@inproceedings{05835f4762fa435eb37c15a4e88abd9c,
title = "Deliver-MPI: Diffusion Embedded-Physics Model for Magnetic Particle Imaging Reconstruction under Strong Liver Background",
abstract = "Magnetic Particle Imaging (MPI) is an emerging, radiationfree modality for quantitatively mapping superparamagnetic tracer concentration, yet liver uptake often overwhelms nearby tumor signals. We propose a physics-constrained diffusion reconstruction that injects the system matrix into a pre-trained diffusion prior, alternating denoising with a onestep data-consistency update and null-space conditioning. Without changing hardware or tracers, the method enforces physical fidelity while preserving fine structures. On simulated and measured liver-tumor phantoms, it reduces artifacts and more reliably recovers small lesions adjacent to strong liver signals compared with traditional reconstructions.",
keywords = "diffusion model, liver interference, Magnetic particle imaging",
author = "Ziwei Chen and Wenxuan Zou and Gen Shi and Jian'an Ye and Ning Sun and Zhongwei Bian and Yu An and Jie Tian",
note = "Publisher Copyright: {\textcopyright} 2026 IEEE.; 23rd IEEE International Symposium on Biomedical Imaging, ISBI 2026 ; Conference date: 08-04-2026 Through 11-04-2026",
year = "2026",
doi = "10.1109/ISBI61048.2026.11515511",
language = "英语",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
booktitle = "ISBI 2026 - 23rd IEEE International Symposium on Biomedical Imaging",
address = "美国",
}