11 citations · 21 across the 12 of their papers we have counts for
3 papers · 1 filter
Towards Trustworthy AI for Glioma Diagnosis: A Task-Aware Evaluation of Uncertainty Quantification
Gonzalo Esteban Mosquera Rojas, Sebastian R. van der Voort, Carolin M. Pirkl +3
Uncertainty Quantification (UQ) is a key requirement for trustworthy AI in high-stakes medical image analysis. In this work, we evaluate UQ in a multi-task Deep Learning framework…
Compressive MRI quantification using convex spatiotemporal priors and deep auto-encoders
Mohammad Golbabaee, Guido Buonincontri, Carolin Pirkl +4
We propose a dictionary-matching-free pipeline for multi-parametric quantitative MRI image computing. Our approach has two stages based on compressed sensing reconstruction and dee…
Deep MR Fingerprinting with total-variation and low-rank subspace priors
Mohammad Golbabaee, Carolin M. Pirkl, Marion I. Menzel +2
Deep learning (DL) has recently emerged to address the heavy storage and computation requirements of the baseline dictionary-matching (DM) for Magnetic Resonance Fingerprinting (MR…