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Excited to share our work PEPSI 🦋: pathology-enhanced contrast-agnostic representations for brain MRI. PEPSI trains on pathology-encoded synthetic data, and can directly apply to real images with various pathologies. Paper: arxiv.org/abs/2403.06227 Code: github.com/peirong26/PEPSI

PEPSI has been accepted to MICCAI 2024!  I will present PEPSI as a poster on Tuesday afternoon (Oct. 8, 15:00 - 16:30; Poster T-PM-190).  Feel free to grab a coffee (or Pepsi 🤓) with me and chat about PEPSI (and beyond)! #MICCAI2024 🇲🇦

I will attend ECCV and present our work 🧠 Brain-ID: Learning Contrast-agnostic Anatomical Representations for Brain Imaging 🤩 Come visit Brain-ID and join me @ Wed, Oct 2, 10:30am - 12:30pm; Poster 279 Paper: arxiv.org/abs/2311.16914 Code: github.com/peirong26/Brai… #ECCV2024 🇮🇹

Our latest work UNA has been accepted to #CVPR2025! UNA is the first modality-agnostic model to synthesize healthy brain anatomy from images with potential abnormal patterns --- Achieved by our novel fluid-driven anomaly generator on-the-fly. Project: github.com/peirong26/UNA

FOMO25 accepted at #MICCAI2025! 🚀 Excited to announce the first challenge at MICCAI focusing on the development of self-supervised pretraining of foundation models for brain MRI! 🧠 With access to a large-scale dataset, codebase, cash prices and multiple tracks. Read more ⬇️

I will be at #CVPR2025 Nashville 🎶 to present our work UNA 🧠 ☕️ Know more about our work or just say hi and chat with me @ Fri, Jun 13, 4-6pm; Poster #484 #CVPR