Hannah Eichhorn

Orcid: 0000-0001-6980-9703

According to our database1, Hannah Eichhorn authored at least 11 papers between 2022 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
PISCO: Self-supervised k-space regularization for improved neural implicit k-space representations of dynamic MRI.
Medical Image Anal., 2026

Master Class on Reproducibility - A Student Hackathon on Advanced MRI Reconstruction Methods.
Proceedings of the Bildverarbeitung für die Medizin 2026 - Proceedings, German Conference on Medical Image Computing, Luebeck, March 15, 2026

2025
Motion-Robust T2* Quantification from Gradient Echo MRI with Physics-Informed Deep Learning.
CoRR, February, 2025

INR Meets Multi-contrast MRI Reconstruction.
Proceedings of the Reconstruction and Imaging Motion Estimation, and Graphs in Biomedical Image Analysis, 2025

2024
Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review.
IEEE Trans. Medical Imaging, February, 2024

Self-Supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representation.
CoRR, 2024

Self-supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representations.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Physics-Informed Deep Learning for Motion-Corrected Reconstruction of Quantitative Brain MRI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

2023
ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space.
Proceedings of the Deep Generative Models - Third MICCAI Workshop, 2023

Physics-Aware Motion Simulation For T2*-Weighted Brain MRI.
Proceedings of the Simulation and Synthesis in Medical Imaging, 2023

2022
Biomedical image analysis competitions: The state of current participation practice.
CoRR, 2022


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