Keywords: Data Acquisition, Cardiovascular
Motivation: Standard cardiac cine imaging is prone to motion artifacts, especially in patients with limited breath-holding capacity.
Goal(s): Our goal was to eliminate the need for breath-holding in cine imaging, enhancing patient comfort during scans.
Approach: We leveraged data correlations across adjacent respiratory states and the k-space uniformity of different respiratory states to improve cine image quality.
Results: Compared to breath-holding techniques, our approach significantly improves image quality and myocardial wall delineation in subjects who have difficulty holding their breath.
Impact: The proposed novel cardiac cine imaging fully eliminates the requirement of breath-holding, allowing patients to breathe freely throughout the scan. This greatly improves comfort and robustness, making the entire scanning process more patient-friendly and reliable.
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