Theodoros P. Vagenas

Orcid: 0000-0003-1004-8668

According to our database1, Theodoros P. Vagenas authored at least 11 papers between 2023 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Mamba-driven MRI-to-CT Synthesis for MRI-only Radiotherapy Planning.
CoRR, March, 2026

MRIgRT real-time target tracking: TrackRAD2025 challenge report.
Medical Image Anal., 2026

A Federated FHIR-Based Interoperability Framework for Multi-Site Heart Failure Monitoring: The RETENTION Project.
Comput., 2026

2025
Towards the Automatic Segmentation, Modeling and Meshing of the Aortic Vessel Tree from Multicenter Acquisitions: An Overview of the SEG.A. 2023 Segmentation of the Aorta Challenge.
CoRR, October, 2025

Representation Learning in PET Scans Enhanced by Semantic and 3D Position Specific Characteristics.
IEEE Trans. Medical Imaging, September, 2025

eHealth literacy assessment as a promoter of user adherence in using digital health systems and services. A case study for balance physiotherapy in the TeleRehaB DSS project.
Frontiers Digit. Health, 2025

Symphy-Ten: A Hybrid Deep Learning Model for Automated Whole Spine Bone Marrow Segmentation in Whole-Body MRI.
Proceedings of the 2025 5th International Conference on Electrical, 2025

2024
FHIR-Driven Advancements in Healthcare Interoperability: Insights from the Retention Project.
Proceedings of the IEEE International Conference on Engineering, 2024

TeleRehaB DSS Project: Advancing Balance Rehabilitation Through Digital Health Technologies.
Proceedings of the IEEE International Conference on Engineering, 2024

2023
A Decision Support System for the Identification of Metastases of Metastatic Melanoma Using Whole-Body FDG PET/CT Images.
IEEE J. Biomed. Health Informatics, March, 2023

Deep Learning-Based Segmentation and Mesh Reconstruction of the Aortic Vessel Tree from CTA Images.
Proceedings of the Segmentation of the Aorta. Towards the Automatic Segmentation, Modeling, and Meshing of the Aortic Vessel Tree from Multicenter Acquisition, 2023


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