Markerless Tracking-Based Registration for Medical Image Motion Correction
Journal:
arXiv
Published Date:
Mar 13, 2025
Abstract
Our study focuses on isolating swallowing dynamics from interfering patient
motion in videofluoroscopy, an X-ray technique that records patients swallowing
a radiopaque bolus. These recordings capture multiple motion sources, including
head movement, anatomical displacements, and bolus transit. To enable precise
analysis of swallowing physiology, we aim to eliminate distracting motion,
particularly head movement, while preserving essential swallowing-related
dynamics. Optical flow methods fail due to artifacts like flickering and
instability, making them unreliable for distinguishing different motion groups.
We evaluated markerless tracking approaches (CoTracker, PIPs++, TAP-Net) and
quantified tracking accuracy in key medical regions of interest. Our findings
show that even sparse tracking points generate morphing displacement fields
that outperform leading registration methods such as ANTs, LDDMM, and
VoxelMorph. To compare all approaches, we assessed performance using MSE and
SSIM metrics post-registration. We introduce a novel motion correction pipeline
that effectively removes disruptive motion while preserving swallowing dynamics
and surpassing competitive registration techniques.
