7 papers
Agentic Autoresearch for CT Reconstruction
Andreas Maier, Lucas Kachelriess, Siming Bayer +4
Comparing CT reconstruction methods fairly is labor-intensive and largely manual, and many benchmarks use idealized data. We ask whether a large language model (LLM) agent can do t…
SIREM: Speech-Informed MRI Reconstruction with Learned Sampling
Md Hasan, Nyvenn Castro, Daiqi Liu +6
Real-time magnetic resonance imaging (rtMRI) of speech production enables non-invasive visualization of dynamic vocal-tract motion and is valuable for speech science and clinical a…
Beating the Style Detector: Three Hours of Agentic Research on the AI-Text Arms Race
Andreas Maier, Moritz Zaiss, Siming Bayer
Reproducing an empirical NLP study used to take weeks. Given the released data and a modern agentic-research harness, we redo every experiment of a recent ACL\,2026 study on person…
Agentic MR sequence development: leveraging LLMs with MR skills for automatic physics-informed sequence development
Moritz Zaiss, Amr Aly, Jonathan Endres +3
Purpose: Novel MR sequence developments still today allow generation of new diagnostic tools or novel imaging biomarkers. Programming MRI pulse sequences, however, is time-consumin…
Multiparameter Uncertainty Mapping in Quantitative Molecular MRI using a Physics-Structured Variational Autoencoder (PS-VAE)
Alex Finkelstein, Ron Moneta, Or Zohar +4
Quantitative imaging methods, such as magnetic resonance fingerprinting (MRF), aim to extract interpretable pathology biomarkers by estimating biophysical tissue parameters from si…
Multi-Parameter Molecular MRI Quantification using Physics-Informed Self-Supervised Learning
Alex Finkelstein, Nikita Vladimirov, Moritz Zaiss +1
Biophysical model fitting plays a key role in obtaining quantitative parameters from physiological signals and images. However, the model complexity for molecular magnetic resonanc…