4 papers
Learning to reason about rare diseases through retrieval-augmented agents
Ha Young Kim, Jun Li, Ana Beatriz Solana +4
Rare diseases represent the long tail of medical imaging, where AI models often fail due to the scarcity of representative training data. In clinical workflows, radiologists freque…
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…
Physics informed guided diffusion for accelerated multi-parametric MRI reconstruction
Perla Mayo, Carolin M. Pirkl, Alin Achim +2
We introduce MRF-DiPh, a novel physics informed denoising diffusion approach for multiparametric tissue mapping from highly accelerated, transient-state quantitative MRI acquisitio…
Denoising Diffusion Probabilistic Models for Magnetic Resonance Fingerprinting
Perla Mayo, Carolin M. Pirkl, Alin Achim +2
Magnetic Resonance Fingerprinting (MRF) is a time-efficient approach to quantitative MRI, enabling the mapping of multiple tissue properties from a single, accelerated scan. Howeve…