Matthias W. Wagner

Orcid: 0000-0001-6501-839X

Affiliations:
  • Hospital for Sick Children, Toronto, ON, Canada


According to our database1, Matthias W. Wagner authored at least 13 papers between 2021 and 2025.

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

Timeline

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Links

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Bibliography

2025
Generating 3D brain tumor regions in MRI using vector-quantization Generative Adversarial Networks.
Comput. Biol. Medicine, 2025

2024
Tumor Location-weighted MRI-Report Contrastive Learning: A Framework for Improving the Explainability of Pediatric Brain Tumor Diagnosis.
CoRR, 2024

Improving Pediatric Low-Grade Neuroepithelial Tumors Molecular Subtype Identification Using a Novel AUROC Loss Function for Convolutional Neural Networks.
CoRR, 2024

Anomaly Detection in Pediatric and Adults Brain MRI with Generative Model.
Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024

2023
Motion artifact correction in fetal MRI based on a Generative Adversarial network method.
Biomed. Signal Process. Control., March, 2023

2022
Fetal Organ Anomaly Classification Network for Identifying Organ Anomalies in Fetal MRI.
Frontiers Artif. Intell., 2022

Automatic Artifact Detection Algorithm in Fetal MRI.
Frontiers Artif. Intell., 2022

A novel GAN-based paradigm for weakly supervised brain tumor segmentation of MR images.
CoRR, 2022

Tumor-location-guided CNNs for Pediatric Low-grade Glioma Molecular Biomarker Classification Using MRI.
CoRR, 2022

Open-radiomics: A Research Protocol to Make Radiomics-based Machine Learning Pipelines Reproducible.
CoRR, 2022

Improving the Segmentation of Pediatric Low-Grade Gliomas Through Multitask Learning.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

2021
Cross Attention Squeeze Excitation Network (CASE-Net) for Whole Body Fetal MRI Segmentation.
Sensors, 2021

Improving the Segmentation of Pediatric Low-Grade Gliomas through Multitask Learning.
CoRR, 2021


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