University of Wisconsin–Madison

Month: November 2024

Evaluating Large Language Models for Technical MRI Expertise: A New Study from MIMRTL

A new arXiv preprint by Alan B. McMillan, PI of MIMRTL, investigates the performance of large language models (LLMs) in answering technical MRI questions, assessing their potential to provide expert-level guidance in real-world clinical settings. The Challenge: Variability in MRI Expertise Magnetic resonance imaging (MRI) is a powerful but technically complex imaging modality. Operator skill …

New paper published: Neural Network Architectures for Self-Supervised Body Part Regression Models with Automated Localized Segmentation Application

Dr. McMillan, Principal Investigator of the MIMRTL group, in collaboration with Michael Fei, currently a medical student at Creighton University, have published a new paper in the Journal of Imaging Informatics in Medicine (JIIM) titled “Technical Note: Neural Network Architectures for Self-Supervised Body Part Regression Models with Automated Localized Segmentation Application.” This work presents advancements …

New arXiv preprint – Enhancing Interpretability in Medical Imaging with Scalable Ensembles

MIMRTL team members, graduate student Weijie Chen and Principal Investigator Alan McMillan, have published a new preprint on arXiv titled “SASWISE-UE: Segmentation and Synthesis with Interpretable Scalable Ensembles for Uncertainty Estimation”. This work introduces a framework aimed at improving the interpretability and reliability of deep learning models in medical imaging. The Challenge of Interpretability in …