QSMDiff: Unsupervised 3D Diffusion Models for Quantitative Susceptibility Mapping

arXiv:2403.14070v1 Announce Type: cross
Abstract: Quantitative Susceptibility Mapping (QSM) dipole inversion is an ill-posed inverse problem for quantifying magnetic susceptibility distributions from MRI tissue phases. While supervised deep learning methods have shown success in specific QSM tasks, their generalizability across different acquisition scenarios remains constrained. Recent developments in diffusion models have demonstrated potential for solving 2D medical imaging inverse problems. However, their application to 3D modalities, such as QSM, remains challenging due to high computational demands. In this work, we …

abstract acquisition arxiv cs.cv deep learning diffusion diffusion models eess.iv mapping mri physics.med-ph quantitative success tasks type unsupervised