Adam Hilbert
Orcid: 0000-0003-3447-5453
According to our database1,
Adam Hilbert authored at least 18 papers
between 2019 and 2025.
Collaborative distances:
Collaborative distances:
Timeline
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Bibliography
2025
RELICT-NI: Replica Detection in Synthetic Neuroimaging - A Study on Noncontrast CT and Time-of-Flight MRA.
Neuroinformatics, December, 2025
External validation of AI-based scoring systems in the ICU: a systematic review and meta-analysis.
BMC Medical Informatics Decis. Mak., December, 2025
Research Data for a Scoping Review about the Interplay between Federated Learning and Explainable Artificial Intelligence.
Dataset, October, 2025
CoRR, February, 2025
Medical Image Anal., 2025
Proceedings of the Segmentation, Classification, and Synthesis for Brain Tumors and Traumatic Brain Injuries, 2025
2024
Perfusion parameter map generation from TOF-MRA in stroke using generative adversarial networks.
NeuroImage, 2024
Interplay between Federated Learning and Explainable Artificial Intelligence: a Scoping Review.
CoRR, 2024
2023
From Single-Hospital to Multi-Centre Applications: Enhancing the Generalisability of Deep Learning Models for Adverse Event Prediction in the ICU.
CoRR, 2023
2022
Generating 3D TOF-MRA volumes and segmentation labels using generative adversarial networks.
Medical Image Anal., 2022
Toward Sharing Brain Images: Differentially Private TOF-MRA Images With Segmentation Labels Using Generative Adversarial Networks.
Frontiers Artif. Intell., 2022
2021
Synthesizing anonymized and labeled TOF-MRA patches for brain vessel segmentation using generative adversarial networks.
Comput. Biol. Medicine, 2021
BMC Medical Imaging, 2021
2020
BRAVE-NET: Fully Automated Arterial Brain Vessel Segmentation in Patients With Cerebrovascular Disease.
Frontiers Artif. Intell., 2020
Anonymization of labeled TOF-MRA images for brain vessel segmentation using generative adversarial networks.
CoRR, 2020
On The Usage Of Average Hausdorff Distance For Segmentation Performance Assessment: Hidden Bias When Used For Ranking.
CoRR, 2020
2019
Data-efficient deep learning of radiological image data for outcome prediction after endovascular treatment of patients with acute ischemic stroke.
Comput. Biol. Medicine, 2019