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.
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.
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: Simin Li Taishan Kang Jian Wu Weikun Chen Qing Lin Zhigang Wu Jiazheng Wang Congbo Cai Shuhui Cai Source Type: research