Real-time fetal head motion tracking for prospective motion correction in fMRI

Motivation: Fetal fMRI offers critical insights into early brain functional development, but unpredictable fetal motion often distorts images, reducing data reliability and limiting research potential. Goal(s): This study aims to develop a prospective motion-correction (PMC) system for fetal fMRI to mitigate motion artifacts, enhancing data quality and enabling accurate study of fetal brain development. Approach: The PMC system integrates U-Net-based segmentation and rigid registration to track fetal head motion and adjust slice positioning in real-time. Results: PMC improved imaging quality with a 23% increase in temporal SNR and a 22% increase in Dice similarity index in an fMRI time series compared to uncorrected data. Impact: Real-time fetal brain segmentation and registration with one-TR latency enable effective motion-correction in fetal fMRI, allowing motion data from one repetition to guide adjustments in subsequent frames. This significantly enhances data reliability and usability in fetal fMRI studies.