Brightness-Invariant Tracking Estimation in Tagged MRI
Journal:
arXiv
Published Date:
May 23, 2025
Abstract
Magnetic resonance (MR) tagging is an imaging technique for noninvasively
tracking tissue motion in vivo by creating a visible pattern of magnetization
saturation (tags) that deforms with the tissue. Due to longitudinal relaxation
and progression to steady-state, the tags and tissue brightnesses change over
time, which makes tracking with optical flow methods error-prone. Although
Fourier methods can alleviate these problems, they are also sensitive to
brightness changes as well as spectral spreading due to motion. To address
these problems, we introduce the brightness-invariant tracking estimation
(BRITE) technique for tagged MRI. BRITE disentangles the anatomy from the tag
pattern in the observed tagged image sequence and simultaneously estimates the
Lagrangian motion. The inherent ill-posedness of this problem is addressed by
leveraging the expressive power of denoising diffusion probabilistic models to
represent the probabilistic distribution of the underlying anatomy and the
flexibility of physics-informed neural networks to estimate
biologically-plausible motion. A set of tagged MR images of a gel phantom was
acquired with various tag periods and imaging flip angles to demonstrate the
impact of brightness variations and to validate our method. The results show
that BRITE achieves more accurate motion and strain estimates as compared to
other state of the art methods, while also being resistant to tag fading.
