3 citations · 3 across the 5 of their papers we have counts for
4 papers · 1 filter
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…
Evaluating and Calibrating Diffusion Model-derived Uncertainty for Quantitative MRI Mapping
Shishuai Wang, Stefan Klein, Juan A. Hernandez-Tamames +1
Quantitative MRI (qMRI) provides standardised tissue parameter maps, but the reliability of deep learning-based qMRI mapping methods is often not explicitly characterised. In this…
Self-Supervised Weighted Image Guided Quantitative MRI Super-Resolution
Alireza Samadifardheris, Dirk H. J. Poot, Florian Wiesinger +2
Object: To present and evaluate Self-supervised Weighted Image Guided quantitative MRI Super-Resolution (SWIG qMRI SR), a physics-informed framework recovering high-resolution (HR)…
qMRI Diffuser: Quantitative T1 Mapping of the Brain using a Denoising Diffusion Probabilistic Model
Shishuai Wang, Hua Ma, Juan A. Hernandez-Tamames +2
Quantitative MRI (qMRI) offers significant advantages over weighted images by providing objective parameters related to tissue properties. Deep learning-based methods have demonstr…