Motion-Guided Deep Image Prior for Cardiac MRI
Journal:
arXiv
Published Date:
Dec 5, 2024
Abstract
Cardiovascular magnetic resonance imaging is a powerful diagnostic tool for
assessing cardiac structure and function. Traditional breath-held imaging
protocols, however, pose challenges for patients with arrhythmias or limited
breath-holding capacity. We introduce Motion-Guided Deep Image prior (M-DIP), a
novel unsupervised reconstruction framework for accelerated real-time cardiac
MRI. M-DIP employs a spatial dictionary to synthesize a time-dependent template
image, which is further refined using time-dependent deformation fields that
model cardiac and respiratory motion. Unlike prior DIP-based methods, M-DIP
simultaneously captures physiological motion and frame-to-frame content
variations, making it applicable to a wide range of dynamic applications. We
validate M-DIP using simulated MRXCAT cine phantom data as well as
free-breathing real-time cine and single-shot late gadolinium enhancement data
from clinical patients. Comparative analyses against state-of-the-art
supervised and unsupervised approaches demonstrate M-DIP's performance and
versatility. M-DIP achieved better image quality metrics on phantom data, as
well as higher reader scores for in-vivo patient data.
