Sub-second whole brain T < sub > 2 < /sub > mapping via multiband SENSE multiple overlapping-echo detachment imaging and deep learning

Phys Med Biol. 2023 Sep 19. doi: 10.1088/1361-6560/acfb71. Online ahead of print.ABSTRACTObjective.Most quantitative magnetic resonance imaging (qMRI) methods are time-consuming. Multiple overlapping-echo detachment (MOLED) imaging can achieve quantitative parametric mapping of a single slice within around one hundred milliseconds. Nevertheless, imaging the whole brain, which involves multiple slices, still takes a few seconds. To further accelerate qMRI, we introduce multiband SENSE (MB-SENSE) technology to MOLED to realize simultaneous multi-slice T2mapping.&#xD;Approach.The multiband MOLED (MB-MOLED) pulse sequence was carried out to acquire raw overlapping-echo signals, and deep learning was utilized to reconstruct T2maps. To address the issue of image quality degradation due to a high multiband factor MB, a plug-and-play (PnP) algorithm with prior denoisers (DRUNet) was applied. U-Net was used for T2map reconstruction. Numerical simulations, water phantom experiments and human brain experiments were conducted to validate our proposed approach.&#xD;Main results.Numerical simulations show that PnP algorithm effectively improved the quality of reconstructed T2maps at low signal-to-noise ratios. Water phantom experiments indicate that MB-MOLED inherited the advantages of MOLED and its results were in good agreement with the results of reference method. In vivo experiments forMB= 1, 2, 4 without the PnP algorithm, and 4 with PnP algorithm indicate that the use of PnP ...
Source: Physics in Medicine and Biology - Category: Physics Authors: Source Type: research