2021/04/16 by Shouchang Guo, Jeffrey A. Fessler, Guo, Shouchang +3
Engineering · Medicine · Neuroscience · Physics and Astronomy · #Advanced MRI Techniques and Applications #Advanced Neuroimaging Techniques and Applications #FOS: Electrical engineering #FOS: Physical sciences #Functional Brain Connectivity Studies #Image and Video Processing (eess.IV) #Medical Physics (physics.med-ph) #Signal Processing (eess.SP) #eess.IV #eess.SP #electronic engineering #information engineering #physics.med-ph
paper · pdf · doi:10.48550/arxiv.2104.08395
arxiv created 2021/04/16 · openalex publication_date 2021/04/16 · arxiv updated 2021/04/20 · openalex created_date 2021/04/26 · openalex updated_date 2026/07/28
Oscillating Steady-State Imaging (OSSI) is a recent fMRI acquisition method that exploits a large and oscillating signal, and can provide high SNR fMRI. However, the oscillatory nature of the signal leads to an increased number of acquisitions. To improve temporal resolution and accurately model the nonlinearity of OSSI signals, we build the MR physics for OSSI signal generation as a regularizer for the undersampled reconstruction rather than using subspace models that are not well suited for the data. Our proposed physics-based manifold model turns the disadvantages of OSSI acquisition into advantages and enables joint reconstruction and quantification. OSSI manifold model (OSSIMM) outperforms subspace models and reconstructs high-resolution fMRI images with a factor of 12 acceleration and without spatial or temporal resolution smoothing. Furthermore, OSSIMM can dynamically quantify important physics parameters, including R2^* maps, with a temporal resolution of 150 ms.