Keywords: Fetal, Motion Correction
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.
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