8 citations · 9 across the 8 of their papers we have counts for
6 papers · 1 filter
From Model Based to Learned Regularization in Medical Image Registration: A Comprehensive Review
Anna Reithmeir, Veronika Spieker, Vasiliki Sideri-Lampretsa +3
Image registration is fundamental in medical imaging applications, such as disease progression analysis or radiation therapy planning. The primary objective of image registration i…
Agreement of Image Quality Metrics with Radiological Evaluation in the Presence of Motion Artifacts
Elisa Marchetto, Hannah Eichhorn, Daniel Gallichan +2
Purpose: Reliable image quality assessment is crucial for evaluating new motion correction methods for magnetic resonance imaging. In this work, we compare the performance of commo…
General Vision Encoder Features as Guidance in Medical Image Registration
Fryderyk Kögl, Anna Reithmeir, Vasiliki Sideri-Lampretsa +5
General vision encoders like DINOv2 and SAM have recently transformed computer vision. Even though they are trained on natural images, such encoder models have excelled in medical…
Data-Driven Tissue- and Subject-Specific Elastic Regularization for Medical Image Registration
Anna Reithmeir, Lina Felsner, Rickmer Braren +2
Physics-inspired regularization is desired for intra-patient image registration since it can effectively capture the biomechanical characteristics of anatomical structures. However…
Self-Supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representation
Veronika Spieker, Hannah Eichhorn, Jonathan K. Stelter +8
Neural implicit k-space representations have shown promising results for dynamic MRI at high temporal resolutions. Yet, their exclusive training in k-space limits the application o…
Physics-Informed Deep Learning for Motion-Corrected Reconstruction of Quantitative Brain MRI
Hannah Eichhorn, Veronika Spieker, Kerstin Hammernik +4
We propose PHIMO, a physics-informed learning-based motion correction method tailored to quantitative MRI. PHIMO leverages information from the signal evolution to exclude motion-c…