Keywords: Image Reconstruction, Cardiovascular
Motivation: Explore the estimation of physiological signals using the thermal noise variance of radiofrequency coils to reconstruct free-breathing cardiac cine images.
Goal(s): Evaluate the reliability of noise variance estimations for ungated free-breathing reconstruction.
Approach: Free-breathing reconstructions with reference signals (ECG and respiratory belts) were compared to sensor-free reconstructions using the CineJENSE algorithm with implicit neural representations. The motion estimation and reconstruction for an arrhythmic patient with a bigeminy were examined.
Results: The correlation coefficient for the respiration and the F1-score of the cardiac peak detections were computed for quantitative evaluation and showed good concordance with the reference signals, even for the arrhythmic patient.
Impact: Sensor-free physiological signal estimations using noise variance from k-space data for free-breathing ungated cardiac cine reconstruction were shown for two examples (healthy volunteer and arrhythmic patient). Results showed good concordance with reference signals and the reconstructions could be performed.
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