6 papers
CUPA-T2*: Covariance-Aware Uncertainty Propagation and Alignment for T2* Mapping in Accelerated MRI
Gideon N. L. Rouwendaal, Natascha Niessen, Hannah Eichhorn +3
Quantitative T2* maps have strong potential for biomarker discovery but are limited by long scan times, rendering them impractical in clinical settings. Significant acceleration ca…
A Master Class on Reproducibility: A Student Hackathon on Advanced MRI Reconstruction Methods
Lina Felsner, Sevgi G. Kafali, Hannah Eichhorn +9
We report the design, protocol, and outcomes of a student reproducibility hackathon focused on replicating the results of three influential MRI reconstruction papers: (a) MoDL, an…
INR meets Multi-Contrast MRI Reconstruction
Natascha Niessen, Carolin M. Pirkl, Ana Beatriz Solana +6
Multi-contrast MRI sequences allow for the acquisition of images with varying tissue contrast within a single scan. The resulting multi-contrast images can be used to extract quant…
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…
Motion-Robust T2* Quantification from Gradient Echo MRI with Physics-Informed Deep Learning
Hannah Eichhorn, Veronika Spieker, Kerstin Hammernik +5
Purpose: T2* quantification from gradient echo magnetic resonance imaging is particularly affected by subject motion due to the high sensitivity to magnetic field inhomogeneities,…
PISCO: Self-Supervised k-Space Regularization for Improved Neural Implicit k-Space Representations of Dynamic MRI
Veronika Spieker, Hannah Eichhorn, Wenqi Huang +9
Neural implicit k-space representations (NIK) have shown promising results for dynamic magnetic resonance imaging (MRI) at high temporal resolutions. Yet, reducing acquisition time…