Members of the Intelligent Imaging Innovation & Translation Lab participated in the Martinos Center Open House on December 9, 2025, joining more than 50 research groups in showcasing the breadth of scientific innovation across the Martinos Center for Biomedical Imaging.
The Open House brought together researchers, trainees, clinicians, and community members for an interactive afternoon featuring hands-on demos, posters, and discussions spanning neuroimaging, MRI physics and hardware, optical and multimodal imaging, molecular imaging, AI and computational methods, and translational research.
At our booth, the lab presented several ongoing projects focused on advancing AI-enabled MRI acquisition, reconstruction, and interpretation. Highlights included work on foundation models for generalist MRI analysis (OmniMRI), AI-accelerated quantitative MRI, multi-parametric tissue characterization, and robust reconstruction frameworks designed for clinical translation. Live demos and visualizations sparked engaging discussions around imaging efficiency, interpretability, and real-world deployment.

🧠 Foundation Models for MRI
Xingxin He and Aurora Rofena delivered a presentation titled:
“OmniMRI: A Unified Vision-Language Foundation Model for Generalist MRI Interpretation”

🌀 Modeling for Accelerated and Quantitative Imaging
Ruimin Feng and Albert Jang presented our recent work:
“BTX: Simultaneous 3D Quantitative Magnetization Transfer Imaging and Susceptibility Mapping”

Looking Ahead
Throughout the event, we had the opportunity to connect with colleagues from across the Martinos Center and beyond, exchange ideas, and explore potential collaborations. The strong interest and thoughtful questions from attendees underscored the growing enthusiasm for integrating AI and physics-guided methods to push the next generation of MRI technology.
We thank the Martinos Center leadership and organizing team for hosting a vibrant and inclusive Open House, and we look forward to continuing to share our work and contribute to the Center’s collaborative research community.

