Keywords: Machine Learning/Artificial Intelligence, Data Acquisition, MRI Acceleration, Fast Acquisition, New MRI Techniques
Motivation: Acquiring a high-quality 3D brain MRI in a short time is highly desired for infants/children studies.
Goal(s): To optimize and systemically evaluate an innovative technology, AI-assisted Compressed Sensing (ACS), used in Chinese Baby Connectome Project (CBCP) with faster 3D-T1w scans and preserved imaging fidelity.
Approach: We compared ACS with conventional techniques along the entire processing pipeline. CBCP-ACS was also compared with the existing infant cohort (BCP) with P2 acceleration regarding the derived development trajectories.
Results: Results suggested that CBCP data, with halved acquisition time, had comparable quality and derived neuroscience findings to BCP, indicating that a large cohort study with ACS is mature.
Impact: Equip high-resolution 3D-T1w MRI acquisition with ACS effectively shortens the acquisition time by 44%, providing a stable and robust solution for building large-scale infant/children brain imaging cohorts. The established technique could also facilitate clinical scans and patient studies.
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