.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

2011
High Dimensional Classification of Structural MRI Alzheimer's Disease Data Based on Large Scale Regularization.
Frontiers Neuroinformatics, 2011


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