Purpose: Conventional brain MRI protocols are time-consuming, which can lead to patient discomfort and inefficiency in clinical settings. This study aims to assess the feasibility of using artificial intelligence-assisted compressed sensing (ACS) to reduce brain MRI scan time while maintaining image quality and diagnostic accuracy compared to a conventional imaging protocol.
Patients And Methods: Seventy patients from the department of neurology underwent brain MRI scans using both conventional and ACS protocols, including axial and sagittal T2-weighted fast spin-echo sequences and T2-fluid attenuated inversion recovery (FLAIR) sequence.